Spatial Heterogeneity of Mangrove Changes and Its Local Driving Factors on the Southern Coast of Java Island, Indonesia
The decline in mangrove forests has reduced their capacity to mitigate climate change, making monitoring and mapping essential for their sustainability. This study examined mangrove area changes in the Segara Anakan Cilacap (SAC) mangrove cluster (2019–2022), analyzed local driving factors, and prop...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Scientifica |
| Online Access: | http://dx.doi.org/10.1155/sci5/6670733 |
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| author | Anang Dwi Purwanto Ketut Wikantika Albertus Deliar Soni Darmawan null Suprapedi Asep Saepuloh Alfita Puspa Handayani Ulung Jantama Wisha Emma Rahmawati Fika Nurul Falah Bayu Prayudha |
| author_facet | Anang Dwi Purwanto Ketut Wikantika Albertus Deliar Soni Darmawan null Suprapedi Asep Saepuloh Alfita Puspa Handayani Ulung Jantama Wisha Emma Rahmawati Fika Nurul Falah Bayu Prayudha |
| author_sort | Anang Dwi Purwanto |
| collection | DOAJ |
| description | The decline in mangrove forests has reduced their capacity to mitigate climate change, making monitoring and mapping essential for their sustainability. This study examined mangrove area changes in the Segara Anakan Cilacap (SAC) mangrove cluster (2019–2022), analyzed local driving factors, and proposed mitigation strategies. Using geographically weighted logistic regression (GWLR) and geospatial machine learning (GML), validated by field surveys, the study identified significant mangrove conversion into ponds, open land, and cultivated areas. The results show that spatial heterogeneity of driving factors was effectively modeled, with a fixed bi-square kernel type increasing accuracy by 3%. Mangrove area changes are influenced by local conditions within a 19,052-m radius. In the western region, mangrove area degradation is caused by population density and salinity (regression coefficient > 0.98); in the central region, it is determined by the distance to aquaculture (coefficient 0.88); and in the eastern region, it is due to the distance to settlements (coefficient ∼0.97). Tailored interventions, such as managing community activities, land use changes, and settlements, are essential for conserving mangrove forests in this area. |
| format | Article |
| id | doaj-art-d1e6522f22d64cac9ab25d7753573c7a |
| institution | Kabale University |
| issn | 2090-908X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Scientifica |
| spelling | doaj-art-d1e6522f22d64cac9ab25d7753573c7a2025-08-25T00:00:05ZengWileyScientifica2090-908X2025-01-01202510.1155/sci5/6670733Spatial Heterogeneity of Mangrove Changes and Its Local Driving Factors on the Southern Coast of Java Island, IndonesiaAnang Dwi Purwanto0Ketut Wikantika1Albertus Deliar2Soni Darmawan3null Suprapedi4Asep Saepuloh5Alfita Puspa Handayani6Ulung Jantama Wisha7Emma Rahmawati8Fika Nurul Falah9Bayu Prayudha10National Research and Innovation Agency (BRIN)Faculty of Earth Sciences and TechnologyFaculty of Earth Sciences and TechnologyFaculty of Civil Engineering and PlanningNational Research and Innovation Agency (BRIN)Faculty of Earth Sciences and TechnologyFaculty of Earth Sciences and TechnologyNational Research and Innovation Agency (BRIN)National Research and Innovation Agency (BRIN)Faculty of BiologyNational Research and Innovation Agency (BRIN)The decline in mangrove forests has reduced their capacity to mitigate climate change, making monitoring and mapping essential for their sustainability. This study examined mangrove area changes in the Segara Anakan Cilacap (SAC) mangrove cluster (2019–2022), analyzed local driving factors, and proposed mitigation strategies. Using geographically weighted logistic regression (GWLR) and geospatial machine learning (GML), validated by field surveys, the study identified significant mangrove conversion into ponds, open land, and cultivated areas. The results show that spatial heterogeneity of driving factors was effectively modeled, with a fixed bi-square kernel type increasing accuracy by 3%. Mangrove area changes are influenced by local conditions within a 19,052-m radius. In the western region, mangrove area degradation is caused by population density and salinity (regression coefficient > 0.98); in the central region, it is determined by the distance to aquaculture (coefficient 0.88); and in the eastern region, it is due to the distance to settlements (coefficient ∼0.97). Tailored interventions, such as managing community activities, land use changes, and settlements, are essential for conserving mangrove forests in this area.http://dx.doi.org/10.1155/sci5/6670733 |
| spellingShingle | Anang Dwi Purwanto Ketut Wikantika Albertus Deliar Soni Darmawan null Suprapedi Asep Saepuloh Alfita Puspa Handayani Ulung Jantama Wisha Emma Rahmawati Fika Nurul Falah Bayu Prayudha Spatial Heterogeneity of Mangrove Changes and Its Local Driving Factors on the Southern Coast of Java Island, Indonesia Scientifica |
| title | Spatial Heterogeneity of Mangrove Changes and Its Local Driving Factors on the Southern Coast of Java Island, Indonesia |
| title_full | Spatial Heterogeneity of Mangrove Changes and Its Local Driving Factors on the Southern Coast of Java Island, Indonesia |
| title_fullStr | Spatial Heterogeneity of Mangrove Changes and Its Local Driving Factors on the Southern Coast of Java Island, Indonesia |
| title_full_unstemmed | Spatial Heterogeneity of Mangrove Changes and Its Local Driving Factors on the Southern Coast of Java Island, Indonesia |
| title_short | Spatial Heterogeneity of Mangrove Changes and Its Local Driving Factors on the Southern Coast of Java Island, Indonesia |
| title_sort | spatial heterogeneity of mangrove changes and its local driving factors on the southern coast of java island indonesia |
| url | http://dx.doi.org/10.1155/sci5/6670733 |
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