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Title: Spatio-Temporal RS. Analysis and Predicting Land use/Land cover Change using CA-Markov Simulation Model: A case study of Gitega District, Burundi
Audace Ntakirutimana
Chaiwiwat Vansarochana
ชัยวิวัฒน์ วงศาโรจน์
Naresuan University. Faculty of Agriculture,Natural Resources and Environment
Keywords: Change Analysis
Kappa statistics
Markov Chain
Land Change Modeler
Prediction process
Issue Date: 2020
Publisher: Naresuan University
Abstract: Spatial and temporal analysis of Land use and Land cover Change (LULC) is a widely used and effective method for monitoring environmental issues caused by humans at both local and global scales.  Land use and land cover change play an important role in ensuring human well-being, particularly throughout regional socioeconomic development, and thus LULC is an important aspect of global environmental dynamics. The rapid increase in human population and associated livelihoods frequently causes problems for the biophysical environment and ecosystems, such as the loss of natural areas, particularly forests and natural vegetation due to urban development and agricultural expansion. The purpose of this study was to monitor land use and land cover change in the Gitega District, and also to simulate a future scenario in order to generate a long-term land use dataset using Geoinformatics.  The first step was to use multi-temporal Landsat imagery from 1984, 2002, and 2019 to generate existing LULC maps using a combination of RS and GIS approaches. The supervised classification method was used to derive five major LULC classes, and the accuracy assessment resulted in an overall accuracy of more than 85 percent for all three years, with respective Kappa statistics of 83 percent and 91 percent. Net Change detection results showed that Agriculture had the greatest extension with an area of 94 km2 and an annual rate of 2.9 km2, a slight increase in Shrub Land by 5,5 km2 and Built-up Area by 2 km2, and a steep decline in Tree Cover of 62.5 km2 with a rate of 1.79 km2 per year, and Grass Land decreased 39 km2 with a rate of 1.12 km2 over the past 35 years. C-A Markov model was further calibrated to predict 2038 and 2057 LULC using the transition probability matrices between the existing and simulated LULC map of 2019. Evaluation and analysis of 2019, 2038 and 2057 simulation results showed an overall moderate agreement of 75 percent for Kappa statistics and the same trends of LULC change: Trees Cover, Grass Land, and Shrub Land are likely to decrease by 11.5 km2, 13 km2, 11.5 km2 respectively, whereas Agriculture and Built-up Area will increase by 30 km2 and 6 km2 respectively in 2057. Overall, major LULC dynamics occurred by conversion large agriculture and possibly thereby, high degradation with soil erosion, loss and soil depletion are some Gitega District. These research findings may assist decision-makers in gaining a thorough understanding of land use and land cover change patterns in order to devise the best strategies for land sustainable land use management, thereby avoiding future irreversible land degradation and environmental problems that may be difficult and costly to address over time.
Description: Master of Science (M.S.)
วิทยาศาสตรมหาบัณฑิต (วท.ม.)
Appears in Collections:คณะเกษตรศาสตร์ ทรัพยากรธรรมชาติและสิ่งแวดล้อม

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