The Lake Victoria Basin (LVB) is a significant resource for five states within East Africa, which faces major land use land cover changes that threaten ecosystem integrity and ecosystem services derived from the basin’s resources. To assess land use land cover changes between 1985 and 2014, and subsequently determine the trends and drivers of these changes, we used a series of Landsat images and field data obtained from the LVB. Landsat image pre-processing and band combinations were done in ENVI 5.1. A supervised classification was applied on 118 Landsat scenes using the maximum likelihood classifier in ENVI 5.1. The overall accuracy of classified images was computed for the 2014 images using 124 reference data points collected through stratified random sampling. Computations of area under various land cover classes were calculated between the 1985 and 2014 images. We also correlated the area from natural vegetation classes to farmlands and settlements (urban areas) to explore relationships between land use land cover conversions among these classes. Based on our land cover classifications, we obtained overall accuracy of 71% and a moderate Kappa statistic of 0.56. Our results indicate that the LVB has undergone drastic changes in land use land cover, mainly driven by human activities that led to the conversion of forests, woodlands, grasslands, and wetlands to either farmlands or settlements. We conclude that information from this work is useful not only for basin-scale assessments and monitoring of land cover changes but also for targeting, prioritizing, and monitoring of small scale, community led efforts to restore degraded and fragmented areas in the basin. Such efforts could mitigate the loss of ecosystem services previously derived from large contiguous land covers which are no longer tenable to restore. We recommend adoption of a basin scale, operational, Earth observation-based, land use change monitoring framework. Such a framework can facilitate rapid and frequent assessments of gains and losses in specific land cover classes and thus focus strategic interventions in areas experiencing major losses, through mitigation and compensatory approaches.

Land cover change in any ecosystem vary in space and time. The study analyzed spatial-temporal land cover change to predict forest degradation pressure points in Eastern Mau Forest Reserve. The study objectives were to determine types and amount of spatial-temporal land cover change; land cover change drivers and; forest resources use sustainability. The study used mixed sample survey design involving purposive sampling of spatial data and cluster sampling of forest resource use data. Primary data included ground control points, field validation data and forest resource use data. Secondary data included Landsat imagery, forest and administration boundaries and settlements data. Analysis was done for 1986-2014 period using Remote Sensing and Geographical Information System. The analysis techniques used included object based image segmentation and classification, accuracy assessment and land cover change detection. Land cover types in Eastern Mau Forest consisted of indigenous forest, shrubland, grassland, plantation forest, cultivated fields, bare ground and built-up area. The analysis results depicted that cultivated fields coverage increased from 1% to 47%. Indigenous and plantation forests decreased from 43% to 36% and 34% to 7% respectively. Grassland and shrubland decreased from 16% to 8% and 6% to 2% respectively. Bare ground and built up area had a change of less than 1% each. Causes of pressure that lead to forest degradation included crop cultivation, settlement construction, livestock grazing, charcoal burning, firewood collection, logging, bee keeping and medicinal herbs extraction. Land cover change was more on the eastern side than on the western side. Indigenous and plantation forests were likely to disappear if cropland and built up area expansions were to remain unchecked. The study recommendations were: resettlement activities be eliminated in the Eastern Mau Forest; excision of forest land for crop cultivation should be discouraged; and scientific research should be carried out on sustainable plantation forest activities.