Guillevic P. C., Privette J. L., Coudert B., Palecki M. A., Demarty Jérome, Ottle C., Augustine J. A. (2012). Land Surface Temperature product validation using NOAA's surface climate observation networks : scaling methodology for the Visible Infrared Imager Radiometer Suite (VIIRS). Remote Sensing of Environment, 124, p. 282-298. ISSN 0034-4257.
Titre du document
Land Surface Temperature product validation using NOAA's surface climate observation networks : scaling methodology for the Visible Infrared Imager Radiometer Suite (VIIRS)
Guillevic P. C., Privette J. L., Coudert B., Palecki M. A., Demarty Jérome, Ottle C., Augustine J. A.
Source
Remote Sensing of Environment, 2012,
124, p. 282-298 ISSN 0034-4257
NOAA will soon use the new Visible Infrared Imager Radiometer Suite (VIIRS) on the Joint Polar Satellite System (JPSS) as its primary polar-orbiting satellite imager. Employing a near real-time processing system, NOAA will generate a series of Environmental Data Records (EDRs) from VIIRS data. For example, the VIIRS Land Surface Temperature (LST) EDR will estimate the surface skin temperature over all global land areas and provide key information for monitoring Earth surface energy and water fluxes. Because both VIIRS and its processing algorithms are new, NOAA is conducting a rigorous calibration and validation program to understand and improve product quality. This paper presents a new validation methodology to estimate the quantitative uncertainty in the LST EDR, and contribute to improving the retrieval algorithm. It employs a physically-based approach to scaling up point LST measurements currently made operationally at many field and weather stations around the world. The scaling method consists of the merging information collected at different spatial resolutions within a land surface model to fully characterize large area (km x km scale) satellite products. The approach can be used to explore scaling issues over terrestrial surfaces spanning a large range of climate regimes and land cover types, including forests and mixed vegetated areas. The methodology was tested successfully with NASA/MODIS data, indicating an absolute error for MODIS LST products of 2.0 K at a mixed agricultural site (Bondville, IL) when accounting for scaling, and higher than 3 K without scaling. The VIIRS LST EDR requires a 1.5 K measurement accuracy and 2.5 K measurement precision. Ultimately, this validation approach should lead to an accurate and continuously-assessed VIIRS LST product suitable to support weather forecast, hydrological applications, or climate studies. It is readily adaptable to other moderate resolution satellite systems.
