On the interest of the spectral bands in the automatic selection of high quality MODIS data through spatial pattern identification

Domingo-Marimon, C., Pesquer, L., Gómez-Carbajo, N., Jiménez-Díaz, M.-T., Pons, X. (2017) On the interest of the spectral bands in the automatic selection of high quality MODIS data through spatial pattern identification. Proceedings of SPIE - The International Society for Optical Engineering. 10427: 0-0.
Link
Doi: 10.1117/12.2278596

Abstract:

Radiometric correction of simultaneously acquired Landsat-7/Landsat-8 and Sentinel-2A imagery using Pseudoinvariant Areas (PIA): Contributing to the Landsat time series legacy

Padró, J.-C., Pons, X., Aragonés, D., Díaz-Delgado, R., García, D., Bustamante, J., Pesquer, L., Domingo-Marimon, C., González-Guerrero, Ò., Cristóbal, J., Doktor, D., Lange, M. (2017) Radiometric correction of simultaneously acquired Landsat-7/Landsat-8 and Sentinel-2A imagery using Pseudoinvariant Areas (PIA): Contributing to the Landsat time series legacy. Remote Sensing. 9: 0-0.
Link
Doi: 10.3390/rs9121319

Abstract:

A geostatistical approach for selecting the highest quality MODIS daily images

Pesquer L., Domingo C., Pons X. (2013) A geostatistical approach for selecting the highest quality MODIS daily images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7887 LNCS: 608-615.
Link
Doi: 10.1007/978-3-642-38628-2_72

Abstract:

The aim of this work was to develop a new methodology for automatic selection of the highest quality MODIS daily images, MOD09GA Surface Reflectance product. The methodology developed here complements the quality assessment of MODIS products with a geostatistical analysis of spatial pattern images based on variogram tools. The resulting selection is formed by 26 high-quality images (from an initial dataset of 365) from throughout 2007. Most images with geometric distortion problems, such as the bow-tie effect, were rejected. The automatic selection was validated by comparing it to manual selection, which showed that it achieved an overall accuracy of 71.4%. © 2013 Springer-Verlag.

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