Vidal-Macua, J.J., Ninyerola, M., Zabala, A., Domingo-Marimon, C., Gonzalez-Guerrero, O., Pons, X. (2018) Environmental and socioeconomic factors of abandonment of rainfed and irrigated crops in northeast Spain. Applied Geography. 90: 155-174.EnllaçDoi: 10.1016/j.apgeog.2017.12.005
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.EnllaçDoi: 10.1117/12.2278596
José Vidal-Macua, J., Ninyerola, M., Zabala, A., Domingo-Marimon, C., Pons, X. (2017) Factors affecting forest dynamics in the Iberian Peninsula from 1987 to 2012. The role of topography and drought. Forest Ecology and Management. 406: 290-306.EnllaçDoi: 10.1016/j.foreco.2017.10.011
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.EnllaçDoi: 10.3390/rs9121319
Carnicer, J., Wheat, C., Vives, M., Ubach, A., Domingo, C., Nylin, S., Stefanescu, C., Vila, R., Wiklund, C., Peñuelas, J. (2016) Evolutionary responses of invertebrates to global climate change: The role of life-history trade-offs and multidecadal climate shifts. Global Climate Change and Terrestrial Invertebrates. : 319-348.EnllaçDoi: 10.1002/9781119070894.ch16
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.EnllaçDoi: 10.1007/978-3-642-38628-2_72
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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