Evaluating Remote Sensing Techniques for Monitoring Grassland Degradation

Ecosystem degradation represents one of the most significant environmental challenges facing the globe. Of particular concern is the impact of grassland degradation on agricultural productivity, species diversity, and soil erosion. This study aimed to compare the applicability of two remote sensing techniques, the Linear Spectral Mixture Model (LSM) and the Grassland Degradation Index (GDI), in assessing and defining the degree of grassland degradation. The results demonstrated that the GDI exhibited superior overall accuracy than LSM, with an accuracy rate of 73.49% as opposed to 63.16% for the LSM. Additionally, the GDI demonstrated a higher F1 score across all evaluated classes, indicating an enhanced capacity to identify true positives and minimise false positives and negatives. Both techniques demonstrated satisfactory performance and can be employed to support restoration and sustainable management studies.