Application of Remote Sensing in Desertification Monitoring

Abstract

Desertification has become one of the greatest international concerns in recent decades. This study mainly focuses on the significance and necessity of applying remote sensing to improve efficiency in desertification monitoring. Results show that applications of remote sensing in desertification monitoring have shown advantages and promises of development in the future. Satellite images and unmanned aerial vehicle technology are two major sources of remote sensing data. This study also contains specific applications of remote sensing techniques, including normalized difference vegetation index (NDVI), land cover classification, and spectral mixture analysis (SMA). NDVI measures the vegetation cover to reflect potential desertification but fails to offer a comprehensive picture of the desertification status of an area. While land cover classification identifies different types of land use to monitor desertification, track changes over time, and find potential environmental stressors, the technique requires huge investments in technology and labor. SMA, the sub-pixel classification technique, provides a detailed analysis while consuming significant computing resources and time. This study also provides prospects for future developments of data acquisition and analysis approaches in desertification monitoring using remote sensing. Making suggestions on future research topics and possible methodologies, this study hopes to inspire further research in this area to better deal with the global issue of desertification.