Landscape dynamics and its related factors in the Citarum River Basin: a comparison of three algorithms with multivariate analysis
Landscape change is intricately linked to natural resource utilization. Landscape dynamics are closely tied to land use and land cover (LULC), serving as a representation of ecosystems and human activities. In the Citarum River Basin, Indonesia, a comprehensive approach is necessary to comprehend la...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-01-01
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| Series: | Geocarto International |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2024.2329665 |
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| author | Moh. Dede Sunardi Sunardi Kuok-Choy Lam Susanti Withaningsih Hendarmawan Hendarmawan Teguh Husodo |
| author_facet | Moh. Dede Sunardi Sunardi Kuok-Choy Lam Susanti Withaningsih Hendarmawan Hendarmawan Teguh Husodo |
| author_sort | Moh. Dede |
| collection | DOAJ |
| description | Landscape change is intricately linked to natural resource utilization. Landscape dynamics are closely tied to land use and land cover (LULC), serving as a representation of ecosystems and human activities. In the Citarum River Basin, Indonesia, a comprehensive approach is necessary to comprehend landscape dynamics as a manifestation of human interaction with the environment. This research aims to analyze landscape dynamics and its factors that can significantly drive changes. We focused on the Cirasea Watershed, which serves as an upper region of the Citarum River Basin. Data was acquired from Landsat-series imageries from 1993 to 2023, and LULC analyses were conducted using classification and regression trees (CART), random forest (RF), and support vector machine (SVM). We analyzed seven independent variables, including slope (X1), elevation (X2), main river (X3), population (X4), central business district (X5), distance from the past settlements (X6), and accessibility (X7) using multivariate analysis. This research found that RF stands out as the optimal choice for LULC analysis over CART and SVM because it had the highest overall accuracy and overall kappa (0.91–0.92, 0.88–0.89). Notably, there was a substantial 273.43% increase in built-up areas, coupled with significant declines in plantations and horticultures. LULC changes was more pronounced in the lower areas near Bandung City. LR model highlighted X1, X3 and X6 as the significant driving forces for built-up areas expansion (r-square 0.44 with p-value < 0.01 and 95% confidence level). Without effective spatial planning, flat areas near rivers and past settlements have the greatest potential for LULC changes. |
| format | Article |
| id | doaj-art-e282a3dcc01e43fdb973fbcfc680f689 |
| institution | OA Journals |
| issn | 1010-6049 1752-0762 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geocarto International |
| spelling | doaj-art-e282a3dcc01e43fdb973fbcfc680f6892025-08-20T01:59:21ZengTaylor & Francis GroupGeocarto International1010-60491752-07622024-01-0139110.1080/10106049.2024.2329665Landscape dynamics and its related factors in the Citarum River Basin: a comparison of three algorithms with multivariate analysisMoh. Dede0Sunardi Sunardi1Kuok-Choy Lam2Susanti Withaningsih3Hendarmawan Hendarmawan4Teguh Husodo5Environmental Science Program, Graduate School, Universitas Padjadjaran, Bandung City, IndonesiaEnvironmental Science Program, Graduate School, Universitas Padjadjaran, Bandung City, IndonesiaGeography Program, Center for Research in Development, Social and Environment, Universiti Kebangsaan Malaysia, Bangi, MalaysiaFaculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Bandung City, IndonesiaFaculty of Geological Engineering, Universitas Padjadjaran, Bandung City, IndonesiaFaculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Bandung City, IndonesiaLandscape change is intricately linked to natural resource utilization. Landscape dynamics are closely tied to land use and land cover (LULC), serving as a representation of ecosystems and human activities. In the Citarum River Basin, Indonesia, a comprehensive approach is necessary to comprehend landscape dynamics as a manifestation of human interaction with the environment. This research aims to analyze landscape dynamics and its factors that can significantly drive changes. We focused on the Cirasea Watershed, which serves as an upper region of the Citarum River Basin. Data was acquired from Landsat-series imageries from 1993 to 2023, and LULC analyses were conducted using classification and regression trees (CART), random forest (RF), and support vector machine (SVM). We analyzed seven independent variables, including slope (X1), elevation (X2), main river (X3), population (X4), central business district (X5), distance from the past settlements (X6), and accessibility (X7) using multivariate analysis. This research found that RF stands out as the optimal choice for LULC analysis over CART and SVM because it had the highest overall accuracy and overall kappa (0.91–0.92, 0.88–0.89). Notably, there was a substantial 273.43% increase in built-up areas, coupled with significant declines in plantations and horticultures. LULC changes was more pronounced in the lower areas near Bandung City. LR model highlighted X1, X3 and X6 as the significant driving forces for built-up areas expansion (r-square 0.44 with p-value < 0.01 and 95% confidence level). Without effective spatial planning, flat areas near rivers and past settlements have the greatest potential for LULC changes.https://www.tandfonline.com/doi/10.1080/10106049.2024.2329665Cirasea watershedgoogle earth enginelogistic regressionLULCrandom forest |
| spellingShingle | Moh. Dede Sunardi Sunardi Kuok-Choy Lam Susanti Withaningsih Hendarmawan Hendarmawan Teguh Husodo Landscape dynamics and its related factors in the Citarum River Basin: a comparison of three algorithms with multivariate analysis Geocarto International Cirasea watershed google earth engine logistic regression LULC random forest |
| title | Landscape dynamics and its related factors in the Citarum River Basin: a comparison of three algorithms with multivariate analysis |
| title_full | Landscape dynamics and its related factors in the Citarum River Basin: a comparison of three algorithms with multivariate analysis |
| title_fullStr | Landscape dynamics and its related factors in the Citarum River Basin: a comparison of three algorithms with multivariate analysis |
| title_full_unstemmed | Landscape dynamics and its related factors in the Citarum River Basin: a comparison of three algorithms with multivariate analysis |
| title_short | Landscape dynamics and its related factors in the Citarum River Basin: a comparison of three algorithms with multivariate analysis |
| title_sort | landscape dynamics and its related factors in the citarum river basin a comparison of three algorithms with multivariate analysis |
| topic | Cirasea watershed google earth engine logistic regression LULC random forest |
| url | https://www.tandfonline.com/doi/10.1080/10106049.2024.2329665 |
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