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Proceedings Paper

A statistical method to correct radiometric data measured by AVHRR onboard the National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellites (POES)
Author(s): Md. Z. Rahman; Leonid Roytman; Abdel Hamid Kadik
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Paper Abstract

This paper apply an statistical technique to correct radiometric data measured by Advanced Very High Resolution Radiometers(AVHRR) onboard the National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellites(POES). This paper study Normalized Difference Vegetation Index (NDVI) stability in the NOAA/NESDIS Global Vegetation Index (GVI) data for the period 1982-2003. AVHRR weekly data for the five NOAA afternoon satellites NOAA-7, NOAA-9, NOAA-11, NOAA-14, and NOAA-16 are used for the China dataset, for it includes a wide variety or different ecosystems represented globally. GVI has found wide use for studying and monitoring land surface, atmosphere, and recently for analyzing climate and environmental changes. Unfortunately the POES AVHRR data, though informative, can not be directly used in climate change studies because of the orbital drift in the NOAA satellites over these satellites' life time. This orbital drift introduces errors in AVHRR data sets for some satellites. To correct this error of satellite data, this paper implements Empirical Distribution Function (EDF) which is a statistical technique to generate error free long-term time-series for GVI data sets. We can use the same methodology globally to create vegetation index to improve the climatology.

Paper Details

Date Published: 16 May 2011
PDF: 12 pages
Proc. SPIE 8029, Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring; and Biometric Technology for Human Identification VIII, 80291F (16 May 2011); doi: 10.1117/12.882919
Show Author Affiliations
Md. Z. Rahman, LaGuardia Community College, CUNY (United States)
Leonid Roytman, The City College of New York, CUNY (United States)
Abdel Hamid Kadik, LaGuardia Community College, CUNY (United States)


Published in SPIE Proceedings Vol. 8029:
Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring; and Biometric Technology for Human Identification VIII
B. V. K. Vijaya Kumar; Sárka O. Southern; Kevin N. Montgomery; Salil Prabhakar; Arun A. Ross; Carl W. Taylor; Bernhard H. Weigl, Editor(s)

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