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New Regression Models for Prediction of Grain Yield Anomalies from Satellite-Based Vegetation Health Indices

  • Gennady MenzhulinEmail author
  • Natalya Shamshurina
  • Artyom Pavlovsky
  • Felix Kogan
Conference paper
Part of the NATO Science for Peace and Security Series C: Environmental Security book series (NAPSC)

Abstract

In the late 1970s, the first operational weather satellite system had been launched, which showed utility for monitoring land greenness, vigor and vegetation productivity. Currently, 30-year satellite data from the Advanced Very High Resolution Radiometer (AVHRR) are available for monitoring land surface, atmosphere near the ground, natural disasters, and socioeconomic activities. Statistical modeling of agricultural crop yield and production was one of the applications. This paper discusses the topic, how design the new regression ­models of yield anomaly based on multivariate algorithms and selection of ­best-fit ensemble of predictors.

Keywords

Crop yields anomaly Vegetation health indices Precipitation Temperature Models 

References

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Gennady Menzhulin
    • 1
    Email author
  • Natalya Shamshurina
    • 1
  • Artyom Pavlovsky
    • 1
  • Felix Kogan
    • 2
  1. 1.Research Center for Interdisciplinary Environmental CooperationRussian Academy of SciencesSt. PetersburgRussia
  2. 2.NOAA, NESDISWashingtonUSA

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