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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
A new approach for mapping of Biological Soil Crusts in semidesert areas with hyperspectral imagery
Remote Sensing of Environment, Volume 112, No. 5, Year 2008
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Description
Biological Soil Crusts (BSCs), consisting of cyanobacteria, algae, microfungi, lichens and bryophytes in varying proportions, live within or immediately on top of the uppermost millimeters of soil, where they form a more or less firm aggregation of soil particles and organisms. They mainly occur in soils of arid and semi-arid regions, which cover more than 35% of the earth's land surface and are assumed to play a major role as primary producers, C- and N-sinks and soil stabilizers. In order to establish a methodology for mapping of BSCs, their spectral characteristics with respect to different crust types were analyzed. The resulting reflectance spectra of different crust types had a shallow absorption feature centered around 680 nm in common, in which they differed from the spectra of bare soil. In October 2004, hyperspectral CASI data with a spatial resolution of 1 m were recorded in conjunction with field spectroscopic measurements in the Succulent Karoo, South Africa. Available spectral indices for Biological Soil Crusts were tested on the image but did not produce satisfying classifications. Therefore, an alternative approach was established based on spectral field data, field observations and the hyperspectral dataset. The newly developed Continuum Removal Crust Identification Algorithm (CRCIA) is based on small and narrow spectral characteristics, that were extracted by continuum removal and subsequently expressed as a set of logical conditions. Using this method, 16.2% of the area which covers 12 km2 of gently sloping hills with some granite outcrops were classified as BSCs. Validation of the classification resulted in a Kappa index of 0.831. In a next step, the methodology will be tested with regard to scale-dependent effects and applied to images covering areas with additional types of BSCs and soil to develop a robust and generally applicable method. © 2008 Elsevier Inc. All rights reserved.
Authors & Co-Authors
Weber, Bettina
Germany, Kaiserslautern
Technische Universität Kaiserslautern
Olehowski, C.
Germany, Heidelberg
Universität Heidelberg
Knerr, T.
Germany, Kaiserslautern
Technische Universität Kaiserslautern
Hill, Joachim
Germany, Trier
Universität Trier
Deutschewitz, Kirstin
Germany, Kaiserslautern
Technische Universität Kaiserslautern
Wessels, Dirk C.J.
South Africa, Sovenga
University of Limpopo
Eitel, Bernhard
Germany, Heidelberg
Universität Heidelberg
Büdel, Burkhard
Germany, Kaiserslautern
Technische Universität Kaiserslautern
Statistics
Citations: 90
Authors: 8
Affiliations: 4
Identifiers
Doi:
10.1016/j.rse.2007.09.014
ISSN:
00344257
Study Locations
South Africa