1a.Objectives (from AD-416):
1. Fuse Landsat and MODIS satellite data streams to facilitate high spatial resolution monitoring of carbon, water and heat fluxes at a temporal frequency not otherwise possible.
2. Refine and implement a novel technique for using satellite estimates of leaf chlorophyll to delineate variability in photosynthetic efficiency in space and time.
3. Develop and apply a scalable thermal-based flux modeling system and multi-scale data fusion approach to targeted regions that encompass a range of land cover types and environmental conditions.
4. Validate blended vegetation biophysical products and flux simulations using a combination of in-situ datasets, multi-year flux tower observations and independent satellite datasets and land-surface model output.
5. Work toward an automated approach to enable routine thermal-based flux mapping at fine spatial scales (<100 m) critically important to local water resource and agricultural management.
1b.Approach (from AD-416):
Using in-situ measurements of canopy light-use efficiency (LUE) and leaf chlorophyll content collected at several flux tower sites across the U.S., evaluate functional relationship developed at BARC OPE3 and Bushland TX ARS experiment sites. This relationship will be embedded into a remote sensing model of vegetation canopy radiative transfer and use to map LUE at several flux sites within the U.S. using high resolution remote sensing inputs. These remotely sensed LUE maps will bed input into a model that maps coupled carbon, water and energy fluxes at multiple spatial and temporal scales using thermal-band imagery from the MODIS (1km daily) and Landsat (30m 16-day) satellites. The STARFM data fusion algorithm will be used to fuse MODIS/Landsat flux maps to generate daily flux maps at 30m (sub-field) spatial resolution. Daily flux predictions of evapotranspiration and canopy carbon uptake will then be evaluated in comparison with flux tower observations.
In Year 1 of this project, the primary implementation tasks were to. 1)improve an existing canopy reflectance model (REGFLEC) used to estimate leaf area and chlorophyll content from shortwave remote sensing data;. 2)commence evaluation of carbon, water and energy flux estimates from the multi-scale Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance model and associated flux disaggregation technique (DisALEXI) using thermal infrared (TIR) imagery and REGFLEC leaf area and chlorophyll data; and. 3)develop and evaluate techniques for fusing ALEXI/DisALEXI maps generated with multiple thermal satellite sensors to provide time-continuous water-use and carbon flux data at scales of individual farm fields.