Many grassland studies have depended on or are currently depending on the Landsat series of satellite sensors for monitoring work. However, given the identified gaps in Landsat data, alternatives to Landsat imagery need to be tested in an operational environment. In this study, normalized difference vegetation index (NDVI) values are derived from a Système Pour l'Observation de la Terre (SPOT), Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Very High Resolution Radiometer (AVHRR) image and compared to the NDVI values from a Landsat image for LAI estimation in a semi-arid heterogeneous grassland. Results indicate a high agreement between Landsat and SPOT data with over 85% at all buffer levels (100, 250, and 1000 m), and a significant but lower agreement between MODIS and Landsat with around 28% at 250 m buffer level to 37% at 100 m buffer level. Based on in situ measurements of LAI in 22 homogeneous sites, the relationships established between LAI and NDVI show that SPOT and Landsat could predict LAI with acceptable accuracy, but MODIS and AVHRR cannot quantify the spatial variation in LAI measurements. Data fusion or blending techniques that combine the spectral information of high spatial/low temporal resolution data with low spatial/high temporal resolution data may be considered to study semi-arid heterogeneous grasslands.