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Title:   Author  item
                                            Cammalleri, Carmeloitem
                                            Anderson, Marthaitem
                                            HOUBORG, RASMUS - Collaboratoritem
                                            Gao, Fengitem
                                            Kustas, William

                                                         - *Bill*item
                                            Schull, Mitchell
  Submitted to: Meeting Abstract
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 7/2/2012
                                    Publication  Date: 7/27/2012
                                    Citation: Cammalleri, C.N., Anderson, M.C., Houborg, R., Gao, F.N., Kustas, W.P., Schull, M.A. 2012. An integrated approach for high spatial resolution mapping of water and carbon fluxes using multi-sensor data [abstract]. Proceedings of the  Society of Photo-Optical Instrumentation Engineers (SPIE) 2012  Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology, July 22-27, 2012, Munich, Germany.Interpretive Summary:
                                Technical Abstract: In the last few years, modeling of surface processes, such as water and carbon balances, vegetation growth and energy budgets, has focused on integrated approaches that combine aspects of hydrology, biology and meteorology into unified analyses. In this context, remotely sensed data often have a core role due to the cross-cutting impact of this novel source of spatially distributed information on all these research areas. However, several applications, such as drought monitoring, yield forecasting and crop management, require spatially detailed products at sub-field scales, which can be obtained only with support of adequately fine resolution remote sensing data (< 100 m). In particular, observations in the visible to the near infrared (VIS/NIR) spectral region can be used to derive biophysical and biochemical properties of the vegetation such as leaf area index and leaf chlorophyll. Complementarily, the thermal infrared (TIR) signal provides valuable information about land surface temperature status, which in turn represents an accurate proxy indicator of the sub-surface moisture status by means of surface energy budget analysis. Additionally, the strong link between crop water stress and stomatal closure allows inference of crop carbon assimilation using the same tools. In this work, an integrated approach is proposed to model both carbon and water budgets at field scale by joint use of a thermal-based Two Source Energy Budget (TSEB) model and an analytical, Light-Use-Efficiency (LUE) based model of canopy resistance. This modeling framework allows integration of information retrieved by both high and coarse resolution satellites by means of a data fusion procedure.
A set of Landsat and MODIS (MODerate resolution Imaging Spectroradiometer) images are used to investigate the suitability of this approach, and the modeled fluxes are compared with observations made by several flux towers in terms of both water and carbon fluxes.


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