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<article xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" article-type="research-article" xml:lang="en"><front><journal-meta><journal-id journal-id-type="issn">2460-3945</journal-id><journal-title-group><journal-title>Forum Geografi</journal-title><abbrev-journal-title>For. Geo.</abbrev-journal-title></journal-title-group><issn pub-type="epub">2460-3945</issn><issn pub-type="ppub">0852-0682</issn><publisher><publisher-name>Universitas Muhammadiyah Surakarta</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.23917/forgeo.v39i3.10379</article-id><article-categories/><title-group><article-title>A Phenomenon of Disparity Between Regional Spatial Planning and Actual Land Use in the Citarum River Corridor, Indonesia</article-title></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5658-8064</contrib-id><name><surname>Setiawan</surname><given-names>Iwan</given-names></name><address><country>Indonesia</country><email>iwansetiawan@upi.edu</email></address><xref ref-type="aff" rid="AFF-1"/><xref ref-type="corresp" rid="cor-0"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-2735-2191</contrib-id><name><surname>Rohmat</surname><given-names>Dede</given-names></name><address><country>Indonesia</country></address><xref ref-type="aff" rid="AFF-1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0390-1635</contrib-id><name><surname>Suhendro</surname></name><address><country>Indonesia</country></address><xref ref-type="aff" rid="AFF-1"/></contrib></contrib-group><aff id="AFF-1"><institution content-type="dept">Department of Geography Education</institution><institution-wrap><institution>Universitas Pendidikan Indonesia</institution><institution-id institution-id-type="ror">https://ror.org/044b0xj37</institution-id></institution-wrap><country>Bandung 40111</country></aff><author-notes><corresp id="cor-0"><bold>Corresponding author: Iwan Setiawan</bold>, Department of Geography Education, Universitas Pendidikan Indonesia, Bandung 40111 .Email:<email>iwansetiawan@upi.edu</email></corresp></author-notes><pub-date date-type="pub" iso-8601-date="2025-9-22" publication-format="electronic"><day>22</day><month>9</month><year>2025</year></pub-date><pub-date date-type="collection" iso-8601-date="2025-9-18" publication-format="electronic"><day>18</day><month>9</month><year>2025</year></pub-date><volume>39</volume><issue>3</issue><fpage>318</fpage><lpage>346</lpage><history><date date-type="received" iso-8601-date="2025-5-14"><day>14</day><month>5</month><year>2025</year></date><date date-type="rev-recd" iso-8601-date="2025-8-15"><day>15</day><month>8</month><year>2025</year></date><date date-type="accepted" iso-8601-date="2025-9-8"><day>8</day><month>9</month><year>2025</year></date></history><permissions><copyright-statement>Copyright (c) 2025 Iwan Setiawan, Dede Rohmat, Suhendro</copyright-statement><copyright-year>2025</copyright-year><copyright-holder>Iwan Setiawan, Dede Rohmat, Suhendro</copyright-holder><license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/"><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">https://creativecommons.org/licenses/by/4.0/</ali:license_ref><license-p>This work is licensed under a Creative Commons Attribution 4.0 International License.</license-p></license></permissions><self-uri xlink:href="https://journals2.ums.ac.id/fg/article/view/10379" xlink:title="A Phenomenon of Disparity Between Regional Spatial Planning and Actual Land Use in the Citarum River Corridor, Indonesia">A Phenomenon of Disparity Between Regional Spatial Planning and Actual Land Use in the Citarum River Corridor, Indonesia</self-uri><abstract><p>The Citarum River in Indonesia is a sensitive and strategic area and is known as the dirtiest river in the world. The root of the problem lies in the existence of gaps along the corridor that are not subject to regional spatial plan (RSP). This study aims to (1) present empirical data illustrating these spatial discrepancies, and (2) analyse the underlying factors contributing to them. A spatial analytical approach was employed, integrating geospatial technologies and an Autel EVO 2 Pro V3 drone, alongside questionnaire surveys based on multi-criteria decision analysis (MCDA) (37 respondents) and in-depth interviews with local communities (35 respondents). The analysis of Sector 3 exhibited the highest disparity (49.85%) in gap area coverage, while Sector 1 showed the lowest (9.41%). A comprehensive investigation was conducted using MCDA to examine the underlying causes of these discrepancies. The findings indicate that economic, environmental and socio-demographic factors; public knowledge of RSP; the role of RSP; and community engagement with RSP are the root causes of the observed disparities along the Citarum River corridor (Sectors 1–4). We recommend aligning RSP with actual geospatial conditions; adopting adaptive zoning; enforcing laws; and enhancing public outreach for sustainable Citarum River management.</p></abstract><kwd-group><kwd>spatial disparity</kwd><kwd>current land utilization</kwd><kwd>regional development planning</kwd><kwd>accessibility and tourism</kwd><kwd>river corridor land use</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>File created by JATS Editor</meta-name><meta-value><ext-link ext-link-type="uri" xlink:href="https://jatseditor.com" xlink:title="JATS Editor">JATS Editor</ext-link></meta-value></custom-meta><custom-meta><meta-name>issue-created-year</meta-name><meta-value>2025</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec><title>1. Introduction</title><p>Water pollution in river systems has emerged as a global issue, with far-reaching implications for environmental sustainability, human health and economic stability. Several notable cases have been documented, including the Ganga River in India (<xref ref-type="bibr" rid="BIBR-108">(Sigdel et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-110">(Singh et al., 2025)</xref>; <xref ref-type="bibr" rid="BIBR-121">(Tiwari et al., 2022)</xref>); the Yangtze River in China (<xref ref-type="bibr" rid="BIBR-107">(Shu et al., 2024)</xref>; <xref ref-type="bibr" rid="BIBR-136">(Xiang et al., 2022)</xref>; <xref ref-type="bibr" rid="BIBR-141">(Xu et al., 2021)</xref>; <xref ref-type="bibr" rid="BIBR-142">(Xu et al., 2024)</xref>); the Kuning River in China (<xref ref-type="bibr" rid="BIBR-57">(Li et al., 2021)</xref>; <xref ref-type="bibr" rid="BIBR-89">(Quan et al., 2022)</xref>; <xref ref-type="bibr" rid="BIBR-126">(Wang et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-137">(Xie et al., 2022)</xref>; <xref ref-type="bibr" rid="BIBR-138">(Xie et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-142">(Xu et al., 2024)</xref>; <xref ref-type="bibr" rid="BIBR-146">(Zhang et al., 2021)</xref>) and the Buriganga River in Bangladesh (Majed <italic>et al., </italic>2022; Pandit <italic>et al., </italic>2024; Rakib <italic>et al., </italic>2024). In Indonesia, the Citarum River is frequently cited as one of the most polluted rivers in the world. It has become the focus of various national strategic programmes, as stipulated in Presidential Regulation No. 15 of 2018. By 2013, it had already attracted significant attention due to its severe pollution levels.</p><p>The Citarum River is one of the most important rivers in Indonesia, holding strategic value as both an ecological and economic corridor. It not only supports the lives of surrounding communities and ecosystems <xref ref-type="bibr" rid="BIBR-64">(Marselina et al., 2022)</xref>, but also serves as an economic lifeline for the people of West Java, through to Jakarta <xref ref-type="bibr" rid="BIBR-85">(Pratiwi et al., 2023)</xref>. Unfortunately, severe environmental degradation and increasingly complex pollution have led to the river being labeled one of the most polluted in the world <xref ref-type="bibr" rid="BIBR-81">(Permatasari et al., 2022)</xref>. As highly vulnerable ecosystems, rivers are particularly affected by anthropogenic pressures, including land conversion, pollution and development activities <xref ref-type="bibr" rid="BIBR-14">(Best &amp; Darby, 2020)</xref><xref ref-type="bibr" rid="BIBR-106">(Setiawan et al., 2024)</xref><xref ref-type="bibr" rid="BIBR-117">(Tampo et al., 2021)</xref>. Consequently, the river corridor has become a focal point for addressing these challenges.</p><p>River corridors are defined as surface areas comprising land and water units that interact directly with rivers <xref ref-type="bibr" rid="BIBR-35">(Du et al., 2025)</xref>. However, their natural flow and functions are increasingly disrupted by ecological fluctuations and human activities. Rapid economic growth and urban expansion have worsened these conditions, which are manifested in land degradation, resource depletion, pollution, and the acceleration of global warming (<xref ref-type="bibr" rid="BIBR-16">(Bosah et al., 2023)</xref>;<xref ref-type="bibr" rid="BIBR-135">(Wu et al., 2021)</xref>; <xref ref-type="bibr" rid="BIBR-144">(Yang et al., 2024)</xref>; <xref ref-type="bibr" rid="BIBR-149">(Zhao et al., 2023)</xref>). Population growth has increased social interactions, in turn correlating with increased crime rates (<xref ref-type="bibr" rid="BIBR-6">(Amirusholihin et al., 2024)</xref>; <xref ref-type="bibr" rid="BIBR-74">(Norita et al., 2024)</xref>); reduced environmental carrying capacity; and potential long-term ecosystem damage <xref ref-type="bibr" rid="BIBR-91">(Rakuasa &amp; Pakniany, 2022)</xref>, along with significant changes in land control and property rights <xref ref-type="bibr" rid="BIBR-83">(Pradoto et al., 2024)</xref>. According to the Regulation of the Ministry of Agrarian Affairs and Spatial Planning/Head of the National Land Agency Number 11 of 2021, the Regional Spatial Plan (RSP), is defined as the outcome of spatial planning for a given territory, which constitutes a geographical unit together with all related elements, the boundaries and systems of which are determined based on administrative considerations. To overcome these challenges caused by anthropogenic activities challenges, spatial planning plays a crucial role.</p><p>Spatial use must be managed with a high-quality development orientation, and mediation in spatial planning is needed as a scientific tool to mitigate land conflicts and reduce developmental inequality <xref ref-type="bibr" rid="BIBR-143">(Yanbo et al., 2023)</xref>. However, in practice, a significant gap remains between spatial plans and actual land use. Rapid urbanisation has triggered uncontrolled land use and land cover transformations, further exacerbating the mismatch between ecological space availability and demand. Ecological degradation in response to ecological demand in the Yellow River Delta region (YRDR) is gradually becoming worse <xref ref-type="bibr" rid="BIBR-148">(Zhang et al., 2024)</xref>. This situation results in adverse outcomes such as habitat loss, declining biodiversity, soil erosion, and disrupted ecosystem processes <xref ref-type="bibr" rid="BIBR-80">(Peng et al., 2023)</xref>. These gaps are especially prominent in developing countries such as Indonesia, where land use conflicts often emerge due to mounting human activity <xref ref-type="bibr" rid="BIBR-145">(Yu et al., 2025)</xref>. Furthermore, overlaps between residential and agricultural zones contribute to social segregation and the degradation of habitat quality (<xref ref-type="bibr" rid="BIBR-1">(Adam &amp; Dadi, 2024)</xref>; <xref ref-type="bibr" rid="BIBR-56">(Li et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-115">(Tadesse &amp; Baye, 2024)</xref>) Amid consensus on the seriousness of this issue, key questions remain: Why does this phenomenon occur? And how does society perceive it? These questions form the basis of the novelty of our research.</p><p>Previous studies on the Citarum River have focused on various angles, such as the impact of land cover changes on ecosystem services using machine learning <xref ref-type="bibr" rid="BIBR-42">(Hakim et al., 2025)</xref>; spatial planning based on local wisdom and community aspirations <xref ref-type="bibr" rid="BIBR-100">(Rohmat et al., 2024)</xref>; land use analysis using remote sensing <xref ref-type="bibr" rid="BIBR-71">(Mukhoriyah et al., 2023)</xref>; and landscape dynamics <xref ref-type="bibr" rid="BIBR-32">(Dede et al., 2024)</xref>. However, most of these studies have not examined the underlying causes of spatial disparity in depth. Furthermore, previous research has primarily focused on landscape changes and have not empirically investigated the driving factors within the Citarum watershed <xref ref-type="bibr" rid="BIBR-48">(Ismail et al., 2024)</xref>. Several studies have examined place-based and multi-level governance in the context of urban river restoration <xref ref-type="bibr" rid="BIBR-75">(Novalia et al., 2024)</xref>; the construction of the Citarum Living Lab as a collaborative platform for shaping a shared vision of sustainable river revitalization <xref ref-type="bibr" rid="BIBR-41">(Hadfield et al., 2024)</xref>; and flood management policies in Bandung City, including potential strategies and challenges within the Upper Citarum area <xref ref-type="bibr" rid="BIBR-105">(Setiadi et al., 2023)</xref> In addition, research has explored how different land use types affect the composition, distribution and functional guilds of macroinvertebrates in the upper reaches of the Citarum River <xref ref-type="bibr" rid="BIBR-84">(Pratiwi et al., 2024)</xref>.</p><p>Despite these contributions, many of the studies have provided no empirical analysis of the spatial planning disparity phenomenon, constituting a research gap which is addressed in this study. Therefore, our study aims to conduct an in-depth analysis of the disparity between regional spatial plans and actual conditions along the Citarum River corridor. Specifically, the objectives of the research are to (1) present a data-driven portrait of the spatial disparity along the Citarum River corridor in West Java Province, Indonesia, and (2) analyse the underlying factors contributing to this disparity. Through a comprehensive approach that integrates geospatial analysis with an in- depth investigation of causal factors, the study offers a methodological innovation. Given that our focus area is both strategic and environmentally sensitive, the application of a cross-sectoral perspective combined with an integrated analytical model constitutes significant added value. This approach positions the study as a reference sampling campaign that can inform policy- making for river restoration in other sectors of the same river system or in other rivers.</p></sec><sec><title>2. Research Methods</title><sec><title>2.1. Overview of Method</title><p>This study employed a mixed-methods approach was employed, incorporating surveys and focus group discussions (FGDs). The methodological framework included both geospatial and regional planning approaches, combined with a critical review of local community perspectives on the observed disparities. The research was implemented systematically over several stages, as visualised in <xref ref-type="fig" rid="figure-1">Figure 1</xref>.</p><fig id="figure-1" ignoredToc=""><label>Figure 1</label><caption><p>Research Procedure (Preparation, Modelling Gaps, Investigations, FGD and Dissemination).</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59209" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig></sec><sec><title>2.1. Study Area</title><p>The research was conducted in the Citarum River area, specifically in the Cirasea sub-watershed located within the administrative region of Bandung Regency, Indonesia (<xref ref-type="fig" rid="figure-2">Figure 2</xref>). Sampling was made in Sectors 1, 2, 3 and 4 to investigate the disparities between the regional spatial plan and actual land use conditions.</p><p>The justification for selecting the Cirasea sub-watershed as the research location was based on several strategic and ecological considerations. It is one of the areas experiencing considerable environmental pressure within the Citarum River Basin, primarily due to land-use conversion, intensive agricultural practices, and rapid urbanisation in Bandung Regency. Furthermore, this sub-watershed exhibits complex hydrological and topographical characteristics, making it representative of micro-scale environmental degradation dynamics within the broader context of the basin. Compared to other sub-watersheds, Cirasea also benefits from the availability of historical data and strong institutional support from local government and community stakeholders, enabling more in-depth and sustained research implementation. Consequently, the study of the Cirasea sub-watershed is not only scientifically relevant, but also practically significant in supporting rehabilitation efforts and the integrated management of the river basin.</p><fig id="figure-2" ignoredToc=""><label>Figure 2</label><caption><p>Study Area: Citarum River Corridor, Cirasea Sub-Watershed, Indonesia.</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59211" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>The sectors were determined based on a spatial approach relevant to the needs of field analysis, while also aligning with priority zoning within the framework of the Citarum Harum Program, which is a strategic government programme to revitalise the Citarum River Basin, as stipulated in Presidential Regulation No. 15 of 2018. The selection of the four sectors as part of the sampling campaign was intended to serve as a reference framework for replication in integrated watershed management in other locations. The investigation area was defined as the river corridor, which refers to the surface area consisting of land and water units that interact and are directly influenced by river dynamics (Du <italic>et al., </italic>2025). We argue that if the spatial planning within this corridor is poorly managed, it could significantly impact water quality (Rohmat <italic>et al., </italic>2024). A visualisation of the river corridor is provided in <xref ref-type="fig" rid="figure-3">Figure 3</xref>.</p><fig id="figure-3" ignoredToc=""><label>Figure 3</label><caption><p>Visualisation of the River Corridor</p></caption><p>(Source: Modified from <xref ref-type="bibr" rid="BIBR-17">(Bosché, 2012)</xref>; <xref ref-type="bibr" rid="BIBR-99">(Rohmat et al., 2024)</xref> and <xref ref-type="bibr" rid="BIBR-134">(Woessner, 2020)</xref>.</p><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59212" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig></sec><sec><title>2.2. Participants</title><p>The investigation involved a range of participants to obtain comprehensive and in-depth data. In addition to aerial photography as the primary data source, we examined the gap areas through two complementary methods: focus group discussions (FGDs) and questionnaire distribution to local residents.</p><p>1) The FGDs involved 35 participants, comprising traditional leaders, local residents, community members, and local government officials. This approach was employed to identify the underlying factors, including socio-economic and spatial planning issues, contributing to the observed gaps along the river corridor from Sector 1 to Sector 4.</p><p>2) The questionnaires were administered in each sector where the gaps occurred. Participants were selected through accidental sampling, and voluntarily agreed to complete the questionnaire and participate in in-depth interviews. This process involved a total of 37 respondents, all selected from within the ground check areas.</p></sec><sec><title>2.3. Data Collection</title><p>To identify and assess the disparity between the regional spatial plan and actual land use, a variety of data sources were processed to gain a detailed understanding of the empirical conditions. The data sources used are listed in <xref ref-type="table" rid="table-3">Table 1</xref></p><table-wrap id="table-3" ignoredToc=""><label>Table 1</label><caption><p>Research Data Collection</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Data Type</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Data requirements</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Data source</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="3" style="" align="center" valign="middle"><p>Primary Data</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Aerial photographs</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Photographs of the gap area using an Autel EVO 2 Pro V3 drone, processed using ArcGIS and Agisoft Metashape software.</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Focus group discussions</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Discussions with local communities from each of the four sectors along the Citarum River corridor (Sectors 1, 2, 3 and 4).</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Distribution of questionnaires</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>The questionnaire was constructed based on previous literature reviews (Table 2), and focused on land use and regional spatial plans along the river corridors[SG1] [f2] .</p></td></tr><tr><td colspan="1" rowspan="5" style="" align="center" valign="middle"><p>Secondary Data</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Land use in 2024</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>USGS Satellite Imagery available at <ext-link ext-link-type="uri" xlink:href="https://www.usgs.gov/landsatmissions/landsa%20t-data-access" xlink:title="https://www.usgs.gov/landsatmissions/landsa t-data-access">https://www.usgs.gov/landsatmissions/landsa t-data-access</ext-link></p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Regional spatial plan for 2011-2031</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Bandung Regency of Public Works and Public Housing (PUPR) Ministry (permission is required to access the data)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Regional administration</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Ina-Geoportal, which can be accessed at <ext-link ext-link-type="uri" xlink:href="https://tanahair.indonesia.go.id/portal-web/" xlink:title="https://tanahair.indonesia.go.id/portal-web/">https://tanahair.indonesia.go.id/portal-web/</ext-link></p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Main river flow</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>River Basin Agency (BWWS) Citarum (permission is required to access the data)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>River sectorisation (sector 1, sector 2, sector 3 and sector 4)</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Citarum River Basin Center (permission is required to access the data)</p></td></tr></tbody></table></table-wrap><p>Data were collected using geospatial technology, including the Autel EVO 2 Pro V3 drone, with further data processing through ArcGIS and Agisoft Metashape software to identify discrepancies between actual land use and the Regional Spatial Plan. The rapid advances in photogrammetry and UAV technology has made aerial data collection more practical and cost-effective, enabling quick acquisition of high-resolution surface data (<xref ref-type="bibr" rid="BIBR-44">(Hematang et al., 2024)</xref>; <xref ref-type="bibr" rid="BIBR-82">(Polat &amp; Kaya, 2021)</xref>). In addition, qualitative data were collected through FGDs and questionnaire distribution among residents, traditional leaders, community members, and local government officials to identify perceived causes of spatial disparity. The development of the instrument indicators used in the analysis is presented in <xref ref-type="table" rid="table-2">Table 2</xref>. </p><table-wrap id="table-2" ignoredToc=""><label>Table 2</label><caption><p>Indicators for Measuring the Discrepancy Between Spatial Planning and Actual Land Use</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Variable</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Symbol</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Indicator’s parameter</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Option description</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>References[SG1] [f2] </p></th></tr></thead><tbody><tr><td colspan="1" rowspan="14" style="" align="left" valign="top"><p>Land use in river corridors[SG3] </p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>1</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knowledge of river corridors</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knows or does not know[SG4] [f5] </p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-66">(Mazzorana et al., 2018)</xref>; <xref ref-type="bibr" rid="BIBR-130">(Ward &amp; Packman, 2019)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>2</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knowledge of land</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knows or does not know[SG6] [f7] </p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-96">(Richelle et al., 2018)</xref>; <xref ref-type="bibr" rid="BIBR-132">(White, 2020)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>3</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knowledge of land use</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knows or does not know[SG8] [f9] </p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-23">(Brunet et al., 2018)</xref>; <xref ref-type="bibr" rid="BIBR-65">(Mattsson et al., 2018)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>4</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knowledge of land change</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knows or does not know[SG10] [f11] </p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-22">(Brown et al., 2018)</xref>; <xref ref-type="bibr" rid="BIBR-123">(Tran et al., 2018)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>5</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knowledge of land ownership</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Owns land or does not own land</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-25">(Bush &amp; Doyon, 2023)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>6</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Actual condition of land use</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Rice fields, housing, gardens, industry, fisheries, livestock</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-149">(Zhao et al., 2023)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>7</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Land ownership permits</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Has a land ownership letter, but does not have land ownership papers</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-87">(Purnomo et al., 2019)</xref>; <xref ref-type="bibr" rid="BIBR-133">(Wily, 