Afera Halefom1*, Asirat Teshome1, Ermias Sisay1, Deepak Khare2, Mihret Dananto4, Lakhwinder Singh2, Dessalew Tadesse3
1Department of Hydraulic and Water Resourcing Engineering, Debre Tabor University, Debre Tabor, Ethiopia
2Department of Water Resources Development and Management, Indian Institute of Technology Roorkee, Roorkee, India
3Department of Hydraulic and Water Resources Engineering, University of Gondar, Gondar, Ethiopia
4Department of Biosystems and Environmental Engineering, Hawassa University, Ethiopia
*Correspondence to: [email protected], [email protected], [email protected], [email protected], [email protected] [email protected], [email protected]
Article Number: se-j-arjgis-2018.0101001; Volume 1(1), pp 1-9, December, 2018.
https://doi.org/10.47721/ARJGIS201801025
Abstract
Remote Sensing, as a direct adjunct to professional fields, is recently playing an important role in the study and assessment of the natural resource in any part of the world. Anthropogenic changes in land use and land cover and land use are often assumed to be identical, they are rather quite different. Land cover may be defined as the biophysical earth surface, while land use is often shaped by human, socio-economic and political influences on the land. Remote Sensing (RS), integrated with Geographic Information System (GIS), provides an effective tool for analysis of land use and land cover changes. Digital change detection is the process that helps in determining the changes associated with land use and land cover properties with reference to geo-registered multi temporal remote sensing data. The study made use of Land Sat imageries of 1997, 2010 and 2017 to study Werota Watershed, where land use had been greatly affected by recent government policies aimed to balance the need to encourage rural development with ecological stability. The images were classified using Maximum Likelihood classification method in ERDAS 2014 and mapped using ArcGIS. The results of the study indicated that severe land cover changes had occurred in croplands (-227.9%), plantation (+0.63ha), water body (+16.97ha), agricultural land (+152.42ha) and pasture land (+57.42ha) areas and these were the discovered knowledgeable types of land use/land cover in the study period. Therefore the research work shows that land use/land cover change detection using multi-temporal images by means of remote sensing and GIS modelling are good means of analysing dynamic changes in time sequence.
Key words: Remote sensing & GIS, Werota, change detection, LULC, classification scheme
Copyright © 2018 Author(s) and Skies Educational.
This article is published under the terms of the Creative Commons Attribution License 4.0
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Article Number: se-j-arjgis-2018.0101001
