Robust downscaling approaches to disaggregation of data and projections under uncertainties: Case of land use and land use change systems

Ermoliev, Y., Ermolieva, T., Havlik, P. ORCID: https://orcid.org/0000-0001-5551-5085, Mosnier, A., Leclere, D., Fritz, S. ORCID: https://orcid.org/0000-0003-0420-8549, Obersteiner, M. ORCID: https://orcid.org/0000-0001-6981-2769, Kyryzyuk, S., & Borodina, O. (2017). Robust downscaling approaches to disaggregation of data and projections under uncertainties: Case of land use and land use change systems. Cybernetics and Systems analysis 53 (1) 31-41.

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Abstract

The interdependencies among land use systems at national and global levels motivate the development of advanced systems analysis approaches for integration of land use models operating at different scales. The paper develops
novel general approaches based on cross-entropy principle for downscaling aggregate data and projections, which are robust with respect to feasible priors.Robust downscaling methods account for the so-called non-Bayesian uncertainties, i.e., not complete, unobservable, or erroneous information or data. In numerous case studies in China, Ukraine, Brazil, the approaches allowed to derive local development projections of land use and land use change consistently with existing trends and expectations.

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