GEOSCAN Search Results: Fastlink


TitleSpatially locating soil classes within complex soil polygons - mapping soil capability for agriculture in Saskatchewan Canada
AuthorLi, Z; Huffman, T; Zhang, A; Zhou, F; McConkey, B
SourceAgriculture, Ecosystems and Environment vol. 152, 2012 p. 59-67,
Alt SeriesNatural Resources Canada, Contribution Series 20181783
PublisherElsevier BV
Mediapaper; on-line; digital
File formatpdf
SubjectsAgriculture; soils science; geophysics; Science and Technology; Nature and Environment; remote sensing; satellite imagery; soils; mapping techniques
ProgramClimate Change Geoscience Climate Change Impacts and Adaptation for Key Economic and Natural Environment Sectors
Released2012 03 21
AbstractThis 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.

Date modified: