GEOSCAN, résultats de la recherche


TitreSpatially locating soil classes within complex soil polygons - mapping soil capability for agriculture in Saskatchewan Canada
AuteurLi, Z; Huffman, T; Zhang, A; Zhou, F; McConkey, B
SourceAgriculture, Ecosystems and Environment vol. 152, 2012 p. 59-67,
Séries alt.Ressources naturelles Canada, Contribution externe 20181783
ÉditeurElsevier BV
Documentpublication en série
Mediapapier; en ligne; numérique
Sujetstélédétection; imagerie par satellite; sols; techniques de cartographie; Agriculture; pédologie; géophysique; Sciences et technologie; Nature et environnement
ProgrammeGéosciences de changements climatiques, Impacts des changements climatiques et adaptation dans le secteur des ressources naturelles et d'autres secteurs clés de l'économie
Diffusé2012 03 21
Résumé(disponible en anglais seulement)
This paper proposes a simplified approach to mapping soil capability, as defined by the Canada Land Inventory (CLI), based on the hypothesis that the primary determinants of soil capability may be surrogated by Normalized Difference Vegetation Index (NDVI) derived from Earth Observation (EO) data integrated with other biophysical information. A case study in which a Decision Tree classification method with a boosting algorithm was used in spatially locating individual soil capability classes as estimated in the complex symbol of the CLI database was conducted in Saskatchewan Canada. The input metrics used for the classification include the first four principal components of the original NDVI images, phenological parameters, topographic factors, land cover and spatial dependence images. Validation showed high Kappa coefficients for the mapped soil capability classes within homogeneous soil polygons and high R-squares between the mapped soil area and CLI-estimated area within heterogeneous polygons. Results confirm the hypothesis that integrating parameters derived from the Moderate Resolution Imaging Spectro-radiometer (MODIS) 250. m time-series Normalized Difference Vegetation Index (NDVI) with ancillary data may serve as a comprehensive tool for classification of soil capability.