Conference paper
Mapping salinity using decision trees and conditional probabilistic networks
2nd IEEE International Conference on Intelligent Processing Systems (IEEE ICIPS'98) (Gold Coast, QLD, 04/08/1998–07/08/1998)
1998
Abstract
This paper examines the use of different classifiers for integrating multi-temporal remotely sensed data with landform data derived from digital elevation models to produce maps showing areas affected by salinity in the south west agricultural region of Western Australia. Decision trees are used to map saline areas in the Ryan's Brook catchment, located approximately 50 kilometres southwest of Kojonup, WA. The results are compared with maximum likelihood classification techniques using single-date Landsat TM imagery. The non-parametric decision tree classifiers combine multi-temporal Landsat TM data with landform data derived from digital elevation models to produce more accurate salinity maps. However, the maps exhibited large amounts of noise and showed errors which might be improved by incorporating prior knowledge about the relationships between input attributes and their relationship with salinity.
Details
- Title
- Mapping salinity using decision trees and conditional probabilistic networks
- Authors/Creators
- F. Evans (Author/Creator)H.T. Kiiveri (Author/Creator)G. West (Author/Creator)M. Gahegan (Author/Creator)
- Conference
- 2nd IEEE International Conference on Intelligent Processing Systems (IEEE ICIPS'98) (Gold Coast, QLD, 04/08/1998–07/08/1998)
- Identifiers
- 991005544360707891
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Conference paper
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