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Proceedings Paper

Algorithm development for land surface temperature measurement from GOES-R satellite
Author(s): Yunyue Yu; Dan Tarpley; Rama Mundakkara Kovilakom; Hui Xu; Jeffrey L. Privette
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Paper Abstract

The Geostationary Operational Environmental Satellite (GOES) program is developing a new generation sensor, the Advanced Baseline Imager (ABI), to be carried on the GOES-R satellite to be lunched in approximately in 2014. Compared to the current GOES imager, ABI will have significant advantages for measuring land surface temperature as well as to providing qualitative and quantitative data for a wide range of applications. Specifically, spatial resolution of the ABI sensor is 2 km, and the infrared window noise equivalent temperature is 0.1 K, which are very close to the polarorbiting satellite sensors such as AVHRR. Most importantly, ABI observes the full disk every five minutes, which not only provides more cloud-free measurements but also makes daily temperature variation analysis possible. In this study we developed split window algorithms for the LST measurement from the ABI sensor. We generated the ABI sensor data using MODTRAN radiative transfer model and NOAA88 atmospheric profiles and ran regression analyses for the LST algorithm development. The algorithms are developed by optimizing existing split window LST algorithms and adding a path length correction term to minimize the retrieval errors due to difference atmospheric path absorption from nadir view to the edge-of-scan. The algorithm coefficients are stratified for dry and moist atmospheric conditions, as well as for the daytime and nighttime. The algorithm sensitivity to land surface emissivity uncertainty is analyzed to ensure the algorithm performance.

Paper Details

Date Published: 30 October 2007
PDF: 12 pages
Proc. SPIE 6749, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VII, 674919 (30 October 2007); doi: 10.1117/12.742245
Show Author Affiliations
Yunyue Yu, National Oceanic and Atmospheric Administration (United States)
Dan Tarpley, National Oceanic and Atmospheric Administration (United States)
Rama Mundakkara Kovilakom, National Oceanic and Atmospheric Administration (United States)
Hui Xu, National Oceanic and Atmospheric Administration (United States)
Jeffrey L. Privette, National Oceanic and Atmospheric Administration (United States)


Published in SPIE Proceedings Vol. 6749:
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VII
Manfred Ehlers; Ulrich Michel, Editor(s)

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