Beharry-Borg, N., JCR Smart, M. Termansen, K Hubacek (In Press). Evaluating farmers’ likely participation in a payment program for water quality protection in the UK uplands. Regional Environmental Change
Drake, B., J.C.R. Smart, M. Termansen, K. Hubacek (In Press). “Public Preferences for Production of Local and Global Ecosystem Services. Regional Environmental Change
Coleby, van der Horst, Hubacek, Goodier, Burgess, Howard, and Graves (2012). “Environmental Impact Assessment and Ecosystems Services: the case of energy crops the UK “Journal for Environmental Planning and Management, Vol. 55/3. 369-385.
Pan, Y., Li, L., Zhang, J., Liang, S., Zhu, X., & Sulla-Menashe, D. (2012). Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index. Remote Sensing of Environment, 119, 232-242
Preserving Landsat's Legacy
The Landsat Legacy Project is directed toward documenting the technical history of the Landsat program and describe the evolution of the program from a remote sensing system, into a global observing system. With each subsequent Landsat mission, there was an evolution in thinking; lessons learned from the operators, requests from a growing community of national and international users, and a shared sense of understanding of the value of the data in the archive, that generated more systematic approaches to the acquisition of data for the archive.
Zhu, X., Liang, S., Pan, Y., & Zhang, X. (2011). Agricultural irrigation impacts on land surface characteristics detected from satellite data products in Jilin Province, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensi
Integration of long term Landsat observations with DESDynI measurements for monitoring terrestrial carbon flux within and beyond the DESDynI mission
The overall objective of this project is to develop improved capabilities for addressing the overarching science question of understanding the spatial patterns and temporal dynamics of terrestrial carbon stocks and fluxes (CCSP, 2003). This will be achieved by improving and extending DESDynI predictions of biomass and biomass dynamics through fusion with the long-term record of Landsat observations. In this proposal we seek to: