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TitleMultitemporal, Multichannel AVHRR Data Sets for Land Biosphere Studies: Artifacts and Corrections
 
AuthorCihlar, J; Ly, H; Li, Z; Chen, J M; Pokrant, H T; Huang, F
SourceRemote Sensing of Environment vol. 60, issue 1, 1997 p. 35-57, https://doi.org/10.1016/s0034-4257(96)00137-x
Image
Year1997
Alt SeriesEarth Sciences Sector, Contribution Series 20041776
PublisherElsevier BV
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
SubjectsScience and Technology; remote sensing; satellites; satellite imagery; reflectance; advanced very high resolution radiometer (AVHRR); normalized difference vegetation index (NDVI); processing; algorithms; atmospheric correction
Illustrationsflow charts; formulae; tables; graphs
AbstractTemporal compositing of daily optical satellite data has become an accepted methodology for obtaining frequent images of large areas for studies of the land surface. However, such composite data sets sometimes contain large 'articfacts', i.e. errors due to sources unrelated to the surface itself. The goal of this study was to develop a series of preprocessing operations which would identify and remove as many of these errors as possible. The specific objective was to obtain, every 10 days, surface reflectance in AVHRR channels 1 and 2 and NDVI (all referenced to a constant viewing geometry) and surface temperature.

The processing steps of the method include atmospheric corrections; the identification of pixels 'contaminated' by clouds and snow (including subpixel); bidirectional reflectance and thermal emissivity corrections; and the replacement of the contaminated pixels through interpolation. The resulting procedures yield surface reflectance and NDVI fully corrected for bidirectional effects; a version of NDVI corrected for solar zenith only; and surface temperature corrected for atmospheric and surface emissivity effects. An evaluation of the resulting data set shows that the procedures provide significantly improved data products compared to the raw composites but they do not approximate a single-date image closely enough. This is attributed to the limitations of the input data and the knowledge of atmospheric (and partly bidirectional) characteristics applicable to each composite pixel.

GEOSCAN ID218578

 
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