The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
(i.e., in 1 to 1 or n to 1 relation) during the period. It’s a very
reasonable assumption for forest type. However, it may not
work for cropland which may break our assumption because of
different crop calendar. For example, if two patches of bare soil
are similar in theASTER image but different in MODIS target
date (i.e., in 1 to n relation such as one grows vs. one not), this
model will not be able to capture different changes unless
additional information are introduced. Therefore, it is more
appropriate to use more informative leave-on images and
normalize it to a leaf-on or leaf-off MODIS target date.
5. ACKNOWLEDGEMENTS
This work was supported by the NASA EOS project and the
USGS LDCM science team project. Authors thank Dr.
Chengquan Huang for providing ASTER data for testing.
6. REFERENCE
Abrams, M., 2000. The Advanced Spacebome Thermal
Emission and Reflection Radiometer (ASTER): Data products
for the high spatial resolution imager on NASA's Terra platform.
International Journal of Remote Sensing, 21(5), pp. 847-859.
Gao, G., and Masek, J., 2008, Towards a consistent data set
from multiple mid-resolution satellite data using general
empirical relation model (GERM) and MODIS surface
reflectance product, Remote Sensing of Environment, submitted.
Masek, J. G., Vermote, E. F., Saleous, N. E., Wolfe, R., Hall, F.
G., Huemmrich, F., Gao, F., Kutler, J., & Lim, T. K., 2006. A
Landsat surface reflectance data set for North America, 1990-
2000. IEEE Geoscience and Remote Sensing Letters, 3, pp. 69-
72.
Powell, S. L., Pflugmacher, D., Kirschbaum, A. A., Kim, Y., &
Cohen W. B., 2007. Moderate resolution remote sensing
alternatives: a review of Landsat-like sensors and their
applications. Journal of Applied Remote Sensing, 1, 012506
[DOI: 10.1117/12.785479].
Vermote E. F., Saleous, N. El, & Justice, C., 2002. Atmospheric
correction of the MODIS data in the visible to middle infrared:
First results. Remote Sensing of Environment, 83, pp. 97-111
Wulder, M.A., J.C. White, S.N. Goward, J.G. Masek, J.R. Irons,
M. Herold, W.B. Cohen, T.R. Loveland, & C.E. Woodcock,
2008. Large area land cover monitoring: Issues and
opportunities related to Landsat continuity. Remote Sensing of
Environment, in press.
Figure 1. Processing flow chart of the improved GERM approach. Solid lines and rectangles show the design of original GERM
approach. Dashed lines and rectangles shows the improvements.
Spectral Bandwidth (p)
Ground Resolution
Swath W idth/Repeat
ASTER
ETM+
MODIS
ASTER
ETM+
ASTER
ETM+
Bl: 0.45-0.52
B3: 0.459-0.479
30 m
60 km
/16 days
185 km
/16 days
Bl: 0.52-0.60
B2: 0.52-0.60
B4: 0.545-0.565
15 m
B2: 0.63-0.69
B3: 0.63-0.69
Bl: 0.620-0.670
B3: 0.76-0.86
B4: 0.76-0.90
B2: 0.841-0.876
B4: 1.60-1.70
B5: 1.55-1.75
B6: 1.628-1.652
30m
B5: 2.145-2.185
B7: 2.09-2.35
B7: 2.105-2.155
B6: 2.185-2.225
B7: 2.235-2.285
B8: 2.295-2.365
B13: 10.25-10.95
B6: 10.4-12.5
B31: 10.78-11.28
90 m
60 m
B14: 10.95-11.65
B32: 11.77-12.27
Table 1. Sensor characteristics among ASTER (black), ETM+ (blue) and MODIS (green)
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