Western Kenya soil geochemistry
Soil prediction maps for 56 chemical elements, pH and organic matter content have been produced using machine learning analysis in western Kenya. The predictive maps were based on 452 soil samples collected across western Kenya during field surveys carried out between 2015 and 2020. Samples were analysed by the inorganic chemistry laboratories at the British Geological Survey. The maps, created using random forest machine learning algorithms, are displayed as raster files with a spatial resolution of 500m. The samples were collected as part of a geochemistry and health project to investigate the spatial incidences of diseases in the Rift Valley (e.g. oesophageal cancer, iodine/zinc deficiency), which included a range of data and sample collections to inform sources of micronutrients or exposure to potentially harmful elements, with outputs to inform agriculture and public health practitioners. These predictive maps provide a baseline geochemistry survey for the agri-community, academics and public health officials.
dataset
https://webapps.bgs.ac.uk/services/ngdc/accessions/index.html#item169711
name: Data
function: download
https://doi.org/10.5285/bd1f80ef-114a-429d-a629-20d19bacec79
name: Digital Object Identifier (DOI)
function: information
http://data.bgs.ac.uk/id/dataHolding/13607850
eng
geoscientificInformation
publication
2008-06-01
Soil maps
Geochemistry
Soils
revision
2011
NERC_DDC
33.9300
35.8300
1.0900
-1.0000
revision
2009
KE
revision
2009
KEN
creation
1979
KENYA [id=687000]
2015-01-01
2020-03-31
creation
2021-08
asNeeded
The soil samples were collected and analysed by the Inorganic Chemistry Facility, University of Eldoret and Moi University during ODA-I (2015-2020) as part of a geochemistry and health project to investigate the spatial incidences of diseases in the Rift Valley. Following the compilation of the soil data BGS undertook random forest machine learning analysis in conjunction with additional open-access environmental covariate datasets to create the geochemical prediction maps.
publication
2011
false
See the referenced specification
publication
2010-12-08
false
See http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:323:0011:0102:EN:PDF
.TIF
The copyright of materials derived from the British Geological Survey's work is vested in the Natural Environment Research Council [NERC]. No part of this work may be reproduced or transmitted in any form or by any means, or stored in a retrieval system of any nature, without the prior permission of the copyright holder, via the BGS Intellectual Property Rights Manager. Use by customers of information provided by the BGS, is at the customer's own risk. In view of the disparate sources of information at BGS's disposal, including such material donated to BGS, that BGS accepts in good faith as being accurate, the Natural Environment Research Council (NERC) gives no warranty, expressed or implied, as to the quality or accuracy of the information supplied, or to the information's suitability for any use. NERC/BGS accepts no liability whatever in respect of loss, damage, injury or other occurence however caused.
University of Eldoret
originator
Moi University
originator
British Geological Survey
Environmental Science Centre, Nicker Hill, Keyworth
NOTTINGHAM
NG12 5GG
United Kingdom
0115 936 3143
0115 936 3276
distributor
British Geological Survey
Environmental Science Centre, Nicker Hill, Keyworth
NOTTINGHAM
NG12 5GG
United Kingdom
0115 936 3143
0115 936 3276
originator
British Geological Survey
Environmental Science Centre, Nicker Hill, Keyworth
NOTTINGHAM
NG12 5GG
United Kingdom
0115 936 3143
0115 936 3276
pointOfContact
British Geological Survey
Environmental Science Centre, Keyworth
NOTTINGHAM
NG12 5GG
United Kingdom
+44 115 936 3100
pointOfContact
2023-01-23