2018)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>8</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Land density</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Very dense, dense, or not dense</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-34">(Dong et al., 2020)</xref>; <xref ref-type="bibr" rid="BIBR-53">(Keeratikasikorn, 2018)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>9</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Land suitability with regional spatial planning</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Suitable or not suitable</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-40">(Hack et al., 2020)</xref>; <xref ref-type="bibr" rid="BIBR-103">(Salviano et al., 2021)</xref>; <xref ref-type="bibr" rid="BIBR-131">(Wei et al., 2022)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>10</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Intensity of land use socialisation activities</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Socialisation has or has not been conducted</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-79">(Pazder, 2020)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>11</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Availability of residents for relocation</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Willing or not willing</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-128">(Wang et al., 2021)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>12</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Track record of land change</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knows about land change; not aware of land change; does not care about land change</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-37">(Feng et al., 2022)</xref>; <xref ref-type="bibr" rid="BIBR-39">(Gollnow et al., 2018)</xref>; <xref ref-type="bibr" rid="BIBR-122">(Tomsett &amp; Leyland, 2019)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>13</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Impact of land change</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Environmental impact, economic impact, disaster impact, social impact</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-31">(Deberiostraat &amp; Mwaijengo, 2020)</xref>; <xref ref-type="bibr" rid="BIBR-38">(Fernandes et al., 2020)</xref>; <xref ref-type="bibr" rid="BIBR-60">(Lin et al., 2022)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>14</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Factors causing land change</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Environment, social demographics, and economy</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-29">(Cui et al., 2021)</xref>; <xref ref-type="bibr" rid="BIBR-88">(Qu et al., 2021)</xref>)</p></td></tr><tr><td colspan="1" rowspan="8" style="" align="left" valign="top"><p>Regional spatial plan along the river corridor</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>15</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knowledge of regional spatial planning</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Knows or does not know[SG12] [f13] </p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-45">(Huang et al., 2022)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>16</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Intensity of socialisation of regional spatial planning</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Has or has not been conducted</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-13">(Balta &amp; Yenil, 2019)</xref>; <xref ref-type="bibr" rid="BIBR-59">(Lin et al., 2024)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>17</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Role of spatial planning policies in society</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Very important or not important</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-66">(Mazzorana et al., 2018)</xref>; <xref ref-type="bibr" rid="BIBR-67">(Meng et al., 2019)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>18</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Conflict between society and government</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Very often, rarely occurs, or never happens</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-12">(Baigún &amp; Minotti, 2021)</xref>; <xref ref-type="bibr" rid="BIBR-60">(Lin et al., 2022)</xref>; <xref ref-type="bibr" rid="BIBR-66">(Mazzorana et al., 2018)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>19</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Incompatibility with building layout</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Has or has not occurred  </p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-49">(Jahani &amp; Barghjelveh, 2021)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>20</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Building layout permits</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Agree or disagree</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-27">(Cialdea &amp; Pompei, 2022)</xref>; <xref ref-type="bibr" rid="BIBR-51">(Jasim et al., 2024)</xref>; <xref ref-type="bibr" rid="BIBR-95">(Ren et al., 2018)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>21</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Perspective of regional spatial planning as an obstacle to regional development</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Agree or disagree</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-15">(Bonakdar &amp; Audirac, 2021)</xref>)</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>X<sub>22</sub></p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Residents are enthusiastic about regional spatial planning policies</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Agree or disagree</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>(<xref ref-type="bibr" rid="BIBR-140">(Xu et al., 2020)</xref>)</p></td></tr></tbody></table></table-wrap></sec><sec><title>2.4. Data Analysis</title><p>The field data were analysed using geospatial methods to identify areas with the most significant disparities. This was achieved by overlaying spatial planning data onto current land use data to delineate gap areas. A binary scoring system was employed: suitable areas were scored as [Equation 1] and non-suitable areas as (0), facilitating the generation of a gap map through GIS processing. As noted by <xref ref-type="bibr" rid="BIBR-112">(Somantri, 2024)</xref>, GIS tools enhance spatial analysis by providing visual elements that aid in interpreting area-related data (in hectares). In this equation, ARSP,i represents regional spatial plan areas and AFactual,I Factual land use conditions.</p><p><inline-formula><tex-math id="math-1"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle A_{\text{Gap},i} = [ A_{\text{RSP},i} - A_{\text{Factual},i} ] \end{document} ]]></tex-math></inline-formula>       (1)</p><p>Using Calculate Geometry on the attributes of the overlay polygon to obtain AGap, the result related to the most significant gap area obtained became our consideration for conducting a ground check (GC) on each sector. In this case, we defined the two terms in the gap area as follows:</p><p>1) Conforming Pattern, an area or actual condition that conforms to local spatial planning.</p><p>2) Non-conforming Pattern, an area or actual condition that does not conform to local spatial planning.</p><p>The formulation for standardising the gap area is shown in Equations 2 - 4, where  <sub> </sub> is the area of suitable land in sector   (hectares);  <sub> </sub> is the total suitable area across all sectors (hectares);  <sub> </sub> is the area of non-suitable land in sector   (hectares);  <sub> </sub> is the total non-suitable area across all sectors units (hectares);  <sub> </sub> is the area of suitable or non-suitable land in sector   (hectares); and</p><p> <sub> , </sub> is the total area of sector   (hectares).</p><p><inline-formula><tex-math id="math-2"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle Suitable\ Area\ Percentage_i = \frac{S_i}{S_{total}} \times 100% \end{document} ]]></tex-math></inline-formula>       (2)</p><p><inline-formula><tex-math id="math-3"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle Non\text{-}Suitable\ Area\ Percentage_i = \frac{N_i}{N_{total}} \times 100% \end{document} ]]></tex-math></inline-formula>       (3)</p><p><inline-formula><tex-math id="math-4"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle Area\ Percentage\ Relative\ to\ Sector_i = \frac{A_i}{A_{total,i}} \times 100% \end{document} ]]></tex-math></inline-formula>       (4)</p><p>Once the gap areas were identified, the largest priority areas (measured in hectares) were selected for ground verification. Orthomosaic data were then processed using 3D modeling techniques to visualise these locations in high detail (<xref ref-type="fig" rid="figure-4">Figure 4</xref>).</p><fig id="figure-4" ignoredToc=""><label>Figure 4</label><caption><p>Modelling of Gap Areas: (a) 2D Orthomosaic Model; (b) 3D Orthomosaic Model.</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59213" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>Orthomosaic modeling, based on UAV imagery, offers a practical alternative for producing very high-resolution images, an essential advantage for land monitoring <xref ref-type="bibr" rid="BIBR-44">(Hematang et al., 2024)</xref>. It also supports the effectiveness of field ground checks. As spatial assessments and mapping become increasingly vital in guiding and mobilising regional resources, this methodological approach aligns with best practices in regional development studies <xref ref-type="bibr" rid="BIBR-118">(Tang et al., 2025)</xref>.</p><p>Data analysis was also conducted by considering the R-squared value to identify the contribution of the influence of the gap on the position of the sector from upstream to downstream (Equations 5 - 6). Equation 5 is the general equation of linear regression <xref ref-type="bibr" rid="BIBR-70">(Montgomery et al., 2021)</xref>, where   is the slope or inclination of a line; b is the intercept or intersection point;  <sub> </sub> is the value of the independent variables or specific sectors;  <sub> </sub> is the dependent variable value or percentage of the suitable area;  ̅ is the mean of  <sub> </sub>; and  ̅ is the mean of  <sub> </sub>. The contribution value or proportion of variation   that can be explained by   ( <sup>2</sup>) (Equation 6).</p><p><inline-formula><tex-math id="math-5"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle y = ax + b \end{document} ]]></tex-math></inline-formula>       (5)</p><p>Each variable is equal to :</p><p><inline-formula><tex-math id="math-6"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle a = \frac{\sum_{i=1}^{n} (x_i - \bar{x})(y_i - \bar{y})}{\sum_{i=1}^{n} (x_i - \bar{x})^2} \end{document} ]]></tex-math></inline-formula>      (5a)</p><p><inline-formula><tex-math id="math-7"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle b = \bar{y} - a \bar{x} \end{document} ]]></tex-math></inline-formula>      (5b)</p><p><inline-formula><tex-math id="math-8"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle R^2 = \frac{\left[\sum_{i=1}^{n} (x_i - \bar{x})(y_i - \bar{y})\right]^2}{\left[\sum_{i=1}^{n} (x_i - \bar{x})^2\right]\left[\sum_{i=1}^{n} (y_i - \bar{y})^2\right]} \end{document} ]]></tex-math></inline-formula>     (6)</p><p>through the criterion of 0 ≤ R<sup>2</sup> ≤ 1</p><p>Furthermore, the processing of FGD data was conducted qualitatively by revealing the issues of spatial discrepancies along the river corridor, while the analysis of the questionnaire results was made using percentage calculations, compiled incidentally in each study sector. The formulation developed to determine the percentage of each indicator in processing community perspectives on the river corridor and the regional spatial plan was based on the Multi-Criteria Decision Analysis (MCDA) approach of <xref ref-type="bibr" rid="BIBR-111">(Sipahi &amp; Timor, 2010)</xref> and <xref ref-type="bibr" rid="BIBR-102">(Saaty, 2013)</xref> (Equations 7 - 9).</p><p><inline-formula><tex-math id="math-9"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle a'_{jk} = \frac{a_{jk}}{\sum_{p=1}^{n} a_{pk}} \end{document} ]]></tex-math></inline-formula>       (7a)</p><p><inline-formula><tex-math id="math-10"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle w_j = \frac{1}{n} \sum_{k=1}^{n} a'_{jk} \end{document} ]]></tex-math></inline-formula>       (7b)</p><p><inline-formula><tex-math id="math-11"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle \lambda_{\max} \approx \frac{1}{n} \sum_{j=1}^{n} \frac{(Aw)_j}{w_j} \, C \end{document} ]]></tex-math></inline-formula>       (7c)</p><p><inline-formula><tex-math id="math-12"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle CI = \frac{\lambda_{\max} - n}{n - 1} \end{document} ]]></tex-math></inline-formula>       (7d)</p><p><inline-formula><tex-math id="math-13"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle CR = \frac{CI}{RI} \end{document} ]]></tex-math></inline-formula>       (7e)</p><p>where  <sub> </sub> represents a comparison value between criteria jto k; '<sub> </sub> represents the normalized result value of  '<sub> </sub>;symbol n is the total criteria;and prepresents row indices on the comparison matrices. CI istheConsistency Index;CR theConsistency Ratio;and RI representstheRandom Index,or reference value from Saaty, depending on the number of criteria (Equation7).