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https://doi.org/10.1186/s40249-017-0385-0

has been cited by the following article:

• TITLE: Subtle Impacts of Temperature and Rainfall Patterns on Land Cover Change Overtime and Future Projections in the Mara River Basin, Kenya

  AUTHORS: Fredrick M. Mngube, Raphael Kapiyo, Paul Aboum, Douglas Anyona, Gabriel O. Dida

  KEYWORDS: Land Cover, Change Detection, Temperature, Rainfall, Sub-Catchments, Mara River, Kenya

  JOURNAL NAME: Open Journal of Soil Science, Vol.10 No.9, September 10, 2020

  ABSTRACT: The interactive and cumulative effect of temperature and rainfall on land cover change is a priority at global, regional and local scale. This study examined changes in six land cover categories (forestland, grasslands, shrub land, bare land, built-up areas and agricultural lands) in four sub-catchments (Amala, Nyangores, Talek and Sand River), of the Mara River basin over a 30-year period (1987-2017) and made predictions of future land cover change patterns. Landsat Imageries of 90 m resolution were retrieved and analyzed using ArcGIS 10.0 software. Relationship between NDVI, temperature and precipitation was determined using Pearson’s correlation coefficient, while Markov chains analyses were performed on different land cover categories to project future trends. Results showed low to moderate (R2 = 0.002 to 0.6) trends of change in NDVI of different land cover categories across all sub-catchments. The greatest change (R2 0.34 to 0.5) was recorded in bare land in three of the four sub-catchments studied. Precipitation showed a strong positive correlation with built-up areas, forestlands, croplands, bare land, grasslands and shrub lands, while temperature correlated strongly but negatively with the same land cover categories. The change detection matrix projected significant but varying changes in land cover categories across the four sub-catchments by 2027. This study underscores the impact of changing climatic factors on various land cover categories in the Mara River basin sub-catchments, with different land cover categories exhibiting strong positive sensitivity to high precipitation and low temperature and vice-versa.