Published November 2017
| Version v1
Journal article
The power of Random Forest for the identification and quantification of technogenic substrates in urban soils on the basis of DRIFT spectra
- 1. Department of General Geography/Human-Environment Research, Institute of Geography, University of Wuppertal, 42119 Wuppertal (Germany)
- 2. Department of Soil Science/Soil Ecology, Institute of Geography, Ruhr-University Bochum, 44780 Bochum (Germany)
Description
Highlights: • Spectroscopy and data mining were combined to a novel approach in soil pollution. • Random Forest algorithm was able to identify and quantify pollutants in urban soils. • A powerful classification system to identify environmental pollution is proposed.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.envpol.2017.06.086Additional details
Identifiers
- DOI
- 10.1016/j.envpol.2017.06.086;
- PII
- S0269-7491(17)30159-8;
Publishing Information
- Journal Title
- Environmental Pollution (1987)
- Journal Volume
- 230
- Journal Page Range
- p. 574-583
- ISSN
- 0269-7491
- CODEN
- ENPOEK
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 49048303
- Subject category
- S54: ENVIRONMENTAL SCIENCES;
- Descriptors DEI
- AIR POLLUTION; ALGORITHMS; CLASSIFICATION; FORESTS; MINING; PETROLEUM; POLLUTANTS; RANDOMNESS; SOILS; SPECTROSCOPY; SUBSTRATES
- Descriptors DEC
- ENERGY SOURCES; FOSSIL FUELS; FUELS; MATHEMATICAL LOGIC; POLLUTION
Optional Information
- Copyright
- Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.