SAR Oil Palm Plantation Mapping in Batu Pahat with X, C, L bands for Change Detection
Oil palms have large economic value and are grown extensively across Southeast Asia. However, growth of the oil palm industry comes at the expense of the environment as forests are cleared to grow oil palms. Oil palm plantations need to be monitored to balance economic growth and environmental susta...
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| Language: | English |
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Copernicus Publications
2025-07-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-G-2025/155/2025/isprs-archives-XLVIII-G-2025-155-2025.pdf |
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| _version_ | 1849245882868826112 |
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| author | J. Y. P. Ang Z. Q. Ng |
| author_facet | J. Y. P. Ang Z. Q. Ng |
| author_sort | J. Y. P. Ang |
| collection | DOAJ |
| description | Oil palms have large economic value and are grown extensively across Southeast Asia. However, growth of the oil palm industry comes at the expense of the environment as forests are cleared to grow oil palms. Oil palm plantations need to be monitored to balance economic growth and environmental sustainability. Synthetic Aperture Radar (SAR) imagery allows for the cost-effective and frequent mapping of the extent of oil palm plantations over large areas. This paper aims to develop an oil palm plantation mapping model using X, C and L band SAR and compare their relative performance. The models are developed with the Feature Pyramid Network based on annotations acquired over Batu Pahat, Malaysia. X-band has the best Dice Score of 0.9 for oil palm plantations and the highest overall accuracy of 81.78%. Repeat pass satellite images captured 6 months later were then inferred with the 3 models to identify changes to the land cover. X-band also has the best accuracy in change detection as it has the best land cover classification performance overall. The plantation maps add semantic meaning to the land cover changes. This paper successfully developed a model that can generate frequently updated and detailed oil palm plantation maps, which can be used to detect changes in the oil palm plantation extent promptly. |
| format | Article |
| id | doaj-art-c99d60bc1e2444cdaae44c41b3e4100d |
| institution | Kabale University |
| issn | 1682-1750 2194-9034 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj-art-c99d60bc1e2444cdaae44c41b3e4100d2025-08-20T03:58:40ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342025-07-01XLVIII-G-202515516110.5194/isprs-archives-XLVIII-G-2025-155-2025SAR Oil Palm Plantation Mapping in Batu Pahat with X, C, L bands for Change DetectionJ. Y. P. Ang0Z. Q. Ng1ST Engineering Geo-Insights Pte Ltd, 6 Ang Mo Kio Electronics Park Road #06-03, SingaporeST Engineering Geo-Insights Pte Ltd, 6 Ang Mo Kio Electronics Park Road #06-03, SingaporeOil palms have large economic value and are grown extensively across Southeast Asia. However, growth of the oil palm industry comes at the expense of the environment as forests are cleared to grow oil palms. Oil palm plantations need to be monitored to balance economic growth and environmental sustainability. Synthetic Aperture Radar (SAR) imagery allows for the cost-effective and frequent mapping of the extent of oil palm plantations over large areas. This paper aims to develop an oil palm plantation mapping model using X, C and L band SAR and compare their relative performance. The models are developed with the Feature Pyramid Network based on annotations acquired over Batu Pahat, Malaysia. X-band has the best Dice Score of 0.9 for oil palm plantations and the highest overall accuracy of 81.78%. Repeat pass satellite images captured 6 months later were then inferred with the 3 models to identify changes to the land cover. X-band also has the best accuracy in change detection as it has the best land cover classification performance overall. The plantation maps add semantic meaning to the land cover changes. This paper successfully developed a model that can generate frequently updated and detailed oil palm plantation maps, which can be used to detect changes in the oil palm plantation extent promptly.https://isprs-archives.copernicus.org/articles/XLVIII-G-2025/155/2025/isprs-archives-XLVIII-G-2025-155-2025.pdf |
| spellingShingle | J. Y. P. Ang Z. Q. Ng SAR Oil Palm Plantation Mapping in Batu Pahat with X, C, L bands for Change Detection The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | SAR Oil Palm Plantation Mapping in Batu Pahat with X, C, L bands for Change Detection |
| title_full | SAR Oil Palm Plantation Mapping in Batu Pahat with X, C, L bands for Change Detection |
| title_fullStr | SAR Oil Palm Plantation Mapping in Batu Pahat with X, C, L bands for Change Detection |
| title_full_unstemmed | SAR Oil Palm Plantation Mapping in Batu Pahat with X, C, L bands for Change Detection |
| title_short | SAR Oil Palm Plantation Mapping in Batu Pahat with X, C, L bands for Change Detection |
| title_sort | sar oil palm plantation mapping in batu pahat with x c l bands for change detection |
| url | https://isprs-archives.copernicus.org/articles/XLVIII-G-2025/155/2025/isprs-archives-XLVIII-G-2025-155-2025.pdf |
| work_keys_str_mv | AT jypang saroilpalmplantationmappinginbatupahatwithxclbandsforchangedetection AT zqng saroilpalmplantationmappinginbatupahatwithxclbandsforchangedetection |