</p><p><inline-formula><tex-math id="math-14"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle r_{ij} = \frac{x_{ij} - x_{ij}}{x_{ij} - x_{ij}} \end{document} ]]></tex-math></inline-formula>       (8)</p><p><inline-formula><tex-math id="math-15"><![CDATA[ \documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle S_i = \sum_{j=1}^{n} w_j \cdot r_{ij} \end{document} ]]></tex-math></inline-formula>       (9)</p><p>where  <sub> </sub> represents the original value of alternative   for criterion  ;  <sub> </sub> is a normalized value;  <sub>  </sub>represents the final score of alternative  ;  <sub> </sub> represents the weight of criterion   from AHP; and  <sub> </sub> is the normalized value of alternative   on criterion  . A higher value for   indicates a higher priority (Equations 8 - 9).</p><p>Furthermore, qualitative analysis was conducted employing the triangulation method, integrating multiple sources of information gathered throughout the investigation. This procedure served to cross-verify the responses between the participants, thereby enhancing the validity, consistency and credibility of the findings while minimising potential bias.</p></sec></sec><sec><title>3. Results and Discussion</title><sec><title>3.1. Data Portrait of the Disparity Phenomenon</title><p>Based on the investigations, several key findings were identified, which are presented as data portraits for each sector. The purpose of these portraits is to visualise current land use, highlight areas where discrepancies exist between actual land use and the regional spatial plan, and ∑ support these findings with field data observations. Each sector is explained in detail below.</p><list list-type="order"><list-item><p>Investigation of Sector 1</p></list-item></list><p>We conducted ground checks at several locations to visualize the actual situation (<xref ref-type="fig" rid="figure-14">Figure 5</xref>). Sector 1, situated within the Kertasari District of Bandung Regency, is classified as a rural area. The inherent value of rural environments as residential settings extends beyond their agricultural and economic foundations to encompass the ecological and aesthetic benefits derived from agricultural landscapes, including scenic vistas and open spaces (<xref ref-type="bibr" rid="BIBR-30">(Dai et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-47">(Inglis et al., 2023)</xref>). However, the intricate nexus between agricultural land utilisation and demographic dynamics underscores the paramount importance of judicious land management in maintaining the long-term economic and social viability of rural communities <xref ref-type="bibr" rid="BIBR-58">(Lillemets et al., 2025)</xref>. A salient challenge in this context is land fragmentation, which can significantly impede agricultural productivity and profitability <xref ref-type="bibr" rid="BIBR-50">(Janus et al., 2023)</xref>. Furthermore, modifications in land cover patterns exert a direct influence on the volume and quality of surface water runoff, with the different imperviousness characteristics of industrial, commercial and residential land uses resulting in distinct hydrological responses (<xref ref-type="bibr" rid="BIBR-109">(Simpson et al., 2022)</xref>; <xref ref-type="bibr" rid="BIBR-119">(Taşkın &amp; Manioğlu, 2024)</xref>).</p><fig id="figure-14" ignoredToc=""><label>Figure 5</label><caption><p>Data Portrait of Sector 1 Land Use.</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59214" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>The findings show that sector 1 is dominated by plantation land use, as climate factors support the elevation in this area. If we examine the land mismatch in this region, we arrive at an area of 16.16 hectares (<xref ref-type="table" rid="table-1">Table 3</xref>), so it can be considered to be the smallest of the four sectors experiencing the phenomenon of inequality.</p><table-wrap id="table-1" ignoredToc=""><label>Table 3</label><caption><p>Portrait of Sector 1 Disparity Data.</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pattern Deviation</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Land Area (Ha)</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Location</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Conforming Pattern</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>2181.39</p></td><td colspan="1" rowspan="2" style="" align="left" valign="middle">Kertasari, Bandung Regency, Indonesia</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Non-conforming Pattern</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>16.16</p></td></tr></tbody></table></table-wrap><p>We identified several areas with disparities that are dominated by conversion to industrial activities. For example, the field findings indicate that tea factories have been built since the Dutch Colonial era (<xref ref-type="fig" rid="figure-6">Figure 6</xref>a). Moreover, anthropogenic activities, particularly the presence of residential areas, constitute the largest gap area, covering 11.01 ha out of the total 16.16 ha. Between 2019 and 2023, the Kertasari Subdistrict Statistics Agency reported continuous population growth, increasing from 71,779 inhabitants in 2019, to 71,992 in 2020, 72,787 in 2021, 73,836 in 2022, and 74,511 in 2023 <xref ref-type="bibr" rid="BIBR-18">(B.P.S., 2024)</xref>. This population growth is a key driver of the spatial gap in Sector 1.</p><p>We identified several contributing factors were identified, including: (a) residential expansion, driven by the development of housing complexes in South Bandung <xref ref-type="bibr" rid="BIBR-61">(Hakim et al., 2019)</xref>; (b) urbanisation and increased population mobility <xref ref-type="bibr" rid="BIBR-6">(Amirusholihin et al., 2024)</xref>, coupled with improved infrastructure and public services such as schools, healthcare facilities and enhanced accessibility; and (c) economic expansion, including the development of plantation estates <xref ref-type="bibr" rid="BIBR-61">(Hakim et al., 2019)</xref>. The appeal of exotic tourism destinations, such as “0 Km Citarum,” and picturesque plantation landscapes draws visitors to the area, some of whom settle there and invest in the development of lodging facilities.</p><fig id="figure-6" ignoredToc=""><label>Figure 6</label><caption><p>Documentary portrait of the Kertasari area in Sector 1: (a) Portrait of the Kertasari settlement; (b) Example of easy accessibility, categorised as good; (c) Portrait of Cisanti 0 Km Citarum; (d) Portrait of the Kertasarie, a tea factory from the Dutch colonial era.</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59215" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>Below, the dominant land use in the gap area in Sector 1 is described quantitatively. Specifically, the land area disparity is presented in <xref ref-type="table" rid="table-4">Table 4</xref>. The phenomenon of disparity areas is largely dominated by the existence of residential areas, followed by industrial areas.</p><fig id="figure-7" ignoredToc=""><label>Figure 7</label><caption><p>Sector 1 Investigation Point Distribution: (a) Land Disparities from Wet Agriculture to Industrial Areas (GC 1.1); b) Land Disparities from Wet Agriculture to Settlements (GC 1.2); and (c) Land Disparities from Residential Areas to Industrial Areas (GC 1.3).</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59216" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><table-wrap id="table-4" ignoredToc=""><label>Table 4</label><caption><p>Sector 1 Disparity Data Specifications.</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Spatial Planning</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Actual Conditions</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pattern deviation</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>∑</p><p>(Ha)</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>AOI</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Non-conforming</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">2.16</td><td colspan="1" rowspan="1" style="" align="left" valign="top">QC 1.1</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Non-conforming</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">11.01</td><td colspan="1" rowspan="1" style="" align="left" valign="top">QC 1.2</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Residential Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Non-conforming</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">2.35</td><td colspan="1" rowspan="1" style="" align="left" valign="top">QC 1.3</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Protected Forest</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Non-conforming</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">0.004</td><td colspan="1" rowspan="1" style="" align="left" valign="top">None</td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Annual Crop Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Non-conforming</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">0.62</td><td colspan="1" rowspan="1" style="" align="left" valign="top">None</td></tr></tbody></table></table-wrap><p>This situation depicted in <xref ref-type="fig" rid="figure-7">Figure 7</xref> is further compounded by the progressive conversion of agricultural land to industrial zones, engendering substantial concerns regarding food security, diminished agricultural output, and a contraction of the agricultural labour force <xref ref-type="bibr" rid="BIBR-150">(Zhuge et al., 2023)</xref>. Numerous developing nations, including India and China, have witnessed extensive transformations of agricultural land for industrial purposes concomitant with periods of economic expansion <xref ref-type="bibr" rid="BIBR-150">(Zhuge et al., 2023)</xref> However, imprudent land conversion practices can render previously productive land economically unviable and may even exacerbate global warming and climate change (<xref ref-type="bibr" rid="BIBR-46">(Huang et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-150">(Zhuge et al., 2023)</xref>). Moreover, industrial expansion poses a considerable threat to ecological systems; intensifies the impacts of climate change; and leads to a reduction in biodiversity (<xref ref-type="bibr" rid="BIBR-54">(Kennedy et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-103">(Salviano et al., 2021)</xref>). Since the 20th century, while urbanisation and industrialisation have served as primary drivers of economic development, environmentally unsustainable governmental policies have facilitated the widespread proliferation of construction land and a corresponding depletion of natural resource endowments <xref ref-type="bibr" rid="BIBR-138">(Xie et al., 2023)</xref>.</p><list list-type="order"><list-item><p>Investigation of Sector 2</p></list-item></list><p>In contrast to Sector 1, Sector 2 is predominantly characterised by its agrarian landscape (<xref ref-type="fig" rid="figure-11">Figure 8</xref>), exhibiting a notable prevalence of paddy cultivation, encompassing both irrigated and rain-fed systems, alongside open fields and moorland. However, preliminary indications suggest a nascent trend towards the development of residential settlements, and an associated reduction in forested areas within this sector. While dedicated industrial zones are not currently discernible, the increasing presence of settlements may serve as a leading indicator of future land conversion pressures, particularly in the absence of stringent regulatory frameworks governing land use.</p><fig id="figure-11" ignoredToc=""><label>Figure 8</label><caption><p>Data Portrait of Sector 2 Land Use.</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59217" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>The data overview highlights the dominance of land in Sector 2, primarily consisting of rice fields (37%), which serve as the primary source of livelihood due to the area’s highly fertile morphology and climate which is well-suited for rice cultivation. Furthermore, we also identified a gap area totalling 20.14 hectares ( <xref ref-type="table" rid="table-5">Table 5</xref>), a higher figure than in Sector 1.</p><table-wrap id="table-5" ignoredToc=""><label>Table 5</label><caption><p>Sector 2 Disparity Investigation.