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Assessing Land Use/Cover dynamics of the Ngorongoro world heritage site in Tanzania using a hybrid CA–Markov model

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dc.contributor.author Mwabumba, Mohamed
dc.contributor.author Yadav, BK
dc.contributor.author Rwiza, Mwemezi J.
dc.contributor.author Twisa, Sekela
dc.contributor.author Larbi, Isaac
dc.date.accessioned 2021-02-08T13:06:50Z
dc.date.available 2021-02-08T13:06:50Z
dc.date.issued 2020-10
dc.identifier.uri https://dspace.nm-aist.ac.tz/handle/20.500.12479/1091
dc.description This research article published by Authorea, 2021 en_US
dc.description.abstract In this study, land-use/cover pattern of the UNESCO world heritage site, Ngorongoro Conservation Area; is analyzed using the CA–Markov model with the help of RS and GIS. Hybrid classification techniques ware used to monitor land use/cover changes, using Landsat images for 1995, 2005 and 2016. The CA-Markov model is then used to predict the land use /cover maps for 2025 and 2035. The highest net gain from 1995-2016 observed in cultivated land (6.55%), grassland (2.68%), bare land (1.82%), bushland (0.48%) and built-up area (0.01%), and the net loss found in woodland (8.38%), forest (1.52%), wetland (1.41%), and water cover area (0.24%). However, reduction is expected in bushland (4.88%), forest (0.82%), water (0.77%) and woodland (0.07%) during 2025-2035 with increase in cultivated land (2.73%), grassland (1.19%), bare land (1.79%) and built-up area (0.14%). As per the current trend in land use management, forest cover is significantly declining; leading to the loss in the ecological values of the Ngorongoro Conservation Area and its surroundings. The results of this study can be used directly by the policymakers to plan appropriate conservation schemes to endorse improved land use management practices for ecological protection of the heritage site. en_US
dc.language.iso en en_US
dc.publisher Authorea en_US
dc.subject Research Subject Categories::NATURAL SCIENCES en_US
dc.title Assessing Land Use/Cover dynamics of the Ngorongoro world heritage site in Tanzania using a hybrid CA–Markov model en_US
dc.type Article en_US


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