Identification of Potential Surface Water Resources for Inland Aquaculture from Sentinel-2 Images of the Rwenzori Region of Uganda

Aquaculture has the potential to sustainably meet growing demand for animal protein. The availability of water is essential aquaculture development, but there no knowledge about inland resources Rwenzori region Uganda. Though remote sensing popularly utilized during studies involving various aspects surface water, it never been employed in mapping bodies In this study, we assessed efficiency seven remote-sensing derived index methods map available using moderate resolution Sentinel 2A/B imagery. From four targeted sites, Automated Water Extraction Index urban areas (AWEInsh) and shadow removal (AWEIsh) were best at identifying region. Both AWEIsh AWEInsh consistently had highest overall accuracy (OA) kappa (OA > 90%, 0.8 sites 1 2; OA 84.9%, 0.61 3 4), as well lowest omission errors all sites. AWEI was able suppress classification noise from shadows other non-water dark surfaces. However, none indices used study efficiently extract narrow such streams. This due a combination factors like presence terrain shadows, dense vegetation cover, image resolution. Nonetheless, can identify crater lakes rivers/streams that are potentially suitable