This study aims at utilizing legacy soil data for digital soil mapping and data delivery. The legacy soil data used in this study is the Reconnaissance Soil Survey of the Busia area (quarter sheet No. 101) (Rachilo and Michieka, 1991). The overall objective of this study is to bring legacy soil data ‘back to life’ using digital soil mapping techniques. The specific objectives include to (i) transform the best available legacy soil survey report of a selected potion of Kenya into a digital format, (ii) make spatial predictions of selected soil properties using data mined from the legacy soil survey using digital soil mapping techniques, (ii) improve the spatial resolution of the legacy soil map of the study area using digital soil mapping, and (iv) develop a prototype platform that could deliver spatially explicit soils and agricultural information of the study area on a smart phone or mobile tablet.
Rachilo, J.R., & Michieka, D.O. (1991). Reconnaissance Soil Survey of the Busia area (quarter degree sheet No. 101). Kenya Soil Survey, pp. 269.
This is a publication series that contains (i) soil property data and environmental covariates of digital soil mapping, (ii) environmental covariates for disaggregating the Busia soil polygon map, (iii) K-means cluster map, (iv) predictive components for stepwise multiple linear regression, (v) crop suitability maps, (vi) land quality maps, (vii) fuzzy soil class map, and (viii) the disaggregated soil class map of the Busia area.
Independent diagnostic criteria reflecting limitations for land use.
These are suitability classes defining the requirements for various crops/ land use types.
Soil property data mined from the Reconnaissance Soil Survey of the Busia Area (quarter degree sheet No. 101) for digital soil mapping.
Environmental covariates were carefully selected to represent factors of soil formation: climate, relief, organisms, and time.
Map that mimics the geometry of 'fully developed slopes'.
Independent predictor variables for stepwise multiple linear regression.
Enviromental covariate data used to develop a digital model that represents the landscape and environmental conditions of the Busia landscape.
Map based on the concept that soil classes can be spatially inferred from soil-related environmental conditions.
This is a disaggregated soil map of the Busia area.
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