Land Suitability Assessment For Effective Crop Production, a Case Study of Taita Hills, Kenya | Land Portal | Securing Land Rights Through Open Data

Resource information

Date of publication: 
April 2015
Resource Language: 
ISBN / Resource ID: 
(ISSN 2061-862X
Pages: 
9

Agriculture is the backbone of Kenya’s economy. Agriculture in Kenya is characterized by low productivity due to low external inputs, lack of good farming practices, soil erosion, and other losses. In most farming regions of the country, agriculture depends entirely on rainfall which sometimes is scarce. The problem of selecting the correct land for the cultivation of certain crops is a long-standing and mainly empirical issue. The objective of this study is to extrapolate and generate a crop suitability map showing areas suitable for agricultural activities in Taita Hills in Kenya. It utilizes the information on environmental condition, altitude, rainfall and other relevant parameters of the case study where the variability of rainfall and recurrent droughts have a great impact on the lives of people whose livelihood is mainly dependent on subsistence agriculture. The methods used include development of elevation models, watershed mapping, climate variability mapping, soil erosion mapping that incorporates the revised universal soil loss empirical (RUSSLE) model and multi-criteria evaluation analysis. The analysis was done using the sum weighted overlay analysis of soil erodibility, slopes, vegetation index and rainfall availability in the modeling. Four categories were achieved and mapped out: most suitable, more suitable, less suitable and least suitable. The research implies that there can be both suitable areas and unsuitable areas for crops in Taita Hills. The study helps farmers to be aware of the environmental conditions of their agricultural land and the impacts that may arise due to varying climate conditions on their cropping patterns.

Authors and Publishers

Author(s), editor(s), contributor(s): 
Mark K. Boitt, Charles N. Mundia, Petri K. E. Pellikka, John K. Kapoi.

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