000060629 001__ 60629
000060629 005__ 20180531095509.0
000060629 0247_ $$2doi$$a10.3390/rs6076136
000060629 0248_ $$2sideral$$a87049
000060629 037__ $$aART-2014-87049
000060629 041__ $$aeng
000060629 100__ $$0(orcid)0000-0001-5025-5691$$aVlassova, L.
000060629 245__ $$aAnalysis of the relationship between land surface temperature and wildfire severity in a series of landsat images
000060629 260__ $$c2014
000060629 5060_ $$aAccess copy available to the general public$$fUnrestricted
000060629 5203_ $$aThe paper assesses spatio-temporal patterns of land surface temperature (LST