Journal article
Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data
- Abstract:
- Background. 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. Methodology/Principal Findings. 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 data for the period from 2001 to 2005. Conclusions/Significance. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multitemporal data sets, mean that these data may be used with greater confidence in species’ distribution modelling.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Publisher copy:
- 10.1371/journal.pone.0001408
Authors
+ "BBSRC/DEFRA", "European Union"
More from this funder
- Funding agency for:
- Rogers, D
- Grant:
- "SE4104", "GOCE-2003-010284 EDEN"
+ "DEFRA", "United Nations", "European Union"
More from this funder
- Funding agency for:
- Wint, G
- Grant:
- "SE3229", "GOCE-2003-010284 EDEN"
- Publisher:
- Public Library of Science
- Journal:
- PLoS ONE More from this journal
- Volume:
- 3
- Issue:
- 1
- Article number:
- e1408
- Publication date:
- 2008-01-01
- Edition:
- Publisher's version
- DOI:
- EISSN:
-
1932-6203
- Language:
-
English
- Keywords:
- Subjects:
- UUID:
-
uuid:4e725ce4-6cfb-40fa-85f1-ba18328be56b
- Local pid:
-
ora:2821
- Deposit date:
-
2009-06-04
Terms of use
- Copyright holder:
- Scharlemann et al
- Copyright date:
- 2008
- Notes:
- Citation: Scharlemann, J. P. W. et al. (2008). 'Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data', PLoS ONE 3(1), e1408. [Available at http://www.plosone.org]. © 2008 Scharlemann et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Licence:
- CC Attribution (CC BY)
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