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

PloS One
Jörn P W ScharlemannDavid J Rogers

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. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS dat...Continue Reading

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Citations

Apr 24, 2014·PloS One·Guillaume Chabot-CouturePhilip Eckhoff
May 31, 2014·PloS One·Timothy P RobinsonMarius Gilbert
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Software Mentioned

TFA
MODLAND
IDRISI Andes
QuickBASIC
IDRISI
ERDAS Imagine
ArcInfo

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