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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.

Default

Identification info

Metadata Language
English (en)
Dataset Reference Date ()
2021-08
Identifier

http://data.bgs.ac.uk/id/dataHolding/13607850

 

University of Eldoret

-

Odipo Osano


 

Moi University

-

Diana Menya


 

British Geological Survey

-

Enquiries


Environmental Science Centre, Nicker Hill, Keyworth

,

NOTTINGHAM

,

NOTTINGHAMSHIRE

,

NG12 5GG

,

United Kingdom

0115 936 3143
0115 936 3276
 

British Geological Survey

-

Enquiries


Environmental Science Centre, Nicker Hill, Keyworth

,

NOTTINGHAM

,

NOTTINGHAMSHIRE

,

NG12 5GG

,

United Kingdom

0115 936 3143
0115 936 3276
 

British Geological Survey

-

Enquiries


Environmental Science Centre, Nicker Hill, Keyworth

,

NOTTINGHAM

,

NOTTINGHAMSHIRE

,

NG12 5GG

,

United Kingdom

0115 936 3143
0115 936 3276
Maintenance and update frequency
asNeeded
GEMET - INSPIRE themes
  • Geology
BGS Thesaurus of Geosciences
  • Soil maps

  • Geochemistry

  • Soils

Keywords
  • NERC_DDC

Limitations on Public Access
otherRestrictions
Other constraints
licenceOGL
Other constraints
Available under the Open Government Licence subject to the following acknowledgement accompanying the reproduced NERC materials "Contains NERC materials ©NERC [year]"
Use constraints
otherRestrictions
Other constraints

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.

Other constraints

There are no restrictions on the use that may be made of the dataset, although an appropriate copyright acknowledgement must be made when any part of the dataset is reproduced. Either no third party data / information is contained in the dataset or BGS has secured written permission from the owner of any third party data / information contained in the dataset to make the dataset freely available without any use constraints - inclusion of any third party data / information will affect the copyright acknowledgement that needs to be made.

Spatial representation type
grid
Topic category
  • Geoscientific information
Extent

KE

Dataset Reference Date ()
2009

Extent

KEN

Dataset Reference Date ()
2009

Extent

KENYA [id=687000]

Dataset Reference Date ()
1979

N
S
E
W


Begin date
2015-01-01
End date
2020-03-31
 

Spatial Reference System

No information provided.

Distribution Information

Data format
  • .TIF

    ()

Resource Locator
Data
Resource Locator
Digital Object Identifier (DOI)
Resource Locator
Data
Resource Locator
Digital Object Identifier (DOI)
 
Quality Scope
dataset
Other

dataset

Report

Dataset Reference Date ()
2011
Explanation

See the referenced specification

Degree

Report

Dataset Reference Date ()
2010-12-08
Explanation

See http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:323:0011:0102:EN:PDF

Degree
Statement

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.

Metadata

File identifier
d171c124-58cf-6e47-e054-002128a47908 XML
Metadata Language
English (en)
Resource type
dataset
Metadata Date
2023-03-31
Metadata standard name
UK GEMINI
Metadata standard version

2.3

 

British Geological Survey


Environmental Science Centre, Keyworth

,

NOTTINGHAM

,

NOTTINGHAMSHIRE

,

NG12 5GG

,

United Kingdom

+44 115 936 3100
 
 

Overviews

N
S
E
W



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