Abstract
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.
Highlights
With the aim of finding all scientific articles studying tropical moist forest degradation with remote sensing tools, a systematic review was realized using the following inclusion criteria: (1) forest degradation is caused by human intervention; (2) remote sensing is used to detect forest degradation; (3) the study is localized in a tropical moist forest
Most of the studies are carried out on a local or landscape scale on areas ranging from plots of a few hectares [53], to forest management unit [54,55], or areas delimited by remote sensing data acquisition footprint (e.g., Landsat tiles [56])
In Amazonia, a regional biomass map was made by linking a canopy height model from remote sensing with an individual-based forest model [62]
Summary
While unprecedented climate change is taking place on a global scale, mainly caused by human carbon emissions [1], and while the great majority of indicators of ecosystems and biodiversity are showing a rapid decline because of human drivers [2,3], forests are important to preserve. Tropical forests are experiencing significant degradation [9], defaunation and deforestation [3,7,10], mainly caused by human activities [2]. Even if tropical forest loss is responsible for significant carbon emissions [11,12], these forests are today still considered as a carbon sink [7,13]. This trend could not continue over the decades because carbon sink saturation will appear in tropical forests, firstly in the Amazon and secondly in Africa [13]
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