Global High-resolution Land-use Change Projections: A Bayesian Multinomial Logit Downscaling Approach Incorporating Model Uncertainty and Spatial Effects

11769 16 31848 2 44943 document 31848 Global High-resolution Land-use Change Projections_A Bayesian Multinomial Logit Downscaling Approach Incorporating Model Uncertainty and Spatial Effects.pdf application/pdf 095c54148ba045ccbb97b66b557227d4 MD5 1093827 2016-01-19 13:28:59 https://pure.iiasa.ac.at/id/eprint/11769/1/Global%20High-resolution%20Land-use%20Change%20Projections_A%20Bayesian%20Multinomial%20Logit%20Downscaling%20Approach%20Incorporating%20Model%20Uncertainty%20and%20Spatial%20Effects.pdf 11769 1 1 application/pdf text en public cc_by_nc_sa

Global High-resolution Land-use Change Projections_A Bayesian Multinomial Logit Downscaling Approach Incorporating Model Uncertainty and Spatial Effects.pdf

published 31867 2 44993 document 31867 lightbox.jpg image/png 5318906b8f73e20cb027d9dcbb64a4a7 MD5 81073 2016-01-19 13:39:05 https://pure.iiasa.ac.at/id/eprint/11769/2/lightbox.jpg 11769 2 2 image/png other Thumbnails conversion from text to thumbnail_lightbox en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/31848 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/31848 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/31848 archive 2 disk0/00/01/17/69 2016-01-19 13:30:18 2025-03-12 05:00:12 2016-01-19 13:46:55 conference_item show 1 Krisztin T. 2088 0000-0002-9241-8628 Havlik P. 1868 0000-0001-5551-5085 Leclère D. 2000 0000-0002-8658-1509 Moreau I. Global High-resolution Land-use Change Projections: A Bayesian Multinomial Logit Downscaling Approach Incorporating Model Uncertainty and Spatial Effects pub prog_esm Using econometric models to estimate land-use change has a long tradition in scientific literature. Recent contributions show the importance of including spatial information and of using a multinomial framework to take into account the interdependencies between the land-use classes. Few studies, however, agree on the relevant determinants of land-use change and there are no contributions so far comparing determinants on a global scale. Using multiple 5 arc minute resolution datasets of land-use change between 2000 and 2010 and taking into account the transitions between forest, cropland, grassland and all other land covers, we estimate a Bayesian multinomial logit model, using the efficient Pólya-Gamma sampling procedure introduced by Polson et al. (2013). To identify and measure the determinants of land-use change and the strength of spatial separation, our model implements Bayesian model selection through stochastic search variable selection (SSVS) priors and spatial information via Gaussian Process (GP) priors. Our results indicate that spatial proximity is of central importance in land-use change, in all regions except the pacific islands. We also show that infrastructure policy, proxied by mean time to market, seems to have a significant impact on deforestation throughout most regions. In a second step we use aggregate, supra national land-use change results from the partial equilibrium agricultural model GLOBIOM as a framework for projecting our model in ten-year intervals up to 2100 on a spatially explicit scale along multiple shared socioeconomic pathways. 2015-11 published 167 119 174 public poster Systems Analysis 2015 - A Conference in Celebration of Howard Raiffa Laxenburg, Austria 11 -13 November, 2015 conference FALSE FALSE info:eu-repo/semantics/conferenceObject