Towards operational monitoring of forest canopy disturbance in evergreen rain forests: a test case in continental Southeast Asia

摘要: This study presents an approach to forest canopy disturbance monitoring in evergreen forests continental Southeast Asia, based on temporal differences of a modified normalized burn ratio (NBR) vegetation index. We generate NBR values from each available Landsat 8 scene given period. A step ‘self-referencing’ normalizes the values, largely eliminating illumination/topography effects, thus maximizing inter-comparability. then create yearly composites these self-referenced (rNBR) selecting per pixel maximum rNBR value over observation period, which reflects most open cover condition that pixel. The ΔrNBR is generated as difference between two reference periods. methodology produces seamless and consistent maps, highlighting patterns disturbances (e.g., encroachment, selective logging), keeping artifacts at minimum level. was validated within four test sites with overall accuracy almost 78% using very high resolution satellite imagery. implemented Google Earth Engine (GEE) script requiring no user interaction. threshold applied final output dataset order separate signal noise. approach, capable detecting sub-pixel events small 0.005 ha, transparent reproducible, can help increase credibility monitoring, reporting verification (MRV), required context reducing emissions deforestation degradation (REDD+).