The impact of size variations in the ground instantaneous field of view of pixels on MODIS BRDF modelling |
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| Institution: | 1. School of Mathematics and Geospatial Science, RMIT University, Melbourne, Australia;2. 13 Heathwood Street, Ringwood East Victoria 3135, Australia;1. School of Engineering and ICT, University of Tasmania, Australia;2. Remote Sensing Research Unit, Meraka Institute, CSIR, Pretoria, South Africa;1. School of Geographical Science, Northeast Normal University, Changchun, 130024, China;2. Air and Space Information Department, Air Force Aviation University, Changchun, 130022, China;1. Amazon Research Team, Department of Biology, University of Turku, FI-20014 Turku, Finland;2. Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA;1. Center for Advanced Land Management Information Technologies, School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE, USA;2. Department of Entomology, University of Nebraska-Lincoln, Lincoln, NE, USA;3. Department of Plant Pathology, University of Nebraska-Lincoln, Lincoln, NE, USA;4. Cooperative Institute of Mesoscale Meteorological Studies, University of Oklahoma, Norman, OK, USA;5. National Severe Storms Laboratory, National Oceanic and Atmospheric Administration, Norman, OK, USA |
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| Abstract: | Bidirectional reflectance distribution functions (BRDF) seek to represent surface reflectance anisotropy resulting from surface physical structure and changes in a satellite sensor’s view and solar illumination angles. NASA’s MODerate resolution imaging spectroradiometer (MODIS) is a wide field of view sensor that generates observations over a large range of view angles. Based on MODIS observations, a BRDF product and several sub-products have been developed by MODIS science teams, i.e. the MCD43 product suite. Variations in pixels’ ground instantaneous field of view (GIFOV), i.e. the size of a pixel’s footprint on the ground, is a well known effect associated with wide field of view sensors such as MODIS, but is not specifically considered in the MODIS BRDF algorithm nor has research been undertaken into its effects on MODIS BRDF modelling. This paper introduces two metrics to examine the relationship between reflectance variations associated with changes in MODIS pixels’ GIFOV and the MODIS BRDF (MCD43) product. These metrics are applied to four different study areas and epochs across the Australian continent. The two metrics are shown to be well correlated (mean correlation coefficient of 0.81 for the four study areas); suggesting that variations in pixels’ GIFOV are a consistent, non-random source of variance in MODIS BRDF modelling. The results contained in this paper suggest that all downstream products which include MODIS BRDF processing in their derivation and results directly based on MODIS BRDF processing may need to be reassessed. |
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| Keywords: | MODIS BRDF GIFOV MCD43 NDVI |
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