Digital soil mapping in the absence of field training data: A case study using terrain attributes and semiautomated soil signature derivation to distinguish ecological potential

TitleDigital soil mapping in the absence of field training data: A case study using terrain attributes and semiautomated soil signature derivation to distinguish ecological potential
Publication TypeJournal Article
Year of Publication2011
AuthorsBrowning D.M., Duniway M.C.
JournalApplied and Environmental Soil Science
Volume2001
IssueArticle ID 421904
Start Page421904
Pagination421904
Date Published04/2011
ARIS Log Number265397
Abstract

Spatially-explicit data for soil properties governing plant water availability are needed to understand mechanisms influencing plant species distributions and predict plant responses to changing climate. This is especially important for arid and semi-arid regions. Spatial data representing surrogates for soil forming factors are becoming widely available (e.g. spectral and terrain layers). However, field-based training data remain a limiting factor, particularly across remote and extensive drylands. We present a method to map soils with Landsat ETM+ imagery and high resolution (5 m) terrain (IFSAR) data based on statistical properties of the input data layers that do not rely on field training data. We then characterize soil classes mapped using this semi-automated technique. The method distinguished spectrally distinct soil classes that differed in subsurface rather than surface properties. Field evaluations of the soil classification in conjunction with analysis of long-term vegetation dynamics indicate the approach was successful in mapping areas with similar soil properties and ecological potential.

URL/files/bibliography/11-006.pdf
DOI10.1155/2011/421904