Refining National Forest Cover Data Based on Fusion Optical Satellite Imageries in Indonesia
Precision mapping towards tropical forest cover data is critical to address the global climate crisis, such as land-based carbon measurement and potential conservation areas identification. In the recent decade, accessibility to open public datasets on forestry is rapidly increased. However, the ava...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2023-01-01
|
| Series: | International Journal of Forestry Research |
| Online Access: | http://dx.doi.org/10.1155/2023/7970664 |
| _version_ | 1827008924862119936 |
|---|---|
| author | Ogy Dwi Aulia Isnenti Apriani Andi Juanda Mufti Fathul Barri Rosima Wati Dewi Fauzan Nafis Muharam Bryandanu Oktanine Theresia Bernadette Phoa Aryo Adhi Condro |
| author_facet | Ogy Dwi Aulia Isnenti Apriani Andi Juanda Mufti Fathul Barri Rosima Wati Dewi Fauzan Nafis Muharam Bryandanu Oktanine Theresia Bernadette Phoa Aryo Adhi Condro |
| author_sort | Ogy Dwi Aulia |
| collection | DOAJ |
| description | Precision mapping towards tropical forest cover data is critical to address the global climate crisis, such as land-based carbon measurement and potential conservation areas identification. In the recent decade, accessibility to open public datasets on forestry is rapidly increased. However, the availability of finer-resolution of forest cover data is still very limited. As a developing country with numerous rainforests, Indonesia suffered multifaceted threats, particularly deforestation. Thus, precise forest cover data can be useful to fulfill Indonesia’s nationally determined contribution to climate change. In this study, we mapped the national forest cover data for Indonesia using a new object-based image classification approach based on combined Planet-NICFI and Sentinel-2 optical imageries. Our findings had relatively high accuracy compared with the other studies, with the F score ranging from 0.67 to 0.99 and can capture the fragmented forest in fine resolution (i.e., ∼5 m). In addition, we found that Planet-NICFI bands had a higher contribution in predicting forest cover than Sentinel-2 imageries. Utilizing forest cover data for further analyses should be performed to help the achievement of national and global agenda, e.g., related to the FOLU net sink in 2030 and the Global Biodiversity Framework. |
| first_indexed | 2024-03-12T13:28:43Z |
| format | Article |
| id | doaj.art-afe715e0e65344c9923fb1f706cd5c5c |
| institution | Directory Open Access Journal |
| issn | 1687-9376 |
| language | English |
| last_indexed | 2025-02-18T12:39:31Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi Limited |
| record_format | Article |
| series | International Journal of Forestry Research |
| spelling | doaj.art-afe715e0e65344c9923fb1f706cd5c5c2024-11-02T04:12:18ZengHindawi LimitedInternational Journal of Forestry Research1687-93762023-01-01202310.1155/2023/7970664Refining National Forest Cover Data Based on Fusion Optical Satellite Imageries in IndonesiaOgy Dwi Aulia0Isnenti Apriani1Andi Juanda2Mufti Fathul Barri3Rosima Wati Dewi4Fauzan Nafis Muharam5Bryandanu Oktanine6Theresia Bernadette Phoa7Aryo Adhi Condro8Department of Data and InformationDepartment of Data and InformationDepartment of Data and InformationDepartment of Data and InformationEnvironmental Analysis and Geospatial Modelling LaboratoryDepartment of Geophysics and MeteorologyDepartment of Geophysics and MeteorologyDepartment of Atmospheric ScienceEnvironmental Analysis and Geospatial Modelling LaboratoryPrecision mapping towards tropical forest cover data is critical to address the global climate crisis, such as land-based carbon measurement and potential conservation areas identification. In the recent decade, accessibility to open public datasets on forestry is rapidly increased. However, the availability of finer-resolution of forest cover data is still very limited. As a developing country with numerous rainforests, Indonesia suffered multifaceted threats, particularly deforestation. Thus, precise forest cover data can be useful to fulfill Indonesia’s nationally determined contribution to climate change. In this study, we mapped the national forest cover data for Indonesia using a new object-based image classification approach based on combined Planet-NICFI and Sentinel-2 optical imageries. Our findings had relatively high accuracy compared with the other studies, with the F score ranging from 0.67 to 0.99 and can capture the fragmented forest in fine resolution (i.e., ∼5 m). In addition, we found that Planet-NICFI bands had a higher contribution in predicting forest cover than Sentinel-2 imageries. Utilizing forest cover data for further analyses should be performed to help the achievement of national and global agenda, e.g., related to the FOLU net sink in 2030 and the Global Biodiversity Framework.http://dx.doi.org/10.1155/2023/7970664 |
| spellingShingle | Ogy Dwi Aulia Isnenti Apriani Andi Juanda Mufti Fathul Barri Rosima Wati Dewi Fauzan Nafis Muharam Bryandanu Oktanine Theresia Bernadette Phoa Aryo Adhi Condro Refining National Forest Cover Data Based on Fusion Optical Satellite Imageries in Indonesia International Journal of Forestry Research |
| title | Refining National Forest Cover Data Based on Fusion Optical Satellite Imageries in Indonesia |
| title_full | Refining National Forest Cover Data Based on Fusion Optical Satellite Imageries in Indonesia |
| title_fullStr | Refining National Forest Cover Data Based on Fusion Optical Satellite Imageries in Indonesia |
| title_full_unstemmed | Refining National Forest Cover Data Based on Fusion Optical Satellite Imageries in Indonesia |
| title_short | Refining National Forest Cover Data Based on Fusion Optical Satellite Imageries in Indonesia |
| title_sort | refining national forest cover data based on fusion optical satellite imageries in indonesia |
| url | http://dx.doi.org/10.1155/2023/7970664 |
| work_keys_str_mv | AT ogydwiaulia refiningnationalforestcoverdatabasedonfusionopticalsatelliteimageriesinindonesia AT isnentiapriani refiningnationalforestcoverdatabasedonfusionopticalsatelliteimageriesinindonesia AT andijuanda refiningnationalforestcoverdatabasedonfusionopticalsatelliteimageriesinindonesia AT muftifathulbarri refiningnationalforestcoverdatabasedonfusionopticalsatelliteimageriesinindonesia AT rosimawatidewi refiningnationalforestcoverdatabasedonfusionopticalsatelliteimageriesinindonesia AT fauzannafismuharam refiningnationalforestcoverdatabasedonfusionopticalsatelliteimageriesinindonesia AT bryandanuoktanine refiningnationalforestcoverdatabasedonfusionopticalsatelliteimageriesinindonesia AT theresiabernadettephoa refiningnationalforestcoverdatabasedonfusionopticalsatelliteimageriesinindonesia AT aryoadhicondro refiningnationalforestcoverdatabasedonfusionopticalsatelliteimageriesinindonesia |