Remote sensing data providesan important source for monitoring and mapping vegetation cover. Vegetation Indices (VI) are derived from multispectral satellite datafor use in monitoring vegetation distribution. This paper assesses the potential of SAVI (Soil-Adjusted Vegetation Index) and NDVI (Normalized Difference Vegetation Index), and uses these to demonstrate the production of plant coverpercentage maps in the Jeffara Plain, Libya,using spatial resolution remote sensing imagery in this semi-arid and arid region. A study region in the Jeffara Plain of 13,800ha was selected to permit processing of training and evaluation data due to the variety in irrigated agricultural area and natural vegetation cover densities. The area also provides a variety ofclimatic and soil conditions. A Landsat image was obtained on March 15, 2016, having a pixel resolution of 30 m over this area and used to compare both vegetation indices. Once obtained, a radiometric correction was applied to the image to produce reflectance and ground reflectance, mosaic, and subset. This data was thenclassified to produce a reference of vegetation cover. The values of each index were compared to the equivalent proportion of the area covered by vegetation. A virtual field study was undertakenusing Google Earth for accuracy assessment purposes. Results indicated that SAVI is best suited in this region, with SAVI resultsproviding an R2 of 0.88, whereas NDVIprovided an R2 of 0.86.Overall, SAVI is considered more appropriatefor use in this semi-arid area even though it requires atmospheric correction. The plant coverpercentagemap for the Jeffara Plain was obtained by determining the threshold values of the plant cover percentage using the SAVI index, validated using avisual assessment method based on the use of high resolution images (Digital Globe) from Google Earth.