|NORMAN, JOHN M - University Of Wisconsin|
|Kustas, William - Bill|
|Starks, Patrick - Pat|
|AGAM, NURIT - Foreign Agricultural Service (FAS, USDA)|
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/13/2008
Publication Date: 12/15/2008
Citation: Anderson, M.C., Norman, J.M., Kustas, W.P., Houborg, R., Starks, P.J., Agam, N. 2008. A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales. Remote Sensing Environment. 112:4227-4241.
Interpretive Summary: Canopy water loss through transpiration and carbon assimilation through the photosynthetic process are both regulated by stomata in the leaf surfaces, which constrict under conditions of stress. Therefore transpiration and assimilation fluxes are expected to be tightly coupled, and it is appropriate that they be modeled within a coupled framework. Stressed canopies, with reduced transpiration rates, exhibit elevated radiometric temperature so remote sensing images acquired in the thermal band provide very useful information for mapping these coupled fluxes over large areas. This paper describes enhancements to an existing thermal-based model of surface energy balance. The enhancements improve water loss predictions by incorporating consideration of the bulk canopy stomatal conductance, and also enable simultaneous mapping of carbon fluxes. Model predictions are verified in comparison with tower and aircraft-based flux observations collected over El Reno, OK during the Southern Great Plains field experiment of 1997 (SGP97).
Technical Abstract: Robust remote sensing methodologies for mapping instantaneous land-surface CO2 fluxes over a range of spatial scales are required to reconcile “top-down” (e.g., atmospheric) and “bottom-up” (e.g., scaled leaf) models of land-atmosphere carbon exchange. This study investigates the implementation of an analytical, light-use efficiency (LUE)-based model of canopy conductance within a two-source energy balance (TSEB) scheme driven primarily by thermal remote sensing inputs. The LUE model computes coupled canopy carbon assimilation and transpiration fluxes, and replaces a Priestley-Taylor (PT) based transpiration estimate used in the original form of the TSEB model. Both the LUE and PT forms of the model were compared with eddy covariance tower measurements acquired in rangeland near El Reno, OK. The LUE method resulted in improved partitioning of the surface energy budget, capturing effects of midday stomatal closure in response to increased vapor pressure deficit and reducing errors in half-hourly flux predictions from 16 to 12%. The spatial distribution of CO2 flux was mapped over the El Reno study area using data from an airborne thermal imaging system and compared to fluxes measured by an aircraft flying a transect over rangeland, riparian areas, and harvested winter wheat. Soil respiration contributions to the net carbon flux were modeled spatially using remotely sensed estimates of soil surface temperature, soil moisture, and leaf area index. Modeled carbon fluxes from this heterogeneous landscape compared well in magnitude and pattern to the aircraft fluxes. Flux footprint analyses suggest that the sensible heat flux (actively involved in buoyancy production) is more tightly correlated with surface states directly under the aircraft, while the more passive water and carbon fluxes are better related to source area conditions upwind of the aircraft. The thermal inputs proved to be valuable in modifying the effective LUE from a nominal species-dependent value. The model associates cooler canopy temperatures with enhanced transpiration, indicating higher canopy conductance and carbon assimilation rates. The surface energy balance constraint in this modeling approach provides a useful and physically intuitive mechanism for incorporating subtle signatures of soil moisture deficiencies and reduced stomatal aperture, manifest in the thermal band signal, into the coupled carbon and water flux estimates.