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Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data.

Authors
Volume
3
Issue
1
Identifiers
DOI: 10.1371/journal.pone.0001408
Keywords
  • Ecology
  • Algorithms
  • Epidemiology
  • Fourier Analysis

Abstract

Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics.

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