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Detecting forest cover and ecosystem service change using integrated approach of remotely sensed derived indices in the central districts of Uganda


A.A. Ssentongo
D Darkey
J Mutyaba

Abstract

Natural forests in Uganda have experienced both spatial and temporal modifications from different drivers which need to be monitored to assess the impacts of such changes on ecosystems and prevent related risks of reduction in ecosystem service benefits. Ground investigations may be complex because of dual ownership, whereas remote sensing techniques and GIS application enable a fast multi-temporal detection of changes in forest cover and offer a cost-effective option for inaccessible areas and their use to detect ecosystem service change. The overarching goal of this study was to use satellite measurements to study forest change and link it to ecosystem service benefit reduction (fresh water) in the study area using a representative sample of Landsat scenes, also testing whether the inclusion of ecosystem service benefits improves the classification. In this paper, an integrated approach of remotely derived indices was used together with post-classification comparison to detect forest cover and ecosystem service changes. Our contribution novelty is the ability to detect at multi-temporal scale private and central reserve forest cover decline along with ecosystem benefit reduction using remotely derived indices in the 20 year period (1986-2005). Change detection analysis showed that forest cover declined significantly in five sub-counties of Mpigi, than in Butambala by 5.99%, disturbed forest was 3%, farm land increased by 44%, grassland declined by 62.5% and light vegetation increased by63.6%. The two most affected areas also experienced fresh water reductions. For sustainable supply of ecosystem service benefits, resource managers must also involve private resource owners in the conservation effort.

Keywords: Change detection, forest cover, ecosystem service, remotely sensed derived indices, central districts of Uganda


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eISSN: 2225-8531