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The use of remote sensing in soil and terrain mapping — A review


Mulder, V L; de Bruin, S; Schaepman, M E; Mayr, T R (2011). The use of remote sensing in soil and terrain mapping — A review. Geoderma, 162(1-2):1-19.

Abstract

This article reviews the use of optical and microwave remote sensing data for soil and terrain mapping with emphasis on applications at regional and coarser scales. Remote sensing is expected to offer possibilities for improving incomplete spatial and thematic coverage of current regional and global soil databases. Traditionally, remotely sensed imagery have been used to support segmentation of the landscape into rather homogeneous soil–landscape units for which soil composition can be established by sampling. Soil properties have also been inferred from optical and microwave data using physically-based and empirical methods. Used as a secondary data source, remotely sensed imagery may support spatial interpolation of sparsely sampled soil property data. Soil properties that have been measured using remote or proximal sensing approaches include mineralogy, texture, soil iron, soil moisture, soil organic carbon, soil salinity and carbonate content. In sparsely vegetated areas, successful use of space borne, airborne, and in situ measurements using optical, passive and active microwave instruments has been reported. On the other hand, in densely vegetated areas, soil data acquisition typically relied on indirect retrievals using soil indicators, such as plant functional groups, productivity changes, and Ellenberg indicator values. Several forms of kriging, classification and regression tree analyses have been used jointly with remotely sensed data to predict soil properties at unvisited locations aiming at obtaining continuous area coverage. We expect that remotely sensed data from existing platforms and planned missions can provide an important data source supporting digital soil mapping. Yet, most studies so far have been performed on a local scale and only few on regional or smaller map scale. Although progress has been made, current methods and techniques still bear potential to further explore the full range of spectral, spatial and temporal properties of existing data sources. For example, space borne spectroscopy has been of limited use in retrieving soil data when compared to laboratory or field spectroscopy. To date, there is no coherent methodology established, where approaches of spatial segmentation, measurements of soil properties and interpolation using remotely sensed data are integrated in a holistic fashion to achieve complete area coverage. Such approaches will enhance the perspectives of using remotely sensed data for digital soil mapping.

Abstract

This article reviews the use of optical and microwave remote sensing data for soil and terrain mapping with emphasis on applications at regional and coarser scales. Remote sensing is expected to offer possibilities for improving incomplete spatial and thematic coverage of current regional and global soil databases. Traditionally, remotely sensed imagery have been used to support segmentation of the landscape into rather homogeneous soil–landscape units for which soil composition can be established by sampling. Soil properties have also been inferred from optical and microwave data using physically-based and empirical methods. Used as a secondary data source, remotely sensed imagery may support spatial interpolation of sparsely sampled soil property data. Soil properties that have been measured using remote or proximal sensing approaches include mineralogy, texture, soil iron, soil moisture, soil organic carbon, soil salinity and carbonate content. In sparsely vegetated areas, successful use of space borne, airborne, and in situ measurements using optical, passive and active microwave instruments has been reported. On the other hand, in densely vegetated areas, soil data acquisition typically relied on indirect retrievals using soil indicators, such as plant functional groups, productivity changes, and Ellenberg indicator values. Several forms of kriging, classification and regression tree analyses have been used jointly with remotely sensed data to predict soil properties at unvisited locations aiming at obtaining continuous area coverage. We expect that remotely sensed data from existing platforms and planned missions can provide an important data source supporting digital soil mapping. Yet, most studies so far have been performed on a local scale and only few on regional or smaller map scale. Although progress has been made, current methods and techniques still bear potential to further explore the full range of spectral, spatial and temporal properties of existing data sources. For example, space borne spectroscopy has been of limited use in retrieving soil data when compared to laboratory or field spectroscopy. To date, there is no coherent methodology established, where approaches of spatial segmentation, measurements of soil properties and interpolation using remotely sensed data are integrated in a holistic fashion to achieve complete area coverage. Such approaches will enhance the perspectives of using remotely sensed data for digital soil mapping.

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Additional indexing

Item Type:Journal Article, refereed, further contribution
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2011
Deposited On:07 Mar 2012 07:46
Last Modified:07 Dec 2017 12:10
Publisher:Elsevier
ISSN:0016-7061
Publisher DOI:https://doi.org/10.1016/j.geoderma.2010.12.018

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