Phenology Assessment Using Satellite Radar & Microwave Remote Sensing
Vegetation Phenology Assessment Using Satellite Radar Remote Sensing: Global Monitoring of Daily and Seasonal Changes in Canopy Structure and Water Status.
Seasonal vegetation dynamics significantly impact the carbon cycle and weather (surface energy balance, transpiration vapor fluxes). These impacts are related to growing season length for evergreen ecosystems, to timing of leaf flush and senescence for drought- or cold-deciduous systems, and to seasonal and annual variability in canopy biomass. Spaceborne remote sensing is the only practical tool for monitoring seasonal vegetation dynamics globally with high temporal repeat and moderate spatial resolution.
We are working to establish a satellite radar and microwave remote sensing-based methodology and associated product time series for global assessment and monitoring of vegetation phenology, capitalizing on the systematic, multi-year (1999 onward) measurement series provided by the SeaWinds scatterometers and AMSR-E radiometer. We exploit the high temporal repeat, all-weather capabilities of satellite radar and microwave and dynamic radar backscatter sensitivity to both vegetation structure and water status to develop a comprehensive phenology measure that is synergistic with existing satellite optical-IR based approaches that are primarily sensitive to effective (sunlit) leaf area and photosynthetic biomass.
Image is estimated Length of the Growing Season derived from the AMSR-E Vegetation Optical Depth (VOD) Land Surface Parameter. VOD is part of a suite of land surface parameters calculated at NTSG/FLBS and is available via our ftp site.
Jones, M.O., Kimball, J.S., McDonald, K.C., Jones, L.A. Utilizing Satellite Passive Microwave Remote Sensing for Monitoring Global Land Surface Phenology – recently submitted
Jones, L.A., Ferguson, C.R., Kimball, J.S., Zhang, K., Chan, S.K., McDonald, K.C., Njoku, E.G., & Wood, E.F. (2010). Satellite Microwave Remote Sensing of Daily Land Surface Air Temperature Minima and Maxima from AMSR-E. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Jones, L.A., Kimball, J.S., McDonald, K.C., Chan, S.K., & Njoku, E.G. (2009). A method for deriving northern hemisphere vegetation phenology, land surface wetness, and open water fraction from AMSRE. In, IGARSS Symposium. Cape Town, South Africa