Detecting and quantifying land use/land cover dynamics in Wadla Delanta Massif, northcentral highlands of Ethiopia

Abstract

For sustainable land management and increased agricultural productivity, detailed and accurate information on land resources, including on land use/land cover dynamics, is required. A study was conducted in Wadla Delanta Massif to investigate land use/cover dynamics over the last four decades (1973-2014) using satellite images (1973 MSS, 1995 TM and 2014 ETM⁺). Global positioning system, topographical maps of 1:50,000 scale for ground verification, ArcGIS 10.2 software and ERDAS imagine 10.0 processing and analysis, supplemented with field work were used. Six land use/land cover (LU/LC) types i.e. forest, shrub, grazing, cultivated, bareland and riverbeds were identified. The results showed that there were remarkable spatiotemporal changes in LU/LC. Bareland and riverbeds increased from 17.2 to 32.30% and 1.68 to 2.61% respectively. Forest and shrub lands decreased drastically from 3.98 to 0.47% and 34.86 to 24.26% in 1973 and 2014, respectively. Agricultural and grazing lands also slightly decreased from 33.78 to 32.70% and 8.5 to 7.66% in 1973 and 2014, respectively. From 1973 to 2014, the forest, shrub, grazing and agricultural lands decreased by 90.3, 31.5, 10.08 and 3.36%, whereas the bare lands and riverbeds increased by 89.88 and 57.54%, respectively. The major contributing factors for such variations are population growth and associated needs, land tenure system, incompatible farming system, and lack of alternative energy sources. An integrated approach should be put in place in order to alleviate the current constraints and, improve agricultural productivity and food security in the study area.

Keywords: GIS, Image classification, Remote sensing, Supervised classification