J
Jordi Cristóbal
Researcher at University of Alaska Fairbanks
Publications - 42
Citations - 2017
Jordi Cristóbal is an academic researcher from University of Alaska Fairbanks. The author has contributed to research in topics: Water cycle & Vegetation. The author has an hindex of 14, co-authored 40 publications receiving 1621 citations. Previous affiliations of Jordi Cristóbal include University of Barcelona & Autonomous University of Barcelona.
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Journal ArticleDOI
Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data
TL;DR: This letter proposes SC and SW algorithms to be applied to Landsat-8 TIRS data for LST retrieval, and results show slightly better results for the SW algorithm than for the SC algorithm with increasing atmospheric water vapor contents.
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Revision of the Single-Channel Algorithm for Land Surface Temperature Retrieval From Landsat Thermal-Infrared Data
Juan C. Jiménez-Muñoz,Jordi Cristóbal,José A. Sobrino,Guillem Soria,Miquel Ninyerola,Xavier Pons +5 more
TL;DR: The generalized single-channel (SC) algorithm developed by Jimenez-Munoz and Sobrino (2003) is extended to the thermal-infrared channel of the TM sensor onboard the Landsat-4 platform and the enhanced TM plus sensor onboard Thematic Mapper (TM) sensor, and updated fits using MODTRAN 4 radiative transfer code are presented.
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Improvements in land surface temperature retrieval from the Landsat series thermal band using water vapor and air temperature
TL;DR: In this article, the authors presented an improved methodology to retrieve LST from Landsat 4 TM, Landsat 5 TM, and Landsat 7 ETM+ using four atmospheric databases covering different water vapor ranges (from 0 to 8 g cm−2) and using both water vapor and air temperature as input variables.
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Modeling air temperature through a combination of remote sensing and GIS data
TL;DR: In this paper, a hybrid methodology between Remote Sensing and Geographical Information Systems is presented to retrieve daily instantaneous, mean, maximum and minimum air temperatures (2002-2004) as well as monthly and annual mean, maxima and minima air temperature (2000-2005) on a regional scale (Catalonia, northeast of the Iberian Peninsula).
Journal ArticleDOI
Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity
Jaime Paneque-Gálvez,Jaime Paneque-Gálvez,Jean-François Mas,G. Moré,Jordi Cristóbal,Martí Orta-Martínez,Ana Catarina Luz,Maximilien Guèze,Manuel J. Macía,Victoria Reyes-García +9 more
TL;DR: The homogeneity index, which has so far been neglected in land use/cover classification efforts, is focused on, and it is found that this index along with reflectance bands significantly increased the overall accuracy of all the classifiers, but particularly of SVM.