Satellite image fusion techniques have been used for more than two decades. Development of satellite sensors for very high-resolution satellite imagery monitoring contributed to the development of new image fusion techniques. We examine the quality of Ehlers, Brovey transform, modified intensity–hue–saturation (M-IHS), and high-filter resolution merge fusion methods on vegetation indices values combining high-resolution WorldView-4 and low-resolution Sentinel-2 imagery. For image fusion, four bands—blue, green, red, and near-infrared—were used. The effect of fusing Sentinel-2 and WorldView-4 imagery is tested on the various vegetation indices [normalized difference vegetation index (NDVI), blue normalized difference vegetation index (BNDVI), and green normalized difference vegetation index (GNDVI)]. M-IHS fusion showed the best result, with the least difference between indices calculated based on the original Sentinel-2 and fused bands. Difference between vegetation indices calculated using original Sentinel-2 and M-IHS fused bands for 30.08.2015, 30.09.2016, and 30.09.2017 is between −0.041 to 0.037. The second part of this research is an evaluation of three different vegetation classes (grassland, mixed vegetation, and forest) on three different years and three different months within a year. Difference between NDVI, GNDVI, and BNDVI calculated based on the original Sentinel-2, and M-IHS fused bands are ranging from −0.043 to 0.103, −0.041 to 0.050, and −0.052 to 0.030 for grassland, mixed vegetation, and forest, respectively. On the other hand, the difference between vegetation indices for grassland, mixed vegetation, and forest are from −0.110 to 0.050, −0.041 to 0.038, and −0.052 to 0.038, when observing August, September, and October of 2017, respectively.
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