MAPPING WOODLANDS IN ANGOLA, TROPICAL AFRICA: CALCULATION OF VEGETATION INDICES FROM REMOTE SENSING DATA

Abstract

This paper presents the application of the scripting algorithm GRASS GIS for calculation and visualization of vegetation indices using satellite data. The data include satellite images Landsat-8 OLI/TIRS covering tropical rainforests of central Angola. The images were acquired in July 2013 and July 2023. The methodology is based on using module 'i.vi' of GRASS GIS which automatically calculated 10 vegetation indices: DVI, NDVI, ARVI, EVI, GEMI, MSAVI2, NDWI, PVI, GARI and IPVI. The algorithms of data processing and calculation of vegetation indices are presented in the scripts. The results include the extracted information on distribution of bright green vegetation compared with other land cover types: tropical forests and coastal areas distinguished from artificial surfaces and urban areas, soils and coastal shores. The results indicated landscape dynamics in Angola with decline in tropical forests since 2013 until 2023. The machine-based workflow increases computational efficiency through fast processing of satellite data. The use of scripts demonstrated that programming method of automated information extraction from satellite images is effective for environmental monitoring of tropical African landscapes in rainforests.