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Tan, B, Woodcock, CE, Hu, J, Zhang, P, Ozdogan, M, Huang, D, Yang, W, Knyazikhin, Y, Myneni, RB (2006). "The impact of gridding artifacts on the local spatial properties of MODIS data: Implications for validation, compositing, and band-to-band registration across resolutions". REMOTE SENSING OF ENVIRONMENT, 105(2), 98-114.

Abstract
Gridding artifacts between observations and predefined grid cells strongly influence the local spatial properties of MODIS images. The sensor observation in any grid cell is only partially derived from the location of the cell, with the average overlap between observations and their grid cells being less than 30%. This mismatch between grid cells and observations has strong implications for the use of reference data for the validation of MODIS products or the training of MODIS algorithms. When generating multidate composites, gridding artifacts introduce bias when spectral compositing criteria are used. Also, results indicate that the ability to generate consistent long-term remote sensing records is dependent on both consistent sensing scenarios (spectral bands, view angle distributions, geolocation error) as well as consistent compositing approaches. The band-to-band registration for the different spatial resolutions of gridded MODIS data can be poor if the different resolutions of data are gridded before aggregation. In all cases it is imprecise to characterize the subpixel properties of the coarser resolution bands using the finer resolution bands due to poor correspondence in the areas from which the observations are derived. All of the band-to-band registration problems are minimized when the MODIS data are aggregated to coarser resolutions. When validating algorithm accuracy, available data on the observation dimensions and the offsets between the grid cell and the observation should be included to ensure the quality of validation results. If this information is not available, MODIS data should be aggregated to coarser resolutions to improve the correspondence between the location of observations and grid cells. (c) 2006 Elsevier Inc. All rights reserved.

DOI:
10.1016/j.rse.2006.06.008

ISSN:
0034-4257

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