Deforestation Estimation

Accurately estimating deforestation, particularly in vast and inaccessible regions like the Amazon, is crucial for environmental monitoring and conservation efforts. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs) and U-Net architectures, often incorporating multimodal data from various satellite sensors (e.g., Landsat, Sentinel) including both optical and Synthetic Aperture Radar (SAR) imagery to overcome weather limitations. These advanced methods aim to improve the precision and efficiency of deforestation detection, providing valuable data for environmental management and policy decisions. The development of standardized datasets and challenges, like the MultiEarth initiatives, fosters collaboration and facilitates the comparison of different approaches within the scientific community.