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

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

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