</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pattern Deviation</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Land Area (Ha)</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Location</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Conforming Pattern</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1399.65</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Kertasari-Pacet,</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Non-conforming Pattern</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>20.14</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Bandung Regency, Indonesia</td></tr></tbody></table></table-wrap><p>Administratively, Sector 2 covers parts of Kertasari and Pacet. Population growth in both areas was identified based on data from the Central Statistics Agency in Pacet Subdistrict, which showed a total population of 114,075 in 2019; 115,066 in 2020; 120,997 in 2021; 124,594 in 2022; and 126,819 in 2023 <xref ref-type="bibr" rid="BIBR-19">(B.P.S., 2024)</xref>. These data indicate that the population growth rate continues to increase year by year. Similar to Kertasari, Pacet is an area with a cool climate and tourist destinations that support its appeal, making it no surprise that the region is one of the targets for urbanisation by the city of Bandung. Urbanisation is considered as an increase in the number and density of urban populations, causing changes in rural life <xref ref-type="bibr" rid="BIBR-113">(Suhendro &amp; G. M. K. A, 2021)</xref>. This is closely related to the current conditions at both locations. Additionally, improvements in the quality of life, such as education, healthcare and the economy, including the presence of cafes, Pertamina stations, markets and others, play a role in the process (<xref ref-type="fig" rid="figure-9">Figure 9</xref>). These three Human Development Index factors can trigger inbound migration, while also driving natural growth.</p><fig id="figure-9" ignoredToc=""><label>Figure 9</label><caption><p>Documentary portrait of the Kertasari and Pacet areas in Sector 2: (a) Local residents' economic activities utilising the Citarum River, such as fishing for small fish; (b) Portrait of the cool climate in Pacet; (c) Portrait of the existence cafe in one of the local residents' economic expansion areas.</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59218" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>The land use dominance occurring in the gap area for sector 2 was identified, and is presented in <xref ref-type="table" rid="table-6">Table 6</xref>. Despite the general conformity of Sector 2 land use with the Regional Spatial Plan (RSP), preliminary analysis revealed evidence of unauthorised land conversion affecting approximately 20.14 hectares. These deviations from the designated land use predominantly involve the transformation of irrigated agricultural land and production forests into residential zones. Such non-compliance warrants diligent monitoring and follow-up due to its potential ramifications for local food security, ecosystem equilibrium, and the integrity of regional spatial governance. Furthermore, our investigation identified several instances of spatial discrepancies within the Citarum River corridor, which are visually documented in <xref ref-type="fig" rid="figure-10">Figure 10</xref>.</p><table-wrap id="table-6" ignoredToc=""><label>Table 6</label><caption><p>Land Area Specifications (Sector 2).</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Spatial Planning</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Actual Conditions</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pattern Deviation</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>∑</p><p>(Ha)</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>AOI</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>8.40</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>QC 2.1</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>10.37</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>QC 2.2</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Production Forest</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1.37</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>QC 2.3</p></td></tr></tbody></table></table-wrap><p>Within Sector 2, specifically along the Kertasari to Pacet corridor in Bandung Regency, discernible instances of land-use change from wet agricultural land to residential areas were observed. This transformation has precipitated a range of environmental and social consequences. Parallels can be drawn with research conducted in the Johor River Basin, Malaysia, which indicated that such conversions can significantly alter river morphology, modify hydrological flow regimes, and raise the potential for fluvial inundation <xref ref-type="bibr" rid="BIBR-52">(Kang &amp; Kanniah, 2022)</xref>. Furthermore, alterations in land cover have been shown to exert a substantial influence on land surface temperature (LST), a critical determinant in the dynamics of climate change <xref ref-type="bibr" rid="BIBR-114">(Tabassum et al., 2023)</xref>. Consequently, for governments in the Southern Hemisphere to formulate efficacious mitigation and adaptation strategies, a comprehensive approach is imperative, one that explicitly addresses the intricate interdependencies between land use and land cover change (LULC) and increased surface temperatures <xref ref-type="bibr" rid="BIBR-114">(Tabassum et al., 2023)</xref>.</p><p>It is crucial to acknowledge that rural transformation driven by land conversion engenders significant shifts in the socio-economic fabric of the region. This process encompasses not only the displacement of traditional agricultural practices, but also a fundamental redefinition of rural area functions, patterns of inter- and intra-sectoral population migration, and the development of new interrelationships between the primary (agricultural) sector and secondary/tertiary sectors, such as residential and service industries <xref ref-type="bibr" rid="BIBR-127">(Wang et al., 2023)</xref>. These multifaceted changes necessitate the adoption of more integrated spatial planning frameworks to effectively minimise adverse impacts on both the environment and rural communities.</p><fig id="figure-10" ignoredToc=""><label>Figure 10</label><caption><p>Sector 2 Investigation Point Distribution: (a) Land Disparities from Wet Agriculture to Settlements (GC 2.1); (b) Land Disparities from Wet Agriculture to Settlements (GC 2.2); (c) Land Gaps from Wet Agriculture to Settlements (GC 2.3).</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59199" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><list list-type="order"><list-item><p>Investigation of Sector 3</p></list-item></list><p>Sector 3 is characterised by a predominance of agricultural land (<xref ref-type="fig" rid="figure-8">Figure 11</xref>), with rice fields constituting the most significant proportion (42.55%), followed by moorlands and open fields. However, the significant presence of settlements, accounting for approximately 32% of the land cover, warrants further investigation due to its potential to drive increasingly widespread conversion of agricultural land. In contrast to Sector 2, the limited extent of industrial land conversion suggests that this sector has thus far remained relatively unaffected by industrial development pressures.</p><fig id="figure-8" ignoredToc=""><label>Figure 11</label><caption><p>Data Portrait of Sector 3 Land Use.</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59200" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>While the majority of land use in Sector 3 aligns with the prevailing spatial plan, a notable deviation of approximately 85.6 hectares was identified. This discrepancy is significant enough to necessitate an in-depth analysis to ascertain its causes and potential consequences. Similar to the preceding sectors, several locations of spatial incongruities within the Citarum River corridor have been identified and are visually represented in <xref ref-type="fig" rid="figure-13">Figure 13</xref>. Detailed specifications regarding the land area distribution within this sector are presented in <xref ref-type="table" rid="table-7">Table 7</xref>.Bandung Regency, Indonesia</p><table-wrap id="table-7" ignoredToc=""><label>Table 7</label><caption><p>Sector 3 Disparity Investigation.</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pattern Deviation</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Land Area (Ha)</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Location</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Conforming Pattern</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">1530.18</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Ibun-Majalaya,</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Non-conforming Pattern</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">85.60</td><td colspan="1" rowspan="1" style="" align="left" valign="top">Bandung Regency, Indonesia</td></tr></tbody></table></table-wrap><p>The investigation of Sector 3 covers two administrative districts, Ibun and Majalaya. The disparities in this sector are more dominant in residential areas, industrial areas and rice fields, which means that the area can be described as undergoing intensive urbanisation. Therefore, it is no surprise that the population growth rate has continued to rise over the past four years, starting from a total of 87,020 people in 2020, to 90,026 in 2021, 92,552 in 2022, and 93,831 in 2023 <xref ref-type="bibr" rid="BIBR-20">(B.P.S., 2024)</xref>. These figures reflect the growing disparity in zones such as residential areas as places of residence; industrial zones as sources of employment; and agricultural lands as means of livelihood (<xref ref-type="fig" rid="figure-12">Figure 12</xref>).</p><fig id="figure-12" ignoredToc=""><label>Figure 12</label><caption><p>Documentary portrait of the Ibun river corridor area in Sector 3: (a) Portrait of settlements in the river corridor; (b) Portrait of rice fields in the river corridor; (c) Portrait of industry in the river corridor.</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59201" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>We specifically identified which areas were quantitatively disadvantaged, as presented in <xref ref-type="table" rid="table-8">Table 8</xref>. Rapid development has put pressure on land resources (Miswar et al., 2023). Agricultural land within Sector 3 is currently subject to significant conversion pressures, primarily driven by the expansion of residential and industrial zones.</p><table-wrap id="table-8" ignoredToc=""><label>Table 8</label><caption><p>Land Area Specifications (Sector 3).</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Spatial Planning</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Actual Conditions</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pattern Deviation</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>∑</p><p>(Ha)</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>AOI</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Fishing Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>9.54</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>QC 3.1</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Residential Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Rice Fields</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>39.49</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>QC 3.2</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Fishing Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>11.90</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>QC 3.3</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1.60</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>9.38</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Residential Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.83</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1.21</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1.03</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Residential Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.31</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>10.6</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Border</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.75</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1.60</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>9.38</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Residential Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.83</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1.21</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1.03</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Residential Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.31</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>10.6</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Border</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.75</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr></tbody></table></table-wrap><p>From the total land area of 1,615.78 hectares in this sector, approximately 5.3% (85.60 hectares) is currently utilised in a manner inconsistent with the designated land use outlined in the Regional Spatial Plan. This pattern of land conversion reflects broader trends associated with urbanisation and industrial growth, which pose a potential threat to local food security and the critical ecological functions of wetland ecosystems within the area. This is because agriculture plays an important role in the Indonesian economy and is the main source of livelihood for most of the rural population <xref ref-type="bibr" rid="BIBR-8">(Anja &amp; D, 2024)</xref> . As previously noted, several locations exhibiting spatial incongruities within the Citarum River corridor have been identified and are visually documented in<xref ref-type="fig" rid="figure-13">Figure 13</xref>.</p><fig id="figure-13" ignoredToc=""><label>Figure 13</label><caption><p>Sector 3 Investigation Point Distribution: (a) Land Disparities from Wet Agriculture to Settlements (GC 3.1); (b) Land Disparities from Wet Agriculture to Settlements (GC 3.2); (c) Land Disparities from Wet Agriculture to Settlements (GC 3.3).