Remote sensing plays a significant role in the monitoring of the undulating the Himalayas. With continuous monitoring, the preservation of natural resources and mitigation of natural hazards is possible. Currently, satellite sensors are not capable enough to deliver the earth's surface image at a very high temporal, spectral, and spatial resolution, simultaneously. Therefore, it is essential to perform the pan-sharpening of spatially high-resolution (HR) panchromatic (PAN) spectral band with low-resolution (LR) multispectral (MS) imagery which must be acquired on the same temporal date from multiple sensors. On the other hand, due to the rugged topography of the Himalayas, topographic effects are generally induced in the form of shadow and affect the spatial information or spectral information.
Process of Pan-sharpening (Fusion)
For regional or global scale studies, the LR satellite dataset is more preferable and can be merged with the HR dataset with nearest-neighbor diffusion (NND) -based pan-sharpening algorithm. With visual interpretation, it is apparent that NND pan-sharpening with topographic correction offers more reliable information by effectively removing the shadow effects as compared with NND pan-sharpening without topographic correction.
Singh et al. (2020) address the topographic correction is required to be implemented with NND-based pan-sharpening and other classification models. For experimental purposes, AWiFS as HR-PAN data and MODIS as LR-MS data have been used.
Reference: Singh, S., Sood, V., Prashar, S. and Kaur, R., 2020. Response of topographic control on nearest-neighbor diffusion-based pan-sharpening using multispectral MODIS and AWiFS satellite dataset. Arabian Journal of Geosciences, 13(14), pp.1-9.
