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.
Highlights
Numerous studies have demonstrated remote sensing as an effective tool for natural resource inventory/interpretation and environmental monitoring, including forest inventory, rangeland productivity monitoring, mapping deforestation dynamics, and alien species/weed invasion assessments, to name a few [1,2,3,4]
The ASTER Normalized Difference Vegetation Index (NDVI) was consistently lower than the Moderate Resolution Imaging Spectroradiometer (MODIS) counterpart (MD of -.031) (Figure 3c)
We investigated product inter-compatibility between ASTER and MODIS atmospherically-corrected reflectance products (AST07 and MOD09, respectively) and vegetation indices (VIs) computed from these standard reflectance products
Summary
Numerous studies have demonstrated remote sensing as an effective tool for natural resource inventory/interpretation and environmental monitoring, including forest inventory, rangeland productivity monitoring, mapping deforestation dynamics, and alien species/weed invasion assessments, to name a few [1,2,3,4]. Applications of synergistic, multi-resolution remote sensing have been shown to improve remote sensing-based land characterization and monitoring capabilities [5,6,7,8], offering great potential for the development of more effective operational monitoring and management decision support systems [9,10,11] This has further been facilitated by the advent of satellite programs such as the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) and European Remote Sensing (ERS) programs as these programs provide systems of coordinated satellite sensors and measurements [12]. ASTER and MODIS are onboard the same Terra platform, which is a significant advantage for their synergistic applications
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