High Resolution Forest Masking for Seasonal Monitoring with a Regionalized and Colourimetrically Assisted Chorologic Typology

Comparisons of recent global forest products at higher resolutions that are only available annually have shown major disagreements among forested areas in highly fragmented landscapes. A holistic reductionist framework and colourimetry were applied to create a chorologic typology environmental indicators map extent with an emphasis on large-scale performance, interpretability/communication, spatial–temporal scalability. Interpretation keys created identify non-forest features, set candidate tree cover indices developed compared decision matrix prescribed criteria. The intentionally limited those applying the visible NIR bands obtain highest possible resolution be compatible commonly multispectral satellites sensors, including aerial potentially UAV/drone sensors. new High-Resolution Tree Cover Index (HRTCI) combination Green band was selected as best index based scores from matrix. To further improve performance indices, included two insolation water surface saturation index, exclude any remaining spectrally similar but unrelated land features such agriculture, water, built-up using process elimination. approach four seasons across wide range ecosystems south-eastern Australia, without regionalisation, which season produces most accurate results for each ecoregion assess potential mitigating scaling effects Modifiable Spatio-Temporal Unit Problem. Autumn found effective season, yielding overall accuracies 94.19% full extent, 95.79% temperate zone, 95.71% arid zone. It produced greatest spatial agreement between recognised products, GEDI heights ESA WorldCover class. transparency, scalability should provide basis globally relatable monitoring.