Instance selection and classification tree analysis for large spatial datasets in digital soil mapping
Authors:
- Karsten SchmidtKarsten Schmidt
- Thorsten BehrensTBThorsten Behrens
- Thomas ScholtenThomas Scholten
Abstract
No abstract availableKeywords
This publication has 36 references indexed in Scilit:
- Estimation and potential improvement of the quality of legacy soil samples for digital soil mappingGeoderma, 2007
- Digital soil mapping in Germany—a reviewJournal of Plant Nutrition and Soil Science, 2006
- Digital soil mapping using artificial neural networksJournal of Plant Nutrition and Soil Science, 2005
- A hierarchical partitioning method for optimizing irrigation strategiesAgricultural Systems, 2004
- Soil survey as a knowledge systemGeoderma, 2004
- A strategy to fill gaps in soil survey over large spatial extents: an example from the Murray–Darling basin of AustraliaGeoderma, 2003
- Advances in Instance Selection for Instance-Based Learning AlgorithmsData Mining and Knowledge Discovery, 2002
- Extracting soil-landscape rules from previous soil surveysSoil Research, 1999
- Random sampling or geostatistical modelling? Choosing between design-based and model-based sampling strategies for soil (with discussion)Geoderma, 1997
- Designing efficient soil survey schemes with a knowledge-based system using dynamic programmingGeoderma, 1997