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

Scharlemann JP, Benz D, Hay SI, Purse BV, Tatem AJ, Wint GR, Rogers DJ - PLoS ONE (2008)

Bottom Line: 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.The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling.

View Article: PubMed Central - PubMed

Affiliation: Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, United Kingdom.

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 multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling.

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Related in: MedlinePlus

Selection of MODIS Enhanced Vegetation Index (EVI) temporal Fourier-processed output layers.Panels show: (a) mean, (b) the percentage of missing values in the time series and (c) the proportion of variance in the original time series described by annual, bi-annual, and tri-annual cycles combined. Amplitude of the (d) annual, (e) bi-annual, and (f) tri-annual cycle are shown in addition to the phase of the (g) annual , (h) bi-annual, and (i) tri-annual cycle in months. Data are histogram-equalized for display from minimum (black) to maximum value (white). A coastline was added to (b) to show the missing values (white) more clearly. Data are displayed in the MODIS sinusoidal projection.
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pone-0001408-g006: Selection of MODIS Enhanced Vegetation Index (EVI) temporal Fourier-processed output layers.Panels show: (a) mean, (b) the percentage of missing values in the time series and (c) the proportion of variance in the original time series described by annual, bi-annual, and tri-annual cycles combined. Amplitude of the (d) annual, (e) bi-annual, and (f) tri-annual cycle are shown in addition to the phase of the (g) annual , (h) bi-annual, and (i) tri-annual cycle in months. Data are histogram-equalized for display from minimum (black) to maximum value (white). A coastline was added to (b) to show the missing values (white) more clearly. Data are displayed in the MODIS sinusoidal projection.

Mentions: To gain a more regional view, as well as display all Fourier harmonics, Figure 6 provides a selection of the 17 output layers for EVI across Africa. Specifications for all output layers for all products are given in Table S2.


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

Scharlemann JP, Benz D, Hay SI, Purse BV, Tatem AJ, Wint GR, Rogers DJ - PLoS ONE (2008)

Selection of MODIS Enhanced Vegetation Index (EVI) temporal Fourier-processed output layers.Panels show: (a) mean, (b) the percentage of missing values in the time series and (c) the proportion of variance in the original time series described by annual, bi-annual, and tri-annual cycles combined. Amplitude of the (d) annual, (e) bi-annual, and (f) tri-annual cycle are shown in addition to the phase of the (g) annual , (h) bi-annual, and (i) tri-annual cycle in months. Data are histogram-equalized for display from minimum (black) to maximum value (white). A coastline was added to (b) to show the missing values (white) more clearly. Data are displayed in the MODIS sinusoidal projection.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2171368&req=5

pone-0001408-g006: Selection of MODIS Enhanced Vegetation Index (EVI) temporal Fourier-processed output layers.Panels show: (a) mean, (b) the percentage of missing values in the time series and (c) the proportion of variance in the original time series described by annual, bi-annual, and tri-annual cycles combined. Amplitude of the (d) annual, (e) bi-annual, and (f) tri-annual cycle are shown in addition to the phase of the (g) annual , (h) bi-annual, and (i) tri-annual cycle in months. Data are histogram-equalized for display from minimum (black) to maximum value (white). A coastline was added to (b) to show the missing values (white) more clearly. Data are displayed in the MODIS sinusoidal projection.
Mentions: To gain a more regional view, as well as display all Fourier harmonics, Figure 6 provides a selection of the 17 output layers for EVI across Africa. Specifications for all output layers for all products are given in Table S2.

Bottom Line: 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.The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling.

View Article: PubMed Central - PubMed

Affiliation: Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, United Kingdom.

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 multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling.

Show MeSH
Related in: MedlinePlus