In addition, we estimated the forest change area using an unbiased stratified estimator that can be used with a small sample of reference data. TRP was used to construct forest change maps during the study period for which the final user’s accuracy was 86% and the final producer’s accuracy was 92%. We processed 572 PlanetScope images acquired between 1 May 2018 and 5 July 2019.
To calibrate and validate TRP, a reference set was constructed as a complete census of five randomly selected study areas in Tuscany, Italy. It produces a new forest change map as soon as a new PlanetScope image is acquired. We present a near-real time forest disturbance alert system based on PlanetScope imagery: the Thresholding Rewards and Penances algorithm (TRP). For this purpose, the new Planetscope nano-satellite constellation is a game changer, with a revisit time of 1 day and a pixel size of 3-m. To combat global deforestation, monitoring forest disturbances at sub-annual scales is a key challenge.
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