Research Article | Open Access | 10.31586/RemoteSensing.0301.04

Monitoring of Land Use/Cover Change Using Remote Sensing and GIS techniques: A case study of Loliondo Game Controlled Area, Tanzania

  • Selassie David Mayunga Department of Geospatial Science and Technology, Ardhi University, P.O.Box 35176, Dar Es Salaam, Tanzania

Abstract

Loliondo Game Controlled Area (LGCA) is unique in East Africa that provides mixed land use activities for the community. The main land uses in LGCA are livestock keeping, wildlife conservation, small scale agriculture, tourism and hunting of wild animals. For decades, Maasai pastoralists coexisted with LGCA but restricted to hunt, set snares and conducting large scale farming. From the year 2000 expansion of agricultural activities have been noted which has escalated the decline of wildlife. I this study the land use/cover change occurred in LGCA for the period of 20 years have been determined and assessed. Supervised classification method was used whereby six classes namely forest, bare land, sand, water, grass land and agriculture were categorized. The results show that from 1996 to 2016 there is a major land cover change on forest, agriculture, bare land, grassland, water bodies and sand by 19.63%, 8.74%, 15.32%, 50.08%, 4.51 %and 1.72%, respectively. Specifically, forest cover is decreasing at 1467.81 ha per year while agriculture is increasing at the rate of 1,467 ha per year. The study concluded that clearing of forest and large scale agriculture has destroyed vegetation cover threatening the existence of wildlife which to a great extent requires immediate measures to counterbalance this effect.

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Published
July 26, 2018
How to Cite
DAVID MAYUNGA, Selassie. Monitoring of Land Use/Cover Change Using Remote Sensing and GIS techniques: A case study of Loliondo Game Controlled Area, Tanzania. Trends Journal of Sciences Research, [S.l.], v. 3, n. 1, p. 18-32, july 2018. ISSN 2377-8083. Available at: <http://tjsr.org/journal/index.php/tjsr/article/view/39>. Date accessed: 21 oct. 2018.
Section
Remote Sensing