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Semi-Automated Semantic Segmentation of Arctic Shorelines Using Very High-Resolution Airborne Imagery, Spectral Indices and Weakly Supervised Machine Learning Approaches
land water segmentation remote sensing deep learning sparse labels
2023/12/5
Precise coastal shoreline mapping is essential for monitoring changes in erosion rates, surface hydrology, and ecosystem structure and function. Monitoring water bodies in the Arctic National Wildlife...
Semantic Segmentation and Analysis on Sensitive Parameters of Forest Fire Smoke Using Smoke-Unet and Landsat-8 Imagery
forest fire remote sensing smoke segmentation Smoke-Unet attention mechanism residual block Landsat-8 band sensibility
2023/12/5
Forest fire is a ubiquitous disaster which has a long-term impact on the local climate as well as the ecological balance and fire products based on remote sensing satellite data have developed rapidly...
Development of Semantic Maps of Vegetation Cover from UAV Images to Support Planning and Management in Fine-Grained Fire-Prone Landscapes
U-Net convolutional neural network (CNN) shrub detection heterogeneous land cover mapping UAV imagery Mediterranean forest
2023/12/1
In Mediterranean landscapes, the encroachment of pyrophytic shrubs is a driver of more frequent and larger wildfires. The high-resolution mapping of vegetation cover is essential for sustainable land ...