French, Andrew: U.S. Arid Land Agricultural Research Center (Project Lead)
Project Funding:
2011 - 2012
NRA: 2010 NASA: HyspIRI Preparatory Activities Using Existing Imagery
Funded by NASA
Abstract:
The proposed NASA mission, HyspIRI, offers an unprecedented opportunity to observe the earth's surface environment using a combination of satellite remote sensing technologies. This new combination would provide both high spectral and high spatial resolution at visible and infrared wavelengths, all at frequent observation intervals. In addition to the hyperspectral capabilities within visible and near infrared wavelengths, the HyspIRI mission notably offers multispectral thermal infrared imaging at 5 day repeat periods. The thermal bands can discriminate land cover and monitor land surface evapotranspiration in ways that are not feasible using more conventional remote sensing approaches.
This project capitalizes upon these innovations by initiating the synthesis of HyspIRI-like images from existing airborne and spaceborne remote sensing data. Data sets chosen will be derived from arid and semi-arid regions where the need for high quality remote sensing data is especially keen. Two data sets will be from New Mexico: the USDA Jornada Experimental Range, and the Sevilleta National Wildlife Refuge. A third data set will be from the Southern Great Plains of Oklahoma and Kansas.
Using archived MASTER, AVIRIS and ASTER data, 60-m remote sensing image data sets will be generated to help address three hydrological and climatological problems. The first problem is how to improve estimation accuracies of land surface temperature and emissivity for all land cover types. Focus for this problem will be placed on implementing calibration techniques for low spectral contrast surfaces. The second problem is how to improve land cover characterization over those achieved with more conventional approaches. Emphasis will be placed on techniques using both hyperspectral visible-infrared channels and multispectral thermal infrared channels; these techniques will help distinguish between short term soil moisture changes and long term vegetation changes. The third problem is how to improve the accuracy of evapotranspiration estimation with remote sensing instruments. Here we will demonstrate that improvements are possible by utilizing well-calibrated hyperspectral visible near infrared data in combination with multispectral thermal data to yield good quality ET estimates for a wide range of land cover conditions.
2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
- Deriving Land Cover Fractional Maps with Unmixing Algorithm
-- (Uttam Kumar, Cristina Milesi, S Kumar Raja, Ramakrishna R. Nemani, Sangram Ganguly)
[abstract]
More details may be found in the following project profile(s):
