Luofan Dong , Xiaojing Tang , Foster Mensah , Bashara Ahmed Abubakari , Kelsee H. Bratley , Pontus Olofsson , Curtis E. Woodcock
{"title":"近实时监测显示,加纳保护区最近出现了广泛的森林扰动","authors":"Luofan Dong , Xiaojing Tang , Foster Mensah , Bashara Ahmed Abubakari , Kelsee H. Bratley , Pontus Olofsson , Curtis E. Woodcock","doi":"10.1016/j.srs.2025.100299","DOIUrl":null,"url":null,"abstract":"<div><div>The Protected Areas (PAs) in Ghana play a critical role in preserving the abundant biodiversity of the West Africa Green Belt. But recent changes in policies and regulations have facilitated logging and mining activities, which have accelerated forest disturbances. While there is a consensus that PAs are undergoing destructive change, the extent, rate, and locations of forest disturbances are undocumented. In this study, we applied the fusion near real-time (FNRT) algorithm that utilizes Landsat, Sentinel-1, and Sentinel-2 data and sampling to monitor forests in the PAs of Ghana. The results reveal that 704.74 (±177.24) km<sup>2</sup> of forest in the PAs were lost in 2023 and 2024, representing 6 % (±1.5 %) of their forest area. Additionally, the forest disturbance rate in 2024 was estimated to be 91 % higher than the rate observed in 2023 (95 % CI: 34 %–172 %). Extensive forest disturbance areas were found in the PAs around Kumasi, such as the Tano Ofin (15.4 % ±3.9 %), Tinte Bepo (42 % ± 10.5 %), and Oda River (18.5 % ± 4.7 %) PAs. Native forests in these PAs are at high risk of further degradation or disappearance in the absence of effective conservation measures. We compared the FNRT results with other alert systems, including RADD and GLAD-L. The comparison demonstrates that multi-sensor fusion provides more timely and accurate detection of forest disturbances in the study area.</div></div>","PeriodicalId":101147,"journal":{"name":"Science of Remote Sensing","volume":"12 ","pages":"Article 100299"},"PeriodicalIF":5.2000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Near real-time monitoring reveals extensive recent forest disturbance in Ghana's protected areas\",\"authors\":\"Luofan Dong , Xiaojing Tang , Foster Mensah , Bashara Ahmed Abubakari , Kelsee H. Bratley , Pontus Olofsson , Curtis E. Woodcock\",\"doi\":\"10.1016/j.srs.2025.100299\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The Protected Areas (PAs) in Ghana play a critical role in preserving the abundant biodiversity of the West Africa Green Belt. But recent changes in policies and regulations have facilitated logging and mining activities, which have accelerated forest disturbances. While there is a consensus that PAs are undergoing destructive change, the extent, rate, and locations of forest disturbances are undocumented. In this study, we applied the fusion near real-time (FNRT) algorithm that utilizes Landsat, Sentinel-1, and Sentinel-2 data and sampling to monitor forests in the PAs of Ghana. The results reveal that 704.74 (±177.24) km<sup>2</sup> of forest in the PAs were lost in 2023 and 2024, representing 6 % (±1.5 %) of their forest area. Additionally, the forest disturbance rate in 2024 was estimated to be 91 % higher than the rate observed in 2023 (95 % CI: 34 %–172 %). Extensive forest disturbance areas were found in the PAs around Kumasi, such as the Tano Ofin (15.4 % ±3.9 %), Tinte Bepo (42 % ± 10.5 %), and Oda River (18.5 % ± 4.7 %) PAs. Native forests in these PAs are at high risk of further degradation or disappearance in the absence of effective conservation measures. We compared the FNRT results with other alert systems, including RADD and GLAD-L. The comparison demonstrates that multi-sensor fusion provides more timely and accurate detection of forest disturbances in the study area.</div></div>\",\"PeriodicalId\":101147,\"journal\":{\"name\":\"Science of Remote Sensing\",\"volume\":\"12 \",\"pages\":\"Article 100299\"},\"PeriodicalIF\":5.2000,\"publicationDate\":\"2025-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science of Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666017225001051\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science of Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666017225001051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Near real-time monitoring reveals extensive recent forest disturbance in Ghana's protected areas
The Protected Areas (PAs) in Ghana play a critical role in preserving the abundant biodiversity of the West Africa Green Belt. But recent changes in policies and regulations have facilitated logging and mining activities, which have accelerated forest disturbances. While there is a consensus that PAs are undergoing destructive change, the extent, rate, and locations of forest disturbances are undocumented. In this study, we applied the fusion near real-time (FNRT) algorithm that utilizes Landsat, Sentinel-1, and Sentinel-2 data and sampling to monitor forests in the PAs of Ghana. The results reveal that 704.74 (±177.24) km2 of forest in the PAs were lost in 2023 and 2024, representing 6 % (±1.5 %) of their forest area. Additionally, the forest disturbance rate in 2024 was estimated to be 91 % higher than the rate observed in 2023 (95 % CI: 34 %–172 %). Extensive forest disturbance areas were found in the PAs around Kumasi, such as the Tano Ofin (15.4 % ±3.9 %), Tinte Bepo (42 % ± 10.5 %), and Oda River (18.5 % ± 4.7 %) PAs. Native forests in these PAs are at high risk of further degradation or disappearance in the absence of effective conservation measures. We compared the FNRT results with other alert systems, including RADD and GLAD-L. The comparison demonstrates that multi-sensor fusion provides more timely and accurate detection of forest disturbances in the study area.