Evaluation of Data Reduction and Composing of the NOAA Global Vegetation Index Product: A Case Study

Abstract

Data acquired by the AVHRR onboard the TIROS/NOSS series of satellites are spatially degraded from a 1 km resolution at nadir (LAC) to several coarser resolutions. Global Area Coverage Coverage (GAC) data are processed onboard the satellites and have a resolution of approximately 4 km. Global Vegetation Index (GVI) data are processed from sampled GAC data and have a resolution of approximately 15 km. The objectives of this study were to examine the effects of spatial degradation of NOAA AVHRR data on monitoring of land surface or related processes over large areas and to examine alternative procedures for computation and compositing of the GVI data product. While differences existed between the vegetation index values computed for the examined data resolutions, a portion of the observed difference was not due directly to reduction of the satellite data. The mean values of the low resolution (GAC or GVI) data were representative of the full resolution data. Thus, low resolution data used in monitoring activities would likely provide the same results as full resolution data (LAC). The difference index would be the recommended algorithm for satellite zenith angle selection if advantages exist for selection of backscatter views of vegetation from satellites.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1990
Accession Number
ADA227397

Entities

People

  • J. F. Brown
  • K. P. Gallo

Organizations

  • National Oceanic and Atmospheric Administration

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Area Coverage
  • Artificial Satellites
  • Backscattering
  • Boundaries
  • Data Centers
  • Data Processing
  • Data Reduction
  • Detection
  • Geography
  • High Resolution
  • Image Processing
  • Information Processing
  • Information Science
  • Low Resolution
  • Standards
  • Urban Areas

Fields of Study

  • Environmental science

Readers

  • Agricultural Chemistry/Soil Science
  • Atmospheric Science/Meteorology
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.

Technology Areas

  • Space