IOSR Journal of Environmental Science, Toxicology and Food Technology (IOSR-JESTFT) e-ISSN: 2319-2402,p- ISSN: 2319-2399.Volume 13, Issue 10 Ser. I (October. 2019), PP 37-51 www.iosrjournals.org DOI: 10.9790/2402-1310013751 www.iosrjournals.org 37 | Page Spatio-temporal assessment of rainfall influence on vegetation in the arid and semi-arid lands of Kenya Charles K.Kigen 1* , Stanley M. Makindi 2 , Francis. N. Muyekho 3 and Edward. N. Masibayi 4 1 Department of Natural Resources,Moi University, Kenya 2 Department of Environmental ScienceMachakos University, Kenya 3 School of Agriculture and Veterinary Science and Technology, MasindeMuliro University of Science and Technology, Kenya 4 Department of Disaster Preparedness and Engineering ManagementMasindeMuliro University of Science and Technology, Kenya Corresponding Author; Charles K.Kigen Abstract: Climate controls the types, health and spatial distribution of vegetation. The rainfall patterns and vegetation distribution have a very high correlation especially within the tropics. The higher and the more evenly distributed the rainfall is, the more the vegetation cover. However, in the arid and semi-arid lands, the rainfall is seasonal and has very high variability thereby affecting the availability of pasture for both livestock and wildlife, critical economic activities.The research was accomplished byspatio-temporaltrend analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data of fifteen years (2001-2015). The spatial data was sourced from USGS, ILRI, and United Nations Africover Project. The data processing and analysis was done usingArcGIS, Map Comparison Kit and Geodasoftwares.The research found out that:The monthly rainfall trend ranged from -15 – 20mm while the annual trend indicated a reduction of -6 – 0mm in the entire country which shifted spatially in some months and years; the monthly MODIS NDVI trend was between-0.065 - 0.060 and also depicted spatial shift in some months; the dependence of MODIS NDVI on rainfall was significant with annual coefficients of determination of 0.541 in 2002 and 0.763 in 2006 and the fifteen years mean at 0.617; and MODIS NDVI did not show evidence of spatial shift. The research concluded that therainfall rangeland vegetation (grass) temporal distribution has changed both with time, seasons and spatially. Keywords: Rangeland,grass, climate change, spatial, temporal, arid and semi-arid lands --------------------------------------------------------------------------------------------------------------------------------------- Date of Submission: 21-09-2019 Date of acceptance: 10-10-2019 --------------------------------------------------------------------------------------------------------------------------------------- I. Introduction Climate change is real and has varied local, regional and global impacts [1]. The relation between climate and rangeland vegetation as concluded by [2] are normally highly correlated. The rangeland ecosystems have enormous ecological and economic benefits. Ecologically, it is home to many animals and plants species which are utilized by man in various ways. The pasture is used for livestock grazing while the wildlife forms the major tourism attractions in the country [3].The rangelands according to [4]are defined aslarge open areas containing plants mainly grass and shrubs used for grazing. The rangeland vegetation depends entirely on climate which has been documented to change by various researchers [5]; [1]. Scientists have unearthed evidenced that the earth has warmed up by an average of about 0.6 o C since the late 19 th centuryand is projected that the temperature will increase by 1.4 o C – 5.8 o C by the year 2100 at a global scale[5]. Temperature anomalies in Kenya are reported to be 0.4 – 1.6 O C with climate change related deaths of 70 – 120 per million population[6]. The repercussions of these climate anomalies among others include changes in land use land cover in both time and space [7] and the entire ecosystems. This will disrupt the economic activities directing depending on rangeland vegetation. [8] findings indicate that developing countries such as Kenya will be hit most due to various reasons includingthe fact that Kenya’s economy is largely dependent on agriculture and tourism. A large part of Kenya about 80% is classified as arid and semi-arid lands (ASALs) and is prone to drought and floods. Many livestock keeping communities, ranches, and game reserves are located in these regions of Kenya.Also, the country’s population is growing and people are migrating to these fragile ecosystems increasing pressure on the limited vegetation resources [9]. This paper consequently seeksto establish both the temporal and spatial nature of climate based rangeland vegetation change in the ASALs of Kenya to aid decision making.