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Proceedings Paper

Algorithms and analysis tools for carbon content modeling in soil based on satellite data
Author(s): Elissa R. Levine; Lubomir Kurz; Jan Smid; Marek Smid; Petr Volf
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Paper Abstract

Estimate of the organic carbon content in soil is critical for global change modeling activities. Therefore, the predictive model for estimating soil carbon would provide an important tool for the scientific community. We used remotely sensed TM imaginary data together with the soil profiles and moss layer carbon data for the Northern Study Area (NSA) of the BOREAS project. Different classification and functional models of the carbon dependency on remotely sensed data were developed. The complexity of the models was scrutinized. Based on these techniques, we have developed a set of analysis tools. These tools and an Internet based access to some of these tools will be presented.

Paper Details

Date Published: 11 December 1998
PDF: 8 pages
Proc. SPIE 3499, Remote Sensing for Agriculture, Ecosystems, and Hydrology, (11 December 1998); doi: 10.1117/12.332764
Show Author Affiliations
Elissa R. Levine, NASA Goddard Space Flight Ctr. (United States)
Lubomir Kurz, SKS Enterprises (United States)
Jan Smid, Morgan State Univ. and SKS Enterprises (United States)
Marek Smid, Morgan State Univ. and SKS Enterprises (Czech Republic)
Petr Volf, UTIA Prague (Czech Republic) and Technical Univ. Liberec (Czech Republic)


Published in SPIE Proceedings Vol. 3499:
Remote Sensing for Agriculture, Ecosystems, and Hydrology
Edwin T. Engman, Editor(s)

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