Algorithms and analysis tools for carbon content modeling in soil based on satellite data

Elissa R. Levine; Lubomir Kurz; Jan Smid; Marek Smid; Petr Volf

doi:10.1117/12.332764

11 December 1998 Algorithms and analysis tools for carbon content modeling in soil based on satellite data

Elissa R. Levine, Lubomir Kurz, Jan Smid, Marek Smid, Petr Volf

Proceedings Volume 3499, Remote Sensing for Agriculture, Ecosystems, and Hydrology; (1998) https://doi.org/10.1117/12.332764
Event: Remote Sensing, 1998, Barcelona, Spain

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.

Citation Download Citation

Elissa R. Levine, Lubomir Kurz, Jan Smid, Marek Smid, and Petr Volf "Algorithms and analysis tools for carbon content modeling in soil based on satellite data", Proc. SPIE 3499, Remote Sensing for Agriculture, Ecosystems, and Hydrology, (11 December 1998); https://doi.org/10.1117/12.332764

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