Document Type
Article
Publication Version
Version of Record
Publication Date
2-3-2012
Description
Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.
Publication Title
Biogeosciences
Volume
9
First Page
631
Last Page
648
DOI of Published Version
10.5194/bg-9-631-2012
Pages
17
Type
text
Format
application/pdf
Language
en
Publisher
Copernicus Publications
Rights
© 2012 Dieye, A. M., Roy, D.P., Hanan, N.P., Liu, S., Hansen, M., Toure, A.
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
Recommended Citation
Dieye, Amadou M.; Roy, David P.; Hanan, N. P.; Lui, S.; Hansen, M.; and Toure, A., "Sensitivity Analysis of the GEMS Soil Organic Carbon Model to Land Cover Land Use Classification Uncertainties Under Different Climate Scenarios in Senegal" (2012). GSCE Faculty Publications. 53.
https://openprairie.sdstate.edu/gsce_pubs/53
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Biogeochemistry Commons, Geology Commons, Physical and Environmental Geography Commons, Remote Sensing Commons, Spatial Science Commons, Stratigraphy Commons