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 2 of this project, the primary implementation tasks were to. 1)develop modeling infrastructure to facilitate routine implementation of the multi-sensor flux evaluations and fusion algorithm;. 2)test fusion applications with ground-based water flux observations collected over multiple agricultural field experiment sites;. 3)evaluate coupled carbon fluxes at a subset of these sites where extensive biophysical data were collected;. 4)further refine an existing canopy reflectance model (REGFLEC) that will be used to estimate leaf area and chlorophyll content inputs to the final fusion algorithm. All ARS objectives for Year 3 were successfully met.