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Article citations


Al-sharif, A. and Pradhan, B. (2013) Monitoring and Predicting Land Use Change in Tripoli Metropolitan City Using an Integrated Markov Chain and Cellular Automata Models in GIS.

has been cited by the following article:

  • TITLE: Land Use Land Cover Change Detection and Deforestation Modeling: In Delomena District of Bale Zone, Ethiopia

    AUTHORS: Girma Ayele, Hussein Hayicho, Mersha Alemu

    KEYWORDS: Deforestation, LULC, Modeling, Transitions, Land Change Modular

    JOURNAL NAME: Journal of Environmental Protection, Vol.10 No.4, April 11, 2019

    ABSTRACT: Previous studies in Delo-Mena district failed to provide conceptual framework about causes and impacts of deforestation including prediction of spatial location of future deforestation. The study was aimed at investigating spatiotemporal dynamics and prediction of future trends of deforestation in this area. Three periods Landsat images were downloaded and preprocessed using ENVI 4.3. Supervised classification technique was employed for image classification. Land Change Modular used to predict deforestation based on transition between 2000 and 2015 along three driving variables (road distance, settlement and soil). Six land-use land-cover classes were classified for three periods. The result indicated that the forest areas were 91,339, 73,274 and 70,481 hectors in year 2000, 2010 and 2015, respectively. This forest area was reduced by 20% between 2000 and 2010 at annual rate of 2%. Between 2010 and 2015, a forest area was lost by 4% with annual rate of 1%. This deforestation rate was greater than global rates and was lower than rates of south eastern African countries. Farmland expansion was a major cause of deforestation contributed to the annual forest loss by 4.9% and 36% over different periods. In 2030, about 33,243 hectors of a forest area would be expected to disappear that implied emission of about 17 million ton of carbon dioxide. Fuelwoods shortage and loss of biodiversity were perceived as impacts of deforestation. Farm-land and settlement were found increasing at expense of vegetation. Forest plantation, supply of fuel efficient technology and community mobilization were recommended that would be emphasized by the forestry sector based at the district office.