AVHRR data processing for near-real-time applications

Andre R. S. Marcal; Alexandra L. Nunes; Janete S. Borges

doi:10.1117/12.510674

13 February 2004 AVHRR data processing for near-real-time applications

Andre R. S. Marcal, Alexandra L. Nunes, Janete S. Borges

Proceedings Volume 5239, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology III; (2004) https://doi.org/10.1117/12.510674
Event: Remote Sensing, 2003, Barcelona, Spain

Abstract

Polar orbiting satellites with low spatial resolution sensors, such as the AVHRR, provide repeated global coverage of the Earth. The data is directly transmitted to ground stations, and in some cases distributed immediately after the data acquisition. Near real time applications can be implemented if the adequate processing tools are available. This paper presents a near real time processing system, developed for NOAA/AVHRR data acquired from the Dundee satellite station. The system performs image calibration, geometric corrections and atmospheric corrections with minimum operator intervention. The geometric corrections consist of an orbital-based correction refined by the automatic identification of Ground Control Points (GCPs) by image matching. The atmospheric correction is based on simulations performed on the 6S radiative transfer code using a set of typical and expected values for the most significant parameters. An attempt to evaluate the error associated with the simplified atmospheric correction method was carried out. As an illustration, 3 AVHRR images from NOAA 16 were processed. The ranges of values encountered for the most relevant parameters were analyzed. The range and average values for the reflectance channels 1 and 2 with and without the atmospheric correction are compared. These were used to produce standard Normalized Difference Vegetation Index (NDVI) images and atmospheric corrected NDVI images.

Citation Download Citation

Andre R. S. Marcal, Alexandra L. Nunes, and Janete S. Borges "AVHRR data processing for near-real-time applications", Proc. SPIE 5239, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology III, (13 February 2004); https://doi.org/10.1117/12.510674

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