Comparison of regional monitoring methods for grassland degradation based on remote sensing images

As an integral part of the ecosystem, grassland plays an important role in protecting water and soil, preventing wind and fixing sand and protecting biodiversity. However, some grasslands are degraded at this stage, so a grassland monitoring method is urgently needed to prevent desertification from spreading. With the rapid rise of deep learning, it is more and more popular to apply artificial intelligence methods to grassland degradation monitoring. This paper systematically and comprehensively analyzes that almost all semantic segmentation methods have been applied to relevant research on grassland degradation areas since semantic segmentation methods were applied to grassland monitoring. Then, according to the different algorithm structures of grassland extraction methods, the principles of representative algorithms are introduced in turn. Then we made a statistical analysis of the publication status, research space distribution and the number of citations of papers in this field. Finally, the analysis results are discussed, and the possible research hotspots in the future are discussed.