Research on the Application Model of Sensing Technology in Monitoring Landscape Resource Changes

This paper proposes an innovative landscape resource change detection algorithm based on multi-sensor fusion. The algorithm integrates multiple data sources such as remote sensing images, ground meteorological data and climate data, uses data fusion technology to improve monitoring accuracy, and combines spatiotemporal filtering algorithm to accurately detect landscape changes. This paper selects a nature reserve as the experimental area, collects multi-source data sets including remote sensing images, meteorological data and ground sensor data, and detects changes in landscape resources through the algorithm. Compared with the traditional method, the detection accuracy of the proposed algorithm is improved by 12.6%, especially when dealing with changes under complex environmental conditions, it shows strong robustness. In addition, the real-time performance of the algorithm has also been optimized, which can adapt to large-scale, complex and changeable monitoring tasks. The multi-sensor fusion algorithm proposed has significant advantages over the traditional single sensor method in terms of accuracy, stability and real-time performance through experiments.