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A Spatial Analysis of Determinants of Deforestation in the Mt. Kenya Region, Kenya: 1976-2000

Keshav Bhattarai, Henry Wambuii, Fridolin Luchidio

Abstract


This paper identifies the spatial driving forces (SDFs) of deforestation in the Mt. Kenya region in Kenya from 1976 until 2000 using MSS (1976) TM (1986) and ETM+ (2000) images along with socio-demographic-and-economic variables covering 31,236 square kilometers of a 154 of the smallest administrative locations in eight administrative districts. Radiometrically calibrated satellite images are individually classified, and assessed. A 90 m SRTM DEM is re-sampled to 60 m and to 30 m resolution to match the pixel sizes of satellite images. The whole region ranging from 325 m to 4935 m is divided into eight elevation classes. Vector layers of 154 administrative locations are overlaid on the classified images to calculate areas for ten land use and cover classes for 1976, 1986, and 2000 for eight elevation levels. Two transition matrices are generated from three classified images. These transition matrices help to visualize actual locations of deforestation as well as factors contributing to deforestation. Socioeconomic data is incorporated with geographic information systems (GIS) and integrated into the elevation and land use and cover data for statistical analyses. Six regression models are estimated using SPSS to identify influences of SDF on deforestation at each elevation zone. These regression analyses reveal that deforestation in the Mt. Kenya region is related to multiple factors, such as types of roads, rivers, and population. Further, historical and policy analyses reveal that deforestation is also attributable to Kenya’s colonial legacy. Additional factors include illegal logging, replacement of indigenous vegetation with fast growing exotic tree species, charcoal burning, and the cultivation of cash crops. Despite participatory approaches in the 1990s in recognition of the site specific dynamic relationship between people and the ecosystems, vacillating forest policy and increasing population pressures have led to varying rates of deforestation at different elevations.

Keywords


Kenya, Forest, Remote Sensing, Mt. Kenya, MSS, TM, ETM+, District, DEM

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