GIS and Remote Sensing Based Land Use/Land Cover Change Detection and Prediction in FagitaLekomaWoreda, Awi Zone, North Western Ethiopia
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Date
2015-06
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Addis Ababa University
Abstract
This project examines the use of GIS and Remote Sensing in mapping Land Use/Land Cover in FagitaLekomaWoreda between 1973 and 2015 so as to detect and analyze the changes that has taken place in their status between these periods.
In order to achieve these, satellite data of Landsat MSS for 1973, TM for 1987 and ETM for 2015 have been obtained and preprocessed using ERDAS Imagine. The Maximum Likelihood Algorithm of Supervised Classification has been used to generate land use and land cover maps. For the accuracy of classified Land Use/Land Cover maps, a confusion matrix was used to derive overall accuracy and results were above the minimum and acceptable threshold level. Post-classification comparison change detection method was employed to identify gains and losses between Land Use/Land Cover classes. Subsequently, an attempt was made to predict for the next 28 years change based on the observed Land Use/Land Cover changes using Marcov Chain Model.
The satellite image results show that cultivated land increased in the first period but decline in the second and the entire study periods.Grassland increased in the first period and decreased in the second period. Wetland is the most converted cover type during the entire study period.In the 42 years, forest lands expanded by over 255% of the original forest cover what was existed at the base year. The impact of this LULC change is more significant on the socioeconomic condition and status of the study area. Urban area which was not found in the first two study years satellite image result have 2.1% proportion in 2015 Land Use/Land Cover classification.
Keywords: FagitaLekoma; Image Classification; GIS; Land Use/Land Cover Change; Marcov Chain Model; Remote Sensing
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Keywords
FagitaLekoma, Image Classification, Land Use Land Cover Change, Remote Sensing, Marcov Chain Model