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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

Temporal Fourier analysis of global (a) daytime Land Surface Temperature (dLST) and (b) Enhanced Vegetation Index (EVI).The analyses were based on the period 2001–2005 using 230 images at 8-day intervals for dLST (a) and 115 images at 16-day intervals for EVI (b), both resampled at 5-day intervals after cubic spline interpolation. Data are displayed as three-channel colour composites with the mean, phase and amplitude of the annual harmonic in the red, green and blue channel, respectively. For display purposes, values in each band were stretched across the full range of intensities within the image processing system using histogram equalization. The insets show the 229 MODLAND tiles that were processed, indicating the number of missing granules in each. Data are displayed in MODIS sinusoidal projection.
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pone-0001408-g002: Temporal Fourier analysis of global (a) daytime Land Surface Temperature (dLST) and (b) Enhanced Vegetation Index (EVI).The analyses were based on the period 2001–2005 using 230 images at 8-day intervals for dLST (a) and 115 images at 16-day intervals for EVI (b), both resampled at 5-day intervals after cubic spline interpolation. Data are displayed as three-channel colour composites with the mean, phase and amplitude of the annual harmonic in the red, green and blue channel, respectively. For display purposes, values in each band were stretched across the full range of intensities within the image processing system using histogram equalization. The insets show the 229 MODLAND tiles that were processed, indicating the number of missing granules in each. Data are displayed in MODIS sinusoidal projection.

Mentions: 52144 granules were acquired for the MOD11A2 data set, and 25697 for MOD43B4, representing 99.0% and 99.3% of the potential granules respectively (note MOD43B4 data were not produced for 4 tiles north of 80°N). The median number of missing granules per tile was 2 (range 1–6 granules) for MOD11A2 and 0 (0–11) for MOD43B4 (insets in Figure 2). The larger number of missing granules in the MOD11A2 data set was due to a power supply anomaly in the sensor from 16 June to 1 July 2001, preventing data collection during one or two 8-day intervals (Julian day 169 and 177) for every tile. Several granules were missing during the winter months for tiles located at high latitudes, as there was insufficient sunlight to reflect back to the satellite. Other sensor problems and failed storage tapes at the data distribution centre accounted for further missing granules.


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)

Temporal Fourier analysis of global (a) daytime Land Surface Temperature (dLST) and (b) Enhanced Vegetation Index (EVI).The analyses were based on the period 2001–2005 using 230 images at 8-day intervals for dLST (a) and 115 images at 16-day intervals for EVI (b), both resampled at 5-day intervals after cubic spline interpolation. Data are displayed as three-channel colour composites with the mean, phase and amplitude of the annual harmonic in the red, green and blue channel, respectively. For display purposes, values in each band were stretched across the full range of intensities within the image processing system using histogram equalization. The insets show the 229 MODLAND tiles that were processed, indicating the number of missing granules in each. Data are displayed in MODIS sinusoidal projection.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0001408-g002: Temporal Fourier analysis of global (a) daytime Land Surface Temperature (dLST) and (b) Enhanced Vegetation Index (EVI).The analyses were based on the period 2001–2005 using 230 images at 8-day intervals for dLST (a) and 115 images at 16-day intervals for EVI (b), both resampled at 5-day intervals after cubic spline interpolation. Data are displayed as three-channel colour composites with the mean, phase and amplitude of the annual harmonic in the red, green and blue channel, respectively. For display purposes, values in each band were stretched across the full range of intensities within the image processing system using histogram equalization. The insets show the 229 MODLAND tiles that were processed, indicating the number of missing granules in each. Data are displayed in MODIS sinusoidal projection.
Mentions: 52144 granules were acquired for the MOD11A2 data set, and 25697 for MOD43B4, representing 99.0% and 99.3% of the potential granules respectively (note MOD43B4 data were not produced for 4 tiles north of 80°N). The median number of missing granules per tile was 2 (range 1–6 granules) for MOD11A2 and 0 (0–11) for MOD43B4 (insets in Figure 2). The larger number of missing granules in the MOD11A2 data set was due to a power supply anomaly in the sensor from 16 June to 1 July 2001, preventing data collection during one or two 8-day intervals (Julian day 169 and 177) for every tile. Several granules were missing during the winter months for tiles located at high latitudes, as there was insufficient sunlight to reflect back to the satellite. Other sensor problems and failed storage tapes at the data distribution centre accounted for further missing granules.

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