</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59202" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>Furthermore, within this sector, the conversion of traditional fishing areas into residential and industrial zones has demonstrably influenced both land use patterns and the livelihoods of local communities. These observations align with findings from previous research conducted at Poyang Lake, China, which indicated that policy-driven transformations can significantly alter the livelihoods of fishing communities, subsequently impacting agricultural landscape configurations and contributing to land fragmentation <xref ref-type="bibr" rid="BIBR-77">(Ou et al., 2022)</xref> .</p><p>Similarly, research in Cambodia has revealed that infrastructure development and the effects of climate change have disrupted natural seasonal flooding regimes and critical fish migration pathways, leading to adverse consequences for fish biodiversity and the food security of local populations <xref ref-type="bibr" rid="BIBR-120">(Tilley et al., 2024)</xref>. It is also pertinent to note that industrial development within riverine corridors can result in substantial riparian ecosystem degradation. Scholarly investigations have shown that activities such as land reclamation and infrastructure construction can disrupt the intrinsic ecological functions of rivers and elevate the risk of flood events <xref ref-type="bibr" rid="BIBR-43">(Han et al., 2022)</xref>.</p><p>Conversely, instances of land-use change from resettlement areas back to wetland agriculture, specifically rice cultivation, represent potential ecosystem restoration initiatives. However, this form of conversion necessitates systemic adjustments, including the revitalisation of existing irrigation infrastructure and the adaptation of community practices to an agrarian mode of life. A primary challenge in this context is the restoration of land productivity in areas previously fragmented by settlement development, while concurrently ensuring both ecological integrity and social sustainability.</p><list list-type="order"><list-item><p>Investigation of Sector 4</p></list-item></list><p>Sector 4 is primarily characterised by its agricultural land use, with rice fields constituting the dominant land cover (<xref ref-type="fig" rid="figure-5">Figure 14</xref>). However, a notable increase in residential areas indicates significant pressure for land conversion within the sector. Furthermore, initial indications of industrial area development are also discernible, albeit on a limited scale at present. It is anticipated that if these prevailing trends persist, the extensive rice fields in this sector could face a significant threat of conversion, particularly to residential developments. This observation aligns with broader patterns, whereby rapid urbanisation in recent years has driven significant changes in land use and land cover, with a particularly salient impact being the fragmentation of existing green spaces <xref ref-type="bibr" rid="BIBR-73">(Nazombe &amp; Nambazo, 2023)</xref> .</p><fig id="figure-5" ignoredToc=""><label>Figure 14</label><caption><p>Data Portrait of Sector 4 Land Use.</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59203" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>The investigation of this sector, encompassing the Majalaya area, reveals that rice fields and residential settlements predominantly characterise land use. However, similar to the preceding sector, the area is not exempt from the phenomenon of spatial disparity. We identified a gap area covering approximately 49.80 hectares (<xref ref-type="table" rid="table-9">Table 9</xref>), indicating that anthropogenic activities may gradually erode established spatial planning regulations and/or previously formulated policies.</p><table-wrap id="table-9" ignoredToc=""><label>Table 9</label><caption><p>Sector 4 Disparity Investigation</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pattern Deviation</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Land Area (Ha)</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Location</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Conforming Pattern</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">1261.56</td><td colspan="1" rowspan="2" style="" align="left" valign="middle"><p>Majalaya, Bandung Regency, Indonesia</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Non-conforming Pattern</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">49.80</td></tr></tbody></table></table-wrap><p>The phenomenon occurring in Sector 4 is very similar to that of Sector 3, with the extent of the gap dominated by residential and industrial areas. Over the past four years, the population has also experienced significant growth, from 102,082 in 2019, to 160,617 in 2020, 165,687 in 2022, and 166,861 in 2023 <xref ref-type="bibr" rid="BIBR-21">(B.P.S., 2024)</xref>. Data for 2021 are unavailable. This demographic trend reflects an accelerated peri-urbanisation process, which in turn has driven local industrialisation. Such rapid growth and industrial expansion signify a broader transformation from an agrarian-based economy to an industrial one in this region. Significant changes in land cover have been documented <xref ref-type="bibr" rid="BIBR-7">(Anggraheni et al., 2025)</xref>, alongside recurring flood events in Majalaya (<xref ref-type="bibr" rid="BIBR-24">(Burnama et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-101">(Rohmat et al., 2022)</xref>); deteriorating water quality in the Citarum River <xref ref-type="bibr" rid="BIBR-85">(Pratiwi et al., 2023)</xref>; and various other environmental concerns. Field observations revealed visible signs of environmental degradation along the Citarum river (<xref ref-type="fig" rid="figure-15">Figure 15</xref>a). Further investigation indicated that the deterioration in water quality was primarily caused by industrial wastewater discharges, in blatant violation of the agreed Environmental Impact Assessment (AMDAL) provisions.</p><fig id="figure-15" ignoredToc=""><label>Figure 15</label><caption><p>Documentary portrait of the Majalaya area in Sector 4: (a) Portrait of industrial waste in Majasetra Village, Majalaya; (b) Portrait of residential land along the river corridor in Neglasari Village; (c) Portrait of industrial presence in Majasetra.</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59204" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>Several locations of disparity phenomena that have occurred in the Citarum river corridor have been identified, and are illustrated in <xref ref-type="fig" rid="figure-16">Figure 16</xref>. The specifications of the sector land area are shown in <xref ref-type="table" rid="table-10">Table 10</xref>. While the dominant land use in Sector 4 currently aligns with the prevailing spatial plan, the sector is exhibiting increasing pressure from land conversion, notably from agricultural land to both settlements and industrial areas. Alarmingly, protected buffer zones are reportedly being utilised for industrial activities, signifying a potential violation of their designated protective function. The functional shift from wet agricultural land to residential areas represents a primary land management challenge in this sector, corroborating the quantitative data presented in earlier analysis (40.89% residential versus 52.59% rice fields). Spatial discrepancies within the Citarum River corridor have also been identified and are visually documented in <xref ref-type="fig" rid="figure-16">Figure 16</xref>.</p><fig id="figure-16" ignoredToc=""><label>Figure 16</label><caption><p>Sector 4 Investigation Point Distribution: (a) Land Disparities from Wet Agriculture to Settlements (GC 4.1); (b) Land Disparities from Wet Agriculture to Settlements (GC 4.2); (c) Land Disparities from Wet Agriculture to Settlements (GC 4.3).</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59205" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><table-wrap id="table-10" ignoredToc=""><label>Table 10</label><caption><p>Land Area Specifications (Sector 4)</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Spatial Planning</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Factual Conditions</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>Pattern deviation</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>∑ (Ha)</p></th><th colspan="1" rowspan="1" style="" align="left" valign="top"><p>AOI</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Border</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>9.11</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>QC 4.1</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Fishing Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>11.94</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>QC 4.2</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>7.20</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>QC 4.3</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.64</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Border</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.02</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Residential Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>5.44</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1.07</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Settlements</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>13.56</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Border</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>9.11</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Wetland Agricultural Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.43</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Residential Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.05</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Border</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Industrial Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top">Non-conforming</td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>0.31</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>None</p></td></tr></tbody></table></table-wrap><p>The area in Sector 4 includes Majalaya, which represents more of a city than settlements in the other sectors. Not surprisingly, the conversion of non-urban land into urban land is designed to accommodate the expansion of residential areas and meet the increasing spatial demands of urbanisation <xref ref-type="bibr" rid="BIBR-74">(Norita et al., 2024)</xref>. For example, the conversion of river borders into industrial and residential areas has caused complex and interrelated environmental impacts. The case of the Citarum River in Indonesia is a clear example of massive land conversion on the riverbanks causing water quality degradation that is difficult to restore <xref ref-type="bibr" rid="BIBR-99">(Rohmat et al., 2024)</xref>.</p><p>A similar phenomenon can be observed globally, where riparian land conversion triggers three critical impacts: first, damage to aquatic ecosystems, characterised by a decrease in water quality due to industrial and domestic pollution, as well as loss of biodiversity of up to 40-60% in some cases (<xref ref-type="bibr" rid="BIBR-97">(Rodríguez-Echeverry, 2023)</xref>; <xref ref-type="bibr" rid="BIBR-125">(Wang et al., 2023)</xref>); second, systemic hydrological disturbances in the form of an increase in flooding frequency of 30-50% due to reduced catchment areas and increased impervious surfaces <xref ref-type="bibr" rid="BIBR-126">(Wang et al., 2023)</xref>; and third, the loss of essential ecosystem services such as natural pollutant filtering and flood control (<xref ref-type="bibr" rid="BIBR-10">(Atesoglu et al., 2025)</xref>; <xref ref-type="bibr" rid="BIBR-150">(Zhuge et al., 2023)</xref>). We conclude that each sector we investigated is experiencing discrepancies between regional spatial planning and actual conditions.</p><p>We now summarise and conduct analysis of the relationship between the gap phenomenon and sectorization in the area from upstream (sector 1) to downstream (sector 4). The findings are presented in <xref ref-type="table" rid="table-11">Table 11</xref>.</p><table-wrap id="table-11" ignoredToc=""><label>Table 11</label><caption><p>Total Area Suitable and Non-Suitable Area.