Spatial Patterns of NDVI Vegetation Greenness Index and NDWI Water Content Index Using Sentinel 2A Imagery

Abstract

Sentinel-2A imagery in forestry and environmental studies is critical to keep up with the changes in dynamic forest ecosystems. Sentinel-2A is a European optical imaging satellite forester that supports forest monitoring services, land cover change detection, and disaster management. The study aimed to analyze the vegetation greenness index with the NDVI [Normalized Difference Vegetation Index] and the NDWI water content index [Normalized Difference Water Index] on various land covers. The research method used was digital transformation techniques of both the NDVI and NDWI indices. The results showed that processing image classification in a combination of NDVI and NDWI index values resulted in various land cover variations with different accuracies. The advantages and disadvantages of the variety of index values suggest that it facilitates interpretation in classifying land cover classes. However, distinguishing vegetation classes in terms of color is difficult because some objects' coloring is almost the same.