Abstract
To investigate land use land cover changes (LULCC) in the Kieni sub-county in Central Kenya from 1987 to 2017, remote sensing and Geographical Information System (GIS) was used. This was done by downloading and processing landsat images of 1987, 1995, 2000, 2010 and 2017. Methods employed were, data identification and acquisition, image processing, validation and presentation. There were six classifications analysed which were; bare areas, bushlands, farmlands, forest, grasslands and waterbodies. The results showed an increase in the classes of water bodies, farmlands and bare areas by 314.86%, 160.45% and 73.18% respectively over the 30-year period. The results also showed a decrease in the land use land cover classes categories of forest, bushlands and grassland by 45.94%, 38.73% and 29.66% respectively. Therefore, in conclusion, there were land use and land cover changes in the study area over the 30-year period between 1987 and 2017 as illustrated by results that showed that farmlands classification increased by more than one and half times while forest cover was reduced by about a half.
Highlights
Land cover refers to the physical and biological cover over the land surface, including; vegetation, bare soil, water and artificial structures
All the Landsat images for 1987 to 2017 a 30-year period were processed and the particular years analysed for land use and land cover changes were 1987, 1995, 2002, 2010 and 2017.The study area land cover was classified into six classifications namely; Bare-lands, bushlands, farmlands, forest, grassland and water bodies as illustrated in Figure 2 below
The land cover for bare lands increased from 13.2% in 1987 to 22.56% in 2017 while that for bushland decreased from 24.5% in 1987 to 15.01% in 2017
Summary
Land cover refers to the physical and biological cover over the land surface, including; vegetation, bare soil, water and artificial structures. It is well established that land cover change has significant effects on basic processes including biogeochemical cycling and thereby on global warming, the erosion of soils and thereby on sustainable land use and for the 100 years is likely to be the most significant variable impacting on biodiversity [3]. Land-use and land-cover changes (LUCC) increasingly have been regarded as a primary source of global environmental change such as emission of greenhouse gases, global climate change, loss of biodiversity, and loss of soil resources [4,5,6]. Updated land use land cover information is essential to many socio-economic and environmental applications, including urban and regional planning, natural resources conservation and management among others. Land ‐ cover binary change detection methods for use in the moist tropical region of the Amazon: a comparative study.
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