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. 2008 Apr 8;8(4):2480-2499.
doi: 10.3390/s8042480.

Inter-Comparison of ASTER and MODIS Surface Reflectance and Vegetation Index Products for Synergistic Applications to Natural Resource Monitoring

Tomoaki Miura  1 , Hiroki Yoshioka  2 , Kayo Fujiwara  3 , Hirokazu Yamamoto  4
Affiliations

Inter-Comparison of ASTER and MODIS Surface Reflectance and Vegetation Index Products for Synergistic Applications to Natural Resource Monitoring

Tomoaki Miura et al. Sensors (Basel). .

Abstract

Synergistic applications of multi-resolution satellite data have been of a great interest among user communities for the development of an improved and more effective operational monitoring system of natural resources, including vegetation and soil. In this study, we conducted an inter-comparison of two remote sensing products, namely, visible/near-infrared surface reflectances and spectral vegetation indices (VIs), from the high resolution Advanced Thermal Emission and Reflection Radiometer (ASTER) (15 m) and lower resolution Moderate Resolution Imaging Spectroradiometer (MODIS) (250 m - 500 m) sensors onboard the Terra platform. Our analysis was aimed at understanding the degree of radiometric compatibility between the two sensors' products due to sensor spectral bandpasses and product generation algorithms. Multiple pairs of ASTER and MODIS standard surface reflectance products were obtained at randomly-selected, globally-distributed locations, from which two types of VIs were computed: the normalized difference vegetation index and the enhanced vegetation indices with and without a blue band. Our results showed that these surface reflectance products and the derived VIs compared well between the two sensors at a global scale, but subject to systematic differences, of which magnitudes varied among scene pairs. An independent assessment of the accuracy of ASTER and MODIS standard products, in which "in-house" surface reflectances were obtained using in situ Aeronet atmospheric data for comparison, suggested that the performance of the ASTER atmospheric correction algorithm may be variable, reducing overall quality of its standard reflectance product. Atmospheric aerosols, which were not corrected for in the ASTER algorithm, were found not to impact the quality of the derived reflectances. Further investigation is needed to identify the sources of inconsistent atmospheric correction results associated with the ASTER algorithm, including additional quality assessments of the ASTER and MODIS products with other atmospheric radiative transfer codes.

Keywords: ASTER; MODIS; product inter-comparison; surface reflectance; vegetation index.

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Figures

Figure 1.
Figure 1.
Normalized spectral response curves of ASTER VNIR (1, 2, and 3N) and MODIS land (1, 2, 3, and 4) bands (sources: http://asterweb.jpl.nasa.gov/characteristics.asp & ftp://ftp.mcst.ssai.biz/pub/permanent/MCST/PFM_L1B_LUT_4-30-99/). The “A” and “M” in the parentheses stand for ASTER and MODIS, respectively, and the numbers that follow A or M are the band numbers. Typical reflectance spectra of forest, grassland, and bare soil are also plotted for reference [27].
Figure 2.
Figure 2.
Global distribution of ASTER vs. MODIS comparative analysis locations.
Figure 3.
Figure 3.
Scatterplots of ASTER vs. MODIS surface reflectance and vegetation indices: (a) red reflectance, (b) NIR reflectance, (c) NDVI, and (d) EVI2 vs. EVI. MDs in the plots stand for mean differences and the values in the parentheses were standard deviations of the differences.
Figure 4.
Figure 4.
Differences of ASTER and MODIS reflectances and vegetation indices (AST07 minus MOD09) plotted against MODIS values.
Figure 5.
Figure 5.
Land cover dependencies of ASTER vs. MODIS differences (AST07 minus MOD09). Per-land cover mean differences are plotted along with 99 % confidence intervals. The sample sizes (number of pairs) used to compute the mean differences and confidence intervals are given at the tops of the bars in (a).
Figure 6.
Figure 6.
Temporal variability in ASTER (AST07) and MODIS (MOD09) radiometric variables and their differences: (a) red reflectance, (b) NIR reflectance, (c) NDVI, and (d) EVI2 (ASTER) and EVI (MODIS). The bars in the figure correspond to the standard deviation estimates. The sample size was 134 for every scene pair.
Figure 7.
Figure 7.
Scatterplots of AST07 vs. atmospherically-corrected ASTER data using in situ Aeronet data for (a) green, (b) red, and (c) NIR reflectances, and (d) NDVI and (e) EVI2. These “in-house” atmospheric corrections of ASTER data were performed by setting aerosol optical thickness to zero, simulating the actual ASTER atmospheric correction scenario.
Figure 8.
Figure 8.
Scatterplots of atmospherically-corrected ASTER data using in situ Aeronet data: no aerosol correction vs. aerosol correction.
Figure 9.
Figure 9.
Scatterplots of MOD09 vs. atmospherically-corrected MODIS data using in situ Aeronet data for (a) green, (b) red, and (c) NIR reflectances, and (d) NDVI and (e) EVI.
Figure 10.
Figure 10.
Comparisons of mean differences between official and in-house products: (a) AST07 vs. in-house ASTER, (b) MOD09 vs. in-house MODIS, and (c) ASTER no aerosol vs. aerosol corrections. The error bars in the figure correspond to 99% confidence intervals. The sample size was 140.
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References

    1. McRoberts R.E., Tomppo E.O. Remote sensing support for national forest inventories. Remote Sens. Environ. 2007;110(4):412–419.
    1. Marsett R.C., Qi J.G., Heilman P., Biedenbender S.H., Watson M.C., Amer S., Weltz M., Goodrich D., Marsett R. Remote sensing for grassland management in the arid Southwest. Rangeland Ecol. Manage. 2006;59(5):530–540.
    1. Morton D.C., DeFries R.S., Shimabukuro Y.E., Anderson L.O., Espirito-Santo F.D.B., Hansen M., Carroll M. Rapid assessment of annual deforestaion in the Brazilian Amazon using MODIS data. Earth Interact. 2005;9(8) doi: 10.1175/EI139.1. - DOI
    1. Morisette J.T., Jarnevich C.S., Ullah A., Cai W.J., Pedelty J.A., Gentle J.E., Stohlgren T.J., Schnase J.L. A tamarisk habitat suitability map for the continental United States. Front. Ecol. Environ. 2006;4(1):11–17.
    1. Hill M.J., Held A.A., Leuning R., Coops N.C., Hughes D., Cleugh H.A. MODIS spectral signals at a flux tower site: Relationships with high-resolution data, and CO2 flux and light use efficiency measurements. Remote Sens. Environ. 2006;103(3):351–368.

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