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Extending deep learning approaches for forest disturbance segmentation on very high‐resolution satellite images
Remote Sensing in Ecology and Conservation
Accurate remote detection of various forest disturbances is a challenge in global environmental monitoring. Addressing this issue is crucial for forest health assessment, planning salvage logging operations, modeling stand dynamics, and estimating forest carbon stocks and uptake. Substantial progress on this problem has been achieved owing to the rapid development of remote sensing devices that provide very high-resolution images. Concurrently, image processing algorithms have witnessed rapiddoi:10.1002/rse2.194 fatcat:t443vrewgjcljc45zonqn5axnu