Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia
Over the last 18 years, Indonesia has experienced significant deforestation due to the expansion of oil palm and rubber plantations. Accurate land cover maps are essential for policymakers to track and manage land change to support sustainable forest management and investment decisions. An automatic...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/1/3 |
| _version_ | 1797497756406775808 |
|---|---|
| author | Inggit Lolita Sari Christopher J. Weston Glenn J. Newnham Liubov Volkova |
| author_facet | Inggit Lolita Sari Christopher J. Weston Glenn J. Newnham Liubov Volkova |
| author_sort | Inggit Lolita Sari |
| collection | DOAJ |
| description | Over the last 18 years, Indonesia has experienced significant deforestation due to the expansion of oil palm and rubber plantations. Accurate land cover maps are essential for policymakers to track and manage land change to support sustainable forest management and investment decisions. An automatic digital processing (ADP) method is currently used to develop land cover change maps for Indonesia, based on optical imaging (Landsat). Such maps produce only forest and non-forest classes, and often oil palm and rubber plantations are misclassified as native forests. To improve accuracy of these land cover maps, this study developed oil palm and rubber plantation discrimination indices using the integration of Landsat-8 and synthetic aperture radar Sentinel-1 images. Sentinel-1 VH and VV difference (>7.5 dB) and VH backscatter intensity were used to discriminate oil palm plantations. A combination of Landsat-8 NDVI, NDMI with Sentinel-1 VV and VH were used to discriminate rubber plantations. The improved map produced four land cover classes: native forest, oil palm plantation, rubber plantation, and non-forest. High-resolution SPOT 6/7 imagery and ground truth data were used for validation of the new classified maps. The map had an overall accuracy of 92%; producer’s accuracy for all classes was higher than 90%, except for rubber (65%), and user’s accuracy was over 80% for all classes. These results demonstrate that indices developed from a combination of optical and radar images can improve our ability to discriminate between native forest and oil palm and rubber plantations in the tropics. The new mapping method will help to support Indonesia’s national forest monitoring system and inform monitoring of plantation expansion. |
| first_indexed | 2024-03-10T03:23:48Z |
| format | Article |
| id | doaj.art-2816eb38d6104bdd800ba3fb0f6ab378 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T03:23:48Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-2816eb38d6104bdd800ba3fb0f6ab3782023-11-23T12:11:38ZengMDPI AGRemote Sensing2072-42922021-12-01141310.3390/rs14010003Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in IndonesiaInggit Lolita Sari0Christopher J. Weston1Glenn J. Newnham2Liubov Volkova3School of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Creswick, VIC 3363, AustraliaSchool of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Creswick, VIC 3363, AustraliaCSIRO Land and Water, Private Bag 10, Clayton South, VIC 3169, AustraliaSchool of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Creswick, VIC 3363, AustraliaOver the last 18 years, Indonesia has experienced significant deforestation due to the expansion of oil palm and rubber plantations. Accurate land cover maps are essential for policymakers to track and manage land change to support sustainable forest management and investment decisions. An automatic digital processing (ADP) method is currently used to develop land cover change maps for Indonesia, based on optical imaging (Landsat). Such maps produce only forest and non-forest classes, and often oil palm and rubber plantations are misclassified as native forests. To improve accuracy of these land cover maps, this study developed oil palm and rubber plantation discrimination indices using the integration of Landsat-8 and synthetic aperture radar Sentinel-1 images. Sentinel-1 VH and VV difference (>7.5 dB) and VH backscatter intensity were used to discriminate oil palm plantations. A combination of Landsat-8 NDVI, NDMI with Sentinel-1 VV and VH were used to discriminate rubber plantations. The improved map produced four land cover classes: native forest, oil palm plantation, rubber plantation, and non-forest. High-resolution SPOT 6/7 imagery and ground truth data were used for validation of the new classified maps. The map had an overall accuracy of 92%; producer’s accuracy for all classes was higher than 90%, except for rubber (65%), and user’s accuracy was over 80% for all classes. These results demonstrate that indices developed from a combination of optical and radar images can improve our ability to discriminate between native forest and oil palm and rubber plantations in the tropics. The new mapping method will help to support Indonesia’s national forest monitoring system and inform monitoring of plantation expansion.https://www.mdpi.com/2072-4292/14/1/3land cover mappingoil palm and rubber plantationsLandsat-8Sentinel-1decision treeIndonesia |
| spellingShingle | Inggit Lolita Sari Christopher J. Weston Glenn J. Newnham Liubov Volkova Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia Remote Sensing land cover mapping oil palm and rubber plantations Landsat-8 Sentinel-1 decision tree Indonesia |
| title | Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia |
| title_full | Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia |
| title_fullStr | Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia |
| title_full_unstemmed | Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia |
| title_short | Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia |
| title_sort | developing multi source indices to discriminate between native tropical forests oil palm and rubber plantations in indonesia |
| topic | land cover mapping oil palm and rubber plantations Landsat-8 Sentinel-1 decision tree Indonesia |
| url | https://www.mdpi.com/2072-4292/14/1/3 |
| work_keys_str_mv | AT inggitlolitasari developingmultisourceindicestodiscriminatebetweennativetropicalforestsoilpalmandrubberplantationsinindonesia AT christopherjweston developingmultisourceindicestodiscriminatebetweennativetropicalforestsoilpalmandrubberplantationsinindonesia AT glennjnewnham developingmultisourceindicestodiscriminatebetweennativetropicalforestsoilpalmandrubberplantationsinindonesia AT liubovvolkova developingmultisourceindicestodiscriminatebetweennativetropicalforestsoilpalmandrubberplantationsinindonesia |