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Summary of Proposal LAN2759

TitlePrediction of maize crop yield using terrasar-x data. A case study of Trans Nzoia county, Kenya
Investigator kuria, bartholomew thiongo - Dedan Kimathi University of Technology, Institute of Geomatics, GIS and Remote Sensing
Team Member
Mr Kuria, Bartholomew Thiongo - University of Bonn , Geography
Prof Menz, Gunter - University of Bonn, Geography
Dr Thonfeld, Frank - University of Bonn, Geography
Dr Kuria, David - Dedan Kimathi University of Technology, Geomatic Engineering and Geospatial Information Science
SummaryWith agriculture remaining as one of the key aspects of a strong society, the ever decreasing crop yields, attributed to climate change, urbanization and the accompanying human practices, have been quite of a concern. In its 2012 Economic Survey Report, the Kenya National Bureau of Statistics estimated that there was a decrease in maize production by nearly over one million bags and an increase in the maize import by about 56.5 percent. There is therefore the need to emphasize and optimize reliable agricultural production. The main objective of this research is to predict the Maize crop yield in Trans Nzoia County, by using TerraSAR-X images VV and VH. Images shall be acquired for the months of May,June, July, August and September to cover the various phenological growth stages of the maize crops from germination to maturity, just before harvest.The backscatter values of the crop shall then be extracted from the images and processed. The information received from the radar images shall be complemented by ground information collected from the identified large scale maize farmers in the area. An optical sensor, preferably RapidEye shall also be used. These backscatter values shall then be compared with the primary ground truth data and yield values collected from the respective farmers by means of questionnaires. A model relating the recorded backscatter values to thecorresponding yield and the yield influencing factors shall then be developed.

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