How Can Remote Sensing Help Monitor Tropical Moist Forest Degradation?-A Systematic Review

编号 030027104

推送时间 20201228

研究领域 森林经理 

年份 2020 

类型 期刊 

语种 英语

标题 How Can Remote Sensing Help Monitor Tropical Moist Forest Degradation?-A Systematic Review

来源期刊 REMOTE SENSING

期 第271期

发表时间 20200328

关键词 tropical moist forest;  forest degradation;  remote sensing;  forest degradation metrics;  forest resilience;  forest structure;  forest composition;  forest regeneration; 

摘要 In the context of the climate and biodiversity crisis facing our planet, tropical forests playing a key role in global carbon flux and containing over half of Earth's species are important to preserve. They are today threatened by deforestation but also by forest degradation, which is more difficult to study. Here, we performed a systematic review of studies on moist tropical forest degradation using remote sensing and fitting indicators of forest resilience to perturbations. Geographical repartition, spatial extent and temporal evolution were analyzed. Indicators of compositional, structural and regeneration criteria were noted as well as remote sensing indices and metrics used. Tropical moist forest degradation is not extensively studied especially in the Congo basin and in southeast Asia. Forest structure (i.e., canopy gaps, fragmentation and biomass) is the most widely and easily measured criteria with remote sensing, while composition and regeneration are more difficult to characterize. Mixing LiDAR/Radar and optical data shows good potential as well as very high-resolution satellite data. The awaited GEDI and BIOMASS satellites data will fill the actual gap to a large extent and provide accurate structural information. LiDAR and unmanned aerial vehicles (UAVs) form a good bridge between field and satellite data. While the performance of the LiDAR is no longer to be demonstrated, particular attention should be brought to the UAV that shows great potential and could be more easily used by local communities and stakeholders.

服务人员 付贺龙

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