Open AccessUpdating land use and land cover classes of Blue Nile basin using landsat-8 images
Author(s) -
A. S. Shobary,
Ahmed S. Elsharkawy,
Hossam Elhanafy,
Osama Moussa
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1172/1/012014
Subject(s) - land cover , watershed , surface runoff , remote sensing , land use , structural basin , hydrology (agriculture) , ground truth , environmental science , drainage basin , agricultural land , geography , cartography , agriculture , geology , computer science , archaeology , geomorphology , artificial intelligence , ecology , civil engineering , geotechnical engineering , machine learning , engineering , biology
Land Use and Land Cover are considered as a main input layer for the estimation of surface runoff along with the soil maps, rainfall data, DEM. The main purpose of this research paper is to update the Land Cover and Land Use of the Blue Nile basin that can be used for further processing to estimate the surface runoff of the Blue Nile basin. Recent satellite images of Landsat 8, dated May and June, 2020, were used with less than 10% clouds covering the full scene of the study area. Six land cover classes were targeted namely; water, urban, barren land, forest, grass and agricultural crops. Supervised (maximum likelihood) classification method was used and accuracy assessment with the help of google earth as ground truth was performed. With the aid of 30-m DEM, the Blue Nile basin was divided into fourteen sub-watersheds. Classification scheme was applied to each of the fourteen sub-watersheds and the classification results were introduced as a percentage of the total area of each sub-watershed. Moreover, confusion matrices were formed for the sub-watersheds.