A Novel Spectral Index for Vegetation Destruction Event Detection Based on Multispectral Remote Sensing Imagery

Monitoring frequent vegetation destruction events is important for ecological conservation and environmental management. Satellite remote sensing technology is a vital tool for vegetation monitoring. Compared with the classifier-based methods, the spectral index-based methods have the advantages of fast speed and low cost. However, due to the complexity of the background environment and the spectral diversity of vegetation destruction events, there is still a lack of universal spectral indices suitable for various vegetation destruction events, and the existing spectral indices lack applicability in complex scenes. In this article, we proposed a new spectral index (called baseline-based vegetation destruction index, BVDI) using the distance from the red band to the baseline formed by the green and near-infrared bands to detect various vegetation destruction events in complex scenes. PROSAIL simulation data, various possible vegetation change scenes, and multiple vegetation destruction cases were utilized to evaluate the performance of BVDI. The results showed that BVDI was superior to the four developed indices (NDVI, EVI, NDMI, and NBR) in highlighting vegetation information while suppressing background information. In addition, BVDI showed strong robustness in cases of vegetation destruction caused by events such as wildfires, logging, insect infestations, landslides, and floods. Compared with the two data products (GLADFA and CEMS), the BVDI-based method provided more detailed spatial information. In addition, BVDI exhibited broad applicability to other multispectral sensors (Landsat-8 and Landsat-9). Therefore, BVDI is an efficient and robust spectral indicator that provides technical support for regional and even global vegetation monitoring and diagnosis.