Tools
Tools
Fritz, S. 
ORCID: https://orcid.org/0000-0003-0420-8549, Havlik, P. ORCID: https://orcid.org/0000-0001-5551-5085, Schneider, U.A., Schmid, E., Skalsky, R. ORCID: https://orcid.org/0000-0002-0983-6897, & Obersteiner, M. ORCID: https://orcid.org/0000-0001-6981-2769
(2009).
Uncertainties in global land cover data and its implications for climate change mitigation policies assessment.
In: Proceedings from the 33rd International Symposium on Remote Sensing of Environment (ISRSE-33) "Sustaining the Millennium Development Goals", 4-8 May 2009.
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Abstract
Land cover maps provide critical input data for global models of land use. Urgent questions exist, such as how much land is available for the expansion of agriculture to combat food insecurity, how high will be competition for land between food and bioenergy in the future as well as how much land is there available for afforestation projects? These questions can only be answered if reliable maps of land cover exist.
We put this research in the framework of GEOSS, examine how modeling tools can be used for benefit assessment and design an assessment framework.
We illustrate the importance of good quality global land cover maps by using cropland extend from the currently best global maps of land cover namely GLC-2000, MODIS, GlobCover and CropLikelyhood as input for the EPIC model (to model crop yields) and global economic land use model GLOBIOM. We use all of the 4 maps and create a maximum crop extend and map. Based on a baseline map and the maximum crop extend map e model effects of climate policies (e.g. the potentials of substitution of fossil fuels with biofuels).
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Research Programs: | Forestry (FOR) |
| Bibliographic Reference: | In:; Proceedings from the 33rd International Symposium on Remote Sensing of Environment (ISRSE-33) "Sustaining the Millennium Development Goals"; 4-8 May 2009, Stresa, Italy |
| Depositing User: | IIASA Import |
| Date Deposited: | 15 Jan 2016 08:42 |
| Last Modified: | 19 Oct 2022 05:00 |
| URI: | https://pure.iiasa.ac.at/9057 |
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