Vegetation indices calculated using Landsat satellite images and GRASS GIS for environmental mapping of the Cape Town region, South Africa

Abstract

The development of the programming techniques and scripting languages integrated in GIS, facilitated satellite image processing for obtaining information from the remote sensing data. In this paper, the effectiveness of integration of space observation multi-temporal data with scripting techniques is demonstrated with an example from South Africa. Four Landsat images covering the coastal region of Cape Town were acquired from the USGS for years 2016, 2018, 2021 and 2023. Their processing enabled the calculation of four vegetation indices using 'i.vi' module of GRASS GIS: DVI, NDVI, SAVI and CI. The index values were mapped for each of the processed images. These maps reflect changes in land use since 2016, such as deforestation and expansion of agricultural land.