</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" rowspan="2" style="" align="center" valign="middle"><p>Sector</p></th><th colspan="3" rowspan="1" style="" align="center" valign="middle"><p>Suitable Area (Ha)</p></th><th colspan="3" rowspan="1" style="" align="center" valign="middle"><p>Non-Suitable Area (Ha)</p></th><th colspan="2" rowspan="1" style="" align="center" valign="middle"><p>Area Total (Ha)</p></th></tr><tr><th colspan="1" rowspan="1" style="" align="center" valign="middle"><p>Land area[SG1] [f2]  per sector</p></th><th colspan="1" rowspan="1" style="" align="center" valign="middle"><p>Total area</p></th><th colspan="1" rowspan="1" style="" align="center" valign="middle"><p>%</p></th><th colspan="1" rowspan="1" style="" align="center" valign="middle"><p> Land area per sector</p></th><th colspan="1" rowspan="1" style="" align="center" valign="middle"><p>Total area</p></th><th colspan="1" rowspan="1" style="" align="center" valign="middle"><p>%</p></th><th colspan="1" rowspan="1" style="" align="center" valign="middle"><p>Total</p></th><th colspan="1" rowspan="1" style="" align="center" valign="middle"><p>%</p></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Sector 1</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>2181.40</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>16.16</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>9.41</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>43.64</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Sector 2</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1399.65</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>20.14</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>11.73</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>33.69</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Sector 3</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1530.19</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>85.60</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>49.85</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>73.86</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Sector 4</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>1261.56</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>49.81</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>29.01</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>48.80</p></td></tr><tr><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>Total Area</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"/><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>100.00</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>6544.52</p></td><td colspan="1" rowspan="1" style="" align="left" valign="top"><p>200.00</p></td></tr></tbody></table><table-wrap-foot><p>Source: Data Processing Results (2025)</p></table-wrap-foot></table-wrap><p>Linear regression modelling and coefficient of determination (R²) formulations were conducted to identify the influence of spatial changes in area gaps using the following formulation <xref ref-type="fig" rid="figure-17">Figure 17</xref>. We indicate that certain factors influence the size of the gap in sectors 1-4 <xref ref-type="fig" rid="figure-17">Figure 17</xref>, with the significance of our results being 69.4%. We conclude that there is an influential contribution from upstream to downstream areas; the further downstream, the greater the mismatch. This is because many anthropogenic factors are increasing, characterised by land conversion such as industry, settlements and rice fields.</p><p>However, in Sector 3, the mismatch is smaller than in Sector 2. It cannot be denied that the closer the rural area is to the city, the higher the level of agricultural land use <xref ref-type="bibr" rid="BIBR-83">(Pradoto et al., 2024)</xref>. We conclude that local policies or the implementation of spatial plans contribute significantly. This is supported by the results of previous research, which show that changes in land use depend on the plans and policies of each government in pursuing the country's development path <xref ref-type="bibr" rid="BIBR-124">(Tuan, 2022)</xref>.</p><p>The findings from this in-depth analysis warrant further investigation into why Sector 3 exhibits a greater disparity than Sector 2, which is geographically oriented toward the upstream area. It is essential to determine whether there are specific interventions or management practices implemented in Sector 2 that are absent in Sector 3. Our preliminary indications suggest that such disparities may be attributable to a combination of factors, including community awareness, land- use politics, the egocentrism of industrial stakeholders, and/or the influence of local political dynamics.</p><fig id="figure-17" ignoredToc=""><label>Figure 17</label><caption><p>Significance of land suitability based on inter-spatial (Sector 1-4).</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59206" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig></sec><sec><title>3.2. Why does the disparity phenomenon occur?</title><p>The disparity phenomenon usually occurs because the demand for spatial resources by industrial and residential activities has increased dramatically, leading to substantial encroachment of ecological space <xref ref-type="bibr" rid="BIBR-139">(Xu et al., 2024)</xref>. As supported by various experts, this occurs because watershed-scale anthropogenic activities, such as agricultural expansion, urbanisation, reforestation and deforestation, are the dominant single or integrated drivers of LUCC <xref ref-type="bibr" rid="BIBR-26">(Chu et al., 2022)</xref><xref ref-type="bibr" rid="BIBR-36">(Feng et al., 2023)</xref><xref ref-type="bibr" rid="BIBR-62">(Lyu et al., 2024)</xref><xref ref-type="bibr" rid="BIBR-116">(Tafazzoli, 2023)</xref>. We explored in depth the perspectives of local communities along the Citarum river corridor, from their way of thinking about land use, to regional spatial planning.</p><list list-type="order"><list-item><p>Land Use Implementation Perspective</p></list-item></list><p>The results of the investigation through the distribution of questionnaires along the Citarum river corridor regarding people’s perspectives on the implementation of land use change, using MCDA with the AHP technique, are visualised in <xref ref-type="fig" rid="figure-18">Figure 18</xref>.</p><fig id="figure-18" ignoredToc=""><label>Figure 18</label><caption><p>Perspective of Land Use-Based MCDA. Description: Community knowledge of river corridors (X1); Community knowledge of land and soil (X2); Community knowledge of land use (X3); Community knowledge of land change (X4); Land ownership (X5); Land ownership use (X6); Land ownership permits (X7); Land density (X8); Land conformity with regional spatial planning (X9); Intensity of land use socialisation activities (X10); Availability of residents for relocation (X11); Land change track record (X12); Land change impact (X13); Factors causing land change (X14).</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59207" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>The MCDA results shown in <xref ref-type="fig" rid="figure-18">Figure 18</xref> indicate a predominant tendency toward the variable representing community perspectives on the drivers of land-use change (X14, with an AHP weight score of 0.1361). Upon further investigation, a significant proportion of respondents identified economic factors (70.27%), environmental factors (43.24%), and socio-demographic factors (37.83%) as the primary contributors. To substantiate why these factors were perceived as central to the phenomenon of spatial planning discrepancies, further clarification is provided below.</p><p>Economic and socio-demographic factors. The investigation revealed that the economic needs of residents for daily living serve as a primary reason for selling land, with such transactions often involving immigrants who purchase these parcels. The process indirectly contributes to the phenomenon of urbanisation. Furthermore, the land acquired by newcomers is frequently developed into residential housing, villas serving as lodging facilities, or industrial sites for business ventures.</p><p>Environmental and economic factors. The findings indicate that, particularly in Sectors 3 and 4, local communities expressed concern over the turbidity of the Citarum River, which they attributed to solid waste, industrial effluents and mining activities. These environmental degradations have become a driving factor behind the decision of many residents to sell their land.</p><p>Socio-demographic and economic factors. It was also found that much of the land in question is inherited across generations. Initially underutilised or barren, it has been progressively converted into residential properties, plantations and rice fields, fulfilling the communities' needs for shelter, food and livelihoods. This transformation has persisted from the first generation through to the third generation of the same families.</p><p>Fundamentally, the three economic, socio-demographic and environmental factors are interrelated, together influencing the phenomenon of spatial disparities along the Citarum River corridor. The phenomenon contributes to land conversion that deviates from its intended use, precipitates social conflicts, and impacts the sustainability of ecological functions within river corridor area.. It is crucial to acknowledge that unsuitable land change is an environmental transformation driven by complex interactions between climate change and anthropogenic activities aimed at fulfilling human needs (<xref ref-type="bibr" rid="BIBR-62">(Lyu et al., 2024)</xref>; <xref ref-type="bibr" rid="BIBR-94">(Reinhart et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-128">(Wang et al., 2021)</xref>), representing a tangible manifestation of human influence on the environment (<xref ref-type="bibr" rid="BIBR-36">(Feng et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-62">(Lyu et al., 2024)</xref>). While the dynamics of land use are paramount for effective area management (<xref ref-type="bibr" rid="BIBR-4">(Alausa et al., 2023)</xref>; <xref ref-type="bibr" rid="BIBR-92">(Ray et al., 2023)</xref>), gaps along river corridors driven by personal and industrial interests can lead to numerous detrimental impacts <xref ref-type="bibr" rid="BIBR-104">(Saputra et al., 2023)</xref>, including soil erosion, sedimentation and even instream landslides <xref ref-type="bibr" rid="BIBR-72">(Mwasenga &amp; Mjemah, 2023)</xref>, affecting river water quality <xref ref-type="bibr" rid="BIBR-76">(Novita et al., 2022)</xref> and increasing vulnerability to flooding <xref ref-type="bibr" rid="BIBR-33">(Devitt et al., 2023)</xref>. Consequently, strategic planning and management of land use are essential to address both current needs and future challenges <xref ref-type="bibr" rid="BIBR-145">(Yu et al., 2025)</xref>. Various studies advocate ecosystem-based solutions as a sustainable approach, with <xref ref-type="bibr" rid="BIBR-28">(Corgo et al., 2024)</xref> recommending the implementation of buffer zones at least 100 metres wide, integrated within the regional spatial plan.</p><list list-type="order"><list-item><p>Regional Spatial Planning Implementation Perspective</p></list-item></list><p>The measurement was conducted in the same manner as in the findings in the previous subsection, in which the MCDA using the AHP method identified several factors contributing to the disparity phenomenon from the perspective of the local community’s spatial planning <xref ref-type="fig" rid="figure-19">Figure 19</xref>.</p><p>The MCDA analysis identified tendencies in the community’s knowledge of RSP, the role of RSP within society, and public enthusiasm toward RSP, which are elaborated as follows.</p><p>Community knowledge of RSP (X15). The findings reveal that all residents encountered during the investigation were aware of RSP. However, it is important to emphasise that such awareness was mostly limited to having heard about it through social media or through occasional visits by relevant agencies, and even then, only in Kertasari Village (Sector 1). Upon further inquiry, it became evident that residents lacked explicit and implicit understanding of RSP functions, meaning and societal role.</p><p><italic>The role of RSP within society (X</italic><italic><sub>17</sub></italic><italic>). </italic>The data indicated that 36 out of the 37 respondents acknowledged that RSP is highly important; however, they lacked comprehension of its practical implementation in daily life. This finding strongly correlates with the earlier clarification regarding their limited knowledge of RSP.</p><p><italic>Community enthusiasm towards RSP (X</italic><italic><sub>22</sub></italic>). A marked difference was observed between communities experiencing low and high levels of river pollution. In Sectors 1–2, where river pollution was minimal, residents generally expressed indifference toward possible relocations for RSP implementation, as long as compensation was provided. In contrast, residents in Sectors 3–4 demonstrated strong enthusiasm for RSP implementation, primarily due to the severe pollution of the Citarum River caused by industrial activities. As previously discussed in the sub-study on Ibun and Majalaya Districts, the discharge of industrial waste has heightened local concern and motivated communities to support RSP enforcement along the Citarum River corridor to restore the river’s ecological condition.</p><fig id="figure-19" ignoredToc=""><label>Figure 19</label><caption><p>Perspective of Regional Spatial Plan-Based MCDA. Description: Knowledge of regional spatial planning (X15); Intensity of socialisation of regional spatial planning (X16); Role of regional spatial planning in the community (X17); Community conflict with the government (X18); Case examples of building inconsistencies (X19); Permits for building layout (X20); Spatial planning as an obstacle to the development of a region (X21); Public enthusiasm for spatial planning (X22).</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59208" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>In contrast, residents in Sectors 3-4 demonstrated strong enthusiasm for the implementation of RSP, largely due to the worsening pollution of the Citarum River caused by industrial activities. This phenomenon has been detailed in the earlier sub-study on the disparity areas within Ibun and Majalaya Districts. The persistent presence of industrial waste has heightened community concern, fostering a strong commitment among residents to support RSP enforcement along the Citarum River corridor as a means to restore the river's ecological condition.</p><p>Based on clarifications derived from the in-depth MCDA analysis, integrating both actual land- use perspectives and the RSP framework, it can be concluded that economic factors, environmental conditions, socio-demographic characteristics, community knowledge of RSP, the perceived role of RSP in society, and public enthusiasm toward its implementation collectively form the underlying drivers of disparity along the Citarum River corridor in Sectors 1–4. To reinforce these findings, we conducted a follow-up investigation through a focus group discussion in Cikitu Village, Bandung Regency <xref ref-type="fig" rid="figure-20">Figure 20</xref>, aimed at deliberating on the disparity phenomenon observed across Sectors 1–4 along the Citarum River corridor.</p><fig id="figure-20" ignoredToc=""><label>Figure 20</label><caption><p>Focus group discussion for further investigation: (a) Presentation of investigation objectives; (b) Perception of Citarum community leaders; (c) End of FGD session.</p></caption><graphic xlink:href="https://journals2.ums.ac.id/fg/article/download/10379/4808/59210" mimetype="image" mime-subtype="png"><alt-text>Image</alt-text></graphic></fig><p>Strengthening the MCDA analysis (Figures 18 and 19), the disparity phenomenon has profoundly eroded the long-standing cultural practices traditionally upheld by communities along the Citarum River corridor, as reflected in the narratives shared during our community discussions.</p><p>Respondent A:</p><p>"…Nowadays, many cultural traditions have almost disappeared. In the past, there was a tradition called Ngabedahkeun (a communal practice of draining fishponds during the harvest season, when villagers would enthusiastically gather to harvest fish together). This was commonly held, especially in Kertasari and Pacet Districts, which once had tens of thousands of ponds. My parents, like most residents of Tarumajaya Cibeureum in Kertasari District, owned ponds. But now, most of these have been converted into gardens, leading to the loss of the Ngabedahkeun tradition. Moreover, the fish found today in Kertasari and Pacet mostly come from Saguling and Cirata reservoirs, which are unfit for consumption. The disappearance of this tradition is mainly due to urbanization, shrinking land availability and the diminishing water supply."”</p><p>(FGD Findings, 2024)</p><p>As a consequence of this disparity, the cultural tradition of Ngabedahkeun has begun to fade due to various contributing factors: urbanisation (a socio-demographic factor); increasing land scarcity (an economic and socio-demographic factor); and diminishing water resources (an environmental factor) along the Citarum River corridor, particularly in Sectors 1 and 2. This observation is further reinforced by subsequent discussion findings; one participant stated:</p><p>Respondent B:</p><p>“………There is customary law introduced by the Dutch, reflecting their efforts to classify communities, similar to the arrangement of the river corridor, which primarily emphasized the functional use of the river. Furthermore, in the customary law established by the Dutch, the term Leuweung Walungan Jero refers to social order within the community”.</p><p>(FGD Findings, 2024)</p><p>In the customary law concept of <bold><italic>Leuweung Walungan Jero</italic></bold>, rivers and their surrounding areas are regarded as a single, integrated ecosystem that holds both ecological and social value. Consequently, their utilisation is strictly regulated to ensure environmental sustainability and social order. When examined in relation to spatial disparity, these customary legal principles should serve as a reference in spatial planning. However, empirical realities reveal that the designated riparian buffer zones often shift due to pressures from development, urbanisation and community economic activities. As a result, many areas originally designated as conservation zones in RSP have been converted into residential areas, rice fields, and even industrial sites.</p><p>Respondent C:</p><p>“………The cultural belief in the existence of Raden Kalung Bimanagara has also now disappeared. I still recall my grandfather saying, “Mun pasosoré tong leuwih teuing ngagarap lahan ke sisi Citarum, Raden Kalung bisi ngadat”, which translates to, “When afternoon falls, do not excessively cultivate land near the banks of the Citarum, or Raden Kalung will be angered.” Raden Kalung Bimanagara, once revered as the guardian deity of the Citarum River, is no longer acknowledged in contemporary local practice, but was a belief once deeply rooted in Sundanese culture.</p><p>In the past, village-scale development initiatives were frequently implemented within our community, often intertwined with these cultural values. However, current regulatory frameworks, such as those outlined in the Regulation of the Minister of Public Works and Public Housing Number 28/PRT/M/2015 of 2015, address riparian zones primarily from a technical standpoint. When it comes to the determination of riparian buffer boundaries, the regulation largely delegates authority back to each respective regional government”.</p><p>(FGD Findings, 2024)</p><p>In responding to and reflecting upon the erosion of cultural values and local beliefs surrounding the mythology of <bold><italic>Raden Kalung Bimanagara, </italic></bold>once revered as the guardian or “deity” of the Citarum River, it is evident that this tradition functioned as an unwritten social norm regulating human activities along the riverbanks, particularly at certain times of the day. For example, the customary prohibition “mun pasosoré tong leuwih teuing ngagarap lahan ke sisi Citarum” (“when afternoon falls, do not excessively cultivate land near the Citarum”) effectively created a natural buffer zone that preserved riparian areas, without the need for formal governmental regulation.</p><p>The disappearance of these beliefs has in turn exacerbated environmental degradation along the Citarum River corridor, contributing to the emergence of spatial disparity phenomena. In addressing this issue, the government’s current regulatory framework, such as the Ministry of Public Works Regulation Number 28 of 2015 on the designation of riparian boundaries, has often been criticised in terms of field implementation, as the enforcement of such regulations is largely delegated to regional authorities.</p><p>In light of this, we recommend that local governments integrate nature-based solutions (NbS) for river corridors into policy implementation in a sustainable manner <xref ref-type="bibr" rid="BIBR-98">(Rohmat &amp; W, 2025)</xref>. Such approaches are critical, as rivers constitute an essential component of water resources and play a pivotal role in sustaining life; they therefore require long-term preservation <xref ref-type="bibr" rid="BIBR-2">(Afriyani et al., 2024)</xref>. Without effective regional support, there will be an imbalance between land use, potential and needs <xref ref-type="bibr" rid="BIBR-68">(Miswar et al., 2023)</xref>. Wise measures are needed in managing land in order to create sustainable land use <xref ref-type="bibr" rid="BIBR-9">(Arsa &amp; D, 2025)</xref>. Research in China and Turkey indicates that riparian vegetation restoration can significantly reduce sedimentation (by up to 25%) and enhance pollutant filtration capacity (<xref ref-type="bibr" rid="BIBR-10">(Atesoglu et al., 2025)</xref>; <xref ref-type="bibr" rid="BIBR-129">(Wang et al., 2024)</xref>).</p><p>Emerging policy implications include: (1) the strengthening of regulations protecting riverine buffer zones, (2) the mandatory implementation of environmental impact assessments based on hydro-ecological studies, and (3) the development of real-time monitoring systems utilising remote sensing technology. The case of the South-to-North Water Diversion project in China <xref ref-type="bibr" rid="BIBR-150">(Zhuge et al., 2023)</xref> provides a valuable precedent for considering the value of ecosystem services in large-scale development planning. The dynamic interplay between natural and anthropogenic factors in shaping land cover underscores the importance of continuous monitoring and adaptive management in conservation efforts <xref ref-type="bibr" rid="BIBR-5">(Alikhanov et al., 2024)</xref>. This transformation necessitates a strategic shift towards sustainable river management through an integrated approach encompassing ecological, hydrological (water resource management), and socio-economic considerations within a sustainable development framework <xref ref-type="bibr" rid="BIBR-3">(Agli et al., 2024)</xref>.</p></sec></sec><sec><title>5. Conclusion</title><p>Regional spatial planning (RSP) serves as a critical framework for guiding land use practices. However, spatial disparities persist, as evidenced along the Citarum River corridor, based on our field investigation covering Sectors 1, 2, 3 and 4. The most pronounced disparity was identified in Sector 3, encompassing approximately 85.60 ha out of a total 1,615.79 ha (49.85%), whereas the smallest disparity occurred in Sector 1, at about 16.16 ha out of 2,197.56 ha (9.41%). Furthermore, our analysis revealed that the influence of inter-sector dynamics from upstream to downstream accounts for approximately 69.4% of the variation in disparity extent.</p><p>The expansion of residential areas, paddy fields and industrial zones has emerged as the root cause of these spatial disparities. Beyond quantitative measurements, we conducted an in-depth exploration of local community perspectives along the river corridor regarding land use and the Regional Spatial Plan (RSP). Using MCDA, we concluded that these disparities are driven by interrelated qualitative factors, namely economic conditions, environmental pressures, socio- demographic characteristics, public knowledge of the RSP the perceived role of RSP within the community, and community enthusiasm toward its implementation.</p><p>We acknowledge several limitations in the study, including the shortage of human resources to conduct a more in-depth investigation, as many underlying issues along the river corridor remain unexplored. In addition, the use of the Autel EVO 2 Pro V3 drone provided only a moderate level of ground-check accuracy compared to the higher precision of LiDAR-based drones. Consequently, we recommend that future research address these limitations by incorporating cutting-edge technological innovations to support the long-term restoration of the Citarum River as a theoretical implication We anticipate that the findings of this research will serve as a relevant evaluation and valuable reference for the planning of sustainable spatial management along the Citarum River corridor in the future. In particular, we propose (1) synchronising RSP with existing conditions through periodic spatial assessments in other sectors using advanced geospatial technologies; (2) establishing derivative regulations specific to river corridor zones that provide more detailed land-use restrictions, including adaptive zoning provisions for sectors with high relaxation levels, such as Sector 3; (3) enhancing law enforcement capacity through well- defined incentive and sanction mechanisms for spatial planning violations; and (4) conducting periodic community outreach to raise awareness regarding the functions and roles of RSP among communities along the Citarum River corridor. We further expect that the innovative research framework developed herein can serve as a sampling campaign model for replicating sustainable river restoration initiatives in other contexts.</p></sec><sec><title>Acknowledgements</title><p>The researchers would like to thank the communities of Citarum sector 1, sector 2, sector 3 and sector 4 and the Geography Education students of Universitas Pendidikan Indonesia who have assisted in the field survey for data collection .</p></sec><sec><title>Author Contributions</title><p><bold>Conceptualization</bold>: Setiawan, I., Rohmat, D., &amp; Suhendro, S.; <bold>methodology</bold>: Setiawan, I.; <bold>investigation</bold>: Setiawan, I., Rohmat, D., &amp; Suhendro, S.; <bold>writing— original draft preparation</bold>: Setiawan, I., &amp; Suhendro, S.; <bold>writing—review and editing</bold>: Setiawan, I., &amp; Suhendro, S.; <bold>visualization</bold>: Setiawan, I., &amp; Suhendro, S.. All authors have read and agreed to the published version of the manuscript.</p></sec><sec><title>Conflict of interest</title><p>All authors declare that they have no conflicts of interest.</p></sec><sec><title>Data availability</title><p>The data supporting this study are available from the corresponding author upon reasonable request</p></sec><sec><title>Funding</title><p>This research was funded by BIMA Progamme with Scheme Fundamental of 2024, grant number 082/ E5/ PG.02.00.PL/ 2024 with Agreement Decree Number: 1128/UN40.LP/PT.01.03/2024</p></sec></body><back><ref-list><title>References</title><ref id="BIBR-1"><element-citation publication-type="article-journal"><article-title>Perspectives for smooth bridging of dichotomized urban–rural land development in the peri-urban areas of Ethiopia: Toward a continuum approach</article-title><source>Regional Science Policy and Practice</source><volume>16</volume><issue>3</issue><person-group 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