- Related Research Areas
- Carbon Cycle & Ecosystems
We propose to develop a comprehensive measure of global vegetation phenology that exploits the high temporal repeat, all-weather capabilities of satellite radar and is sensitive to dynamic changes in both vegetation structure and water status. We will utilize a radar backscatter modeling framework with biophysical measurements from regional station networks to quantify sensitivities of alternate frequencies (Ku-, C- and L-band) and polarizations to canopy phenology across regional biomass and moisture gradients using time series satellite radar backscatter measurements from the SeaWinds scatterometer, ALOS PALSAR and ASCAT. We will examine potential synergies between radar based phenology and vegetation indices derived from satellite optical-IR remote sensing. This investigation builds on previous work, wherein we successfully applied SeaWinds for monitoring North American grassland response to regional drought, and seasonal changes in vegetation canopy biomass and LAI for a diverse set of global biomes. We will extend this effort to the full global vegetated domain by exploiting robust Ku-band backscatter sensitivity to surface structure and dielectric properties, as well as the daily temporal fidelity and global coverage of the SeaWinds scatterometers. These attributes will enable us to develop a comprehensive measure of global phenology, incorporating dynamic variability in landscape moisture and canopy structure. Satellite Radar backscatter time series are sensitive to spatial and temporal variations in landscape freeze/thaw state, which is a fundamental environmental constraint to the growing season for more than two-thirds of Earth's vegetated land area. It also provides a mechanism for disaggregating annual time series into growing and non-growing seasons where cold temperatures constrain water mobility and ecosystem activity. Radar backscatter time series can also be analyzed to assess temporal changes in canopy structure and water status, including the capacity to identify significant plant stress (e.g., drought) and associated plant physiological constraints to canopy evaporation, ecosystem productivity and terrestrial carbon sequestration of atmospheric CO2. Radar backscatter sensitivity to canopy condition is a function of sensor frequency and polarization, as well as land cover type and vegetation biomass. We will assess coincident satellite radar backscatter time series encompassing a range of different sensors, frequencies and polarizations using forward radar scattering models to quantify the physical basis of observed backscatter behavior and for developing improved phenology algorithms. These results will also be evaluated using current satellite remote sensing measures of global vegetation dynamics and site based ecosystem model simulations to determine linkages between radar backscatter behavior and landscape biospheric processes. This study will provide a comprehensive measure of global phenology that incorporates information on both canopy structure and water status and provides relatively precise global daily mapping and monitoring capabilities regardless of solar illumination, cloud cover, smoke and other optical aerosol effects. The proposed high-temporal resolution mapping of this critical variable will substantially augment and enhance current information from EOS visible-IR remote sensing (e.g., MODIS, AVHRR), which is commonly limited to coarse temporal composites of standard products required to mitigate cloud cover and atmospheric aerosol contamination, and substantial data loss at high latitudes from shadowing and reduced solar illumination for much of the year.
Project PI: Kyle McDonald/Jet Propulsion Laboratory
Jet Propulsion Laboratory M/S 300-233 4800 Oak Grove Drive Pasadena, CA 91109
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