Research on Remote Sensing Monitoring Technology for Land Desertification Based on YOLOv9

The global ecological and environmental problems are severe, and effective monitoring of desertification land is an important prerequisite for protecting and controlling desertification land. This article is based on the remote sensing monitoring technology of land desertification using the object detection algorithm YOLOv9, in order to provide more accurate and efficient monitoring methods for ecological environment protection and governance. As the latest achievement of the YOLO series, YOLOv9 provides a new technological path for complex surface feature recognition with its outstanding speed, accuracy, and excellent detection ability for multi-scale targets. This article first reviews the application progress of remote sensing technology in the field of land desertification monitoring, analyzes the limitations of existing technologies, especially the challenges of small-scale desertification feature recognition and dynamic monitoring. Subsequently, this article provides a detailed introduction to the core technological innovations of YOLOv9, including programmable gradient information (PPG) strategy, efficient layer aggregation network (GELAN) structure, and multi-scale detection optimized feature pyramid network. Through these improvements, YOLOv9 can more effectively capture desertification characteristics of different textures and cover types, especially in monitoring desertification processes in areas with sparse vegetation and complex terrain.