Assessment of Land Use Land Cover Dynamics and Soil Erosion Susceptible Modeling in Amhara Regional State: Case Study at Dessie Zuria Woreda Using Remote Sensing and Gis
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Date
2009-06
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Addis Ababa Universty
Abstract
Spatial data processing especially using GIS techniques has been playing an
important role in different applications. Multiple source spatial and non-spatial data
can be processed and integrated for the analysis of spatio-temporal dimension of a
given area. In this study, land use/cover dynamics that occurred from 1973 to 2000 &
potential area to soil erosion have been identified. The main objective of the study is to
assess land use land cover dynamics for the last 27 years and to identify soil erosion
susceptible area. To this end, remotely sensed data i.e. Landsat satellite images of
1973 MSS, 1986TM and 2000ETM+ have been used to produce land use land cover
classes and to see the dynamics using Geographical Information System (GIS).The
results in this research for the last 27 years are the following. From 1973 to 1986
agriculture and bare lands have been increased with 7348.8 ha and 3998.9 ha,
respectively. The main factor of this is population growth in the area. While forest,
bush and grass lands have been diminished by 2152.7, 2381.7, and 6386.5ha,
respectively. From 1986 to 2000, only agricultural lands have been expanded by
2282.8 ha, while bare, forest, bush and grass lands have been decreased with 272.3,
4.1, 241.7 and 1765.2 ha, respectively. The dynamics have been detected and
supported with NDVI statistics. It indicates that there has been increasing forest
degradation in the Study area. Agricultural lands have been analyzed with slope and
soil erosion susceptible areas. In both cases, such land class has been expanded.
This is the best indicator of the scarcity of agricultural land in the area. As a result
people have been forced to use marginal land. This is also the main factor to increase
bare/degraded land. To sum up the conclusion; land use/cover dynamics have been
detected and analyzed with the input data of landsat image using GIS to understand
the trend in short period of time, least cost and in effective manner. However, for
sound decision making process, other data such as socio-economic should be used
and integrated in GIS.
Key words: Land use/ cover Dynamics, Land Degradation (forest degradation),soil erosion Modeling, Remote Sensing and GIS
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Keywords
Land use/ cover Dynamics, Land Degradation (forest degradation), Soil erosion Modeling, Remote Sensing and GIS