Theses

RATE OF LAND USE LAND COVER CHANGES AND ITS DRIVING FORCES IN SETEMA DISTRICT JIMMA ZONE, ETHIOPIA

Abstract

LULCC is the result of the long-time process of natural and anthropogenic activities that have been practiced on the land. The study intended to carry out the rate of land use /land cover changes, trends, and their magnitude over the last 30 years (1988-2018), its driving forces, and simulation for the coming ten years (2028) using remote sensing and GIS.

The study has initiated due to, loss of biodiversity (used for food, fuelwood, construction medicine, etc.) and wetland expansion to agricultural land. The General objective of this study was concentrated on the rate of land use land cover changes and its driving forces of Setema district Southwest Ethiopia. The study area was classified into seven LULCC categories on the basis of field study, geographical conditions, and remote sensing data. For the identification of land use/ land cover change land sat imagery of 1988, 1998, 2008, and 2018 were used to determine the change in land use/land cover using Semi-automatic classification plug-in. In establishing the main drivers of land use/land cover change, the study utilized household survey, Key informant interview, and focus group discussion. A total of 384 respondents were selected from the four kebeles by stratification and purposely based on the criteria of  Coffee grower kebeles, cereal crop grower kebeles, kebeles change wetland to agricultural land illegally,  the most kebeles proximity to forest land by more discussion with kebele administrator “cabinets” and DAs. From the kebele’s Masimano, Kimiso, and Done and Setema Kecha were selected which satisfies the criteria. The study has used QGIS software 2.18.3, SCP plug-in extension version 5.4.2, and MOULUSCE plug-in extension version.3 for image detection, classification, and Simulation whereas for social survey interpretation Mini Minitab software version 19.1. and Microsoft Excel 2010 was used. The LULCC classification result revealed that at the base period of  1988 Land sat imagery,  forest land (56.22%), grassland (15.7%), Agricultural land(23.13%), Bare land(0.03%), wetland (2.18), and Settlement land(1.58%) were identified with their respective percentage.  On the contrary in the recent period of  2018 land sat imagery forest land, grassland, wetland were decreased to  (39.71%), (6.53%), (0.87%),(23.13%) respectively. The result analysis of households survey, Focus group discussion, and key informant interview was used and identified the major proximate drivers and underlying drivers such as fuelwood extraction, illegal wetland conversion to agricultural land, and illegal timber production, and agricultural expansion, extraction of wood for house construction population growth and corruption.  The maps of 1998 and 2008 were used to simulate the LULC for 2018 using MOLUSCE available in QGIS software. The predicted result was compared with the classified LULC map of 2018 to validate the model. Finally, based on this, the prediction of future LULC for the years 2028 was performed. The outcomes of this study show that there would be decreasing in forestland; grassland and increasing in agricultural land and settlement area. Lastly, further study is required to identify the role of wetlands for LULCC.

Keywords: Cellular Automata, Geographical Information system, Land use land cover change Modules for Land Use Change Evaluation, Quantum Geographical Information system, Semi-automatic Classification Plug-in.

 

 

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National Measuring, Reporting and Verification Capacity Building Towards Climate Resilient Development in Ethiopia.

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