Optimization of Open-Access Optical and Radar Satellite Data in Google Earth Engine for Oil Palm Mapping in the Muda River Basin, Malaysia
Continuous oil palm distribution maps are essential for effective agricultural planning and management. Due to the significant cloud cover issue in tropical regions, the identification of oil palm from other crops using only optical satellites is difficult. Based on the Google Earth Engine (GEE), th...
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| Format: | Article |
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MDPI AG
2022-09-01
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| Series: | Agriculture |
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| Online Access: | https://www.mdpi.com/2077-0472/12/9/1435 |
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| author | Ju Zeng Mou Leong Tan Yi Lin Tew Fei Zhang Tao Wang Narimah Samat Fredolin Tangang Zulkifli Yusop |
| author_facet | Ju Zeng Mou Leong Tan Yi Lin Tew Fei Zhang Tao Wang Narimah Samat Fredolin Tangang Zulkifli Yusop |
| author_sort | Ju Zeng |
| collection | DOAJ |
| description | Continuous oil palm distribution maps are essential for effective agricultural planning and management. Due to the significant cloud cover issue in tropical regions, the identification of oil palm from other crops using only optical satellites is difficult. Based on the Google Earth Engine (GEE), this study aims to evaluate the best combination of open-source optical and microwave satellite data in oil palm mapping by utilizing the C-band Sentinel-1, L-band PALSAR-2, Landsat 8, Sentinel-2, and topographic images, with the Muda River Basin (MRB) as the test site. The results show that the land use land cover maps generated from the combined images have accuracies from 95 to 97%; the best combination goes to Sentinel-1 and Sentinel-2 for the overall classification. Meanwhile, the best combination for oil palm classification is C5 (PALSAR-2 + Landsat 8), with the highest producer accuracy (96%) and consumer accuracy (100%) values. The combination of C-band radar images can improve the classification accuracy of oil palm, but compared with the combination of L-band images, the oil palm area was underestimated. The oil palm area had increased from 2015 to 2020, ranging from 10% to 60% across all combinations. This shows that the selection of optimal images is important for oil palm mapping. |
| first_indexed | 2024-03-10T01:01:10Z |
| format | Article |
| id | doaj.art-019985284c414483af22e01924d83804 |
| institution | Directory Open Access Journal |
| issn | 2077-0472 |
| language | English |
| last_indexed | 2024-03-10T01:01:10Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agriculture |
| spelling | doaj.art-019985284c414483af22e01924d838042023-11-23T14:33:53ZengMDPI AGAgriculture2077-04722022-09-01129143510.3390/agriculture12091435Optimization of Open-Access Optical and Radar Satellite Data in Google Earth Engine for Oil Palm Mapping in the Muda River Basin, MalaysiaJu Zeng0Mou Leong Tan1Yi Lin Tew2Fei Zhang3Tao Wang4Narimah Samat5Fredolin Tangang6Zulkifli Yusop7GeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, Penang 11800, MalaysiaGeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, Penang 11800, MalaysiaGeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, Penang 11800, MalaysiaCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, ChinaCollege of Geography and Land Engineering, Yuxi Normal University, Yuxi 653100, ChinaGeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, Penang 11800, MalaysiaDepartment of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, MalaysiaCentre for Environmental Sustainability and Water Security (IPASA), Universiti Teknologi Malaysia (UTM), Johor Bharu 81310, MalaysiaContinuous oil palm distribution maps are essential for effective agricultural planning and management. Due to the significant cloud cover issue in tropical regions, the identification of oil palm from other crops using only optical satellites is difficult. Based on the Google Earth Engine (GEE), this study aims to evaluate the best combination of open-source optical and microwave satellite data in oil palm mapping by utilizing the C-band Sentinel-1, L-band PALSAR-2, Landsat 8, Sentinel-2, and topographic images, with the Muda River Basin (MRB) as the test site. The results show that the land use land cover maps generated from the combined images have accuracies from 95 to 97%; the best combination goes to Sentinel-1 and Sentinel-2 for the overall classification. Meanwhile, the best combination for oil palm classification is C5 (PALSAR-2 + Landsat 8), with the highest producer accuracy (96%) and consumer accuracy (100%) values. The combination of C-band radar images can improve the classification accuracy of oil palm, but compared with the combination of L-band images, the oil palm area was underestimated. The oil palm area had increased from 2015 to 2020, ranging from 10% to 60% across all combinations. This shows that the selection of optimal images is important for oil palm mapping.https://www.mdpi.com/2077-0472/12/9/1435Google Earth Engineland useMuda River Basinoil palmMalaysiasentinel |
| spellingShingle | Ju Zeng Mou Leong Tan Yi Lin Tew Fei Zhang Tao Wang Narimah Samat Fredolin Tangang Zulkifli Yusop Optimization of Open-Access Optical and Radar Satellite Data in Google Earth Engine for Oil Palm Mapping in the Muda River Basin, Malaysia Agriculture Google Earth Engine land use Muda River Basin oil palm Malaysia sentinel |
| title | Optimization of Open-Access Optical and Radar Satellite Data in Google Earth Engine for Oil Palm Mapping in the Muda River Basin, Malaysia |
| title_full | Optimization of Open-Access Optical and Radar Satellite Data in Google Earth Engine for Oil Palm Mapping in the Muda River Basin, Malaysia |
| title_fullStr | Optimization of Open-Access Optical and Radar Satellite Data in Google Earth Engine for Oil Palm Mapping in the Muda River Basin, Malaysia |
| title_full_unstemmed | Optimization of Open-Access Optical and Radar Satellite Data in Google Earth Engine for Oil Palm Mapping in the Muda River Basin, Malaysia |
| title_short | Optimization of Open-Access Optical and Radar Satellite Data in Google Earth Engine for Oil Palm Mapping in the Muda River Basin, Malaysia |
| title_sort | optimization of open access optical and radar satellite data in google earth engine for oil palm mapping in the muda river basin malaysia |
| topic | Google Earth Engine land use Muda River Basin oil palm Malaysia sentinel |
| url | https://www.mdpi.com/2077-0472/12/9/1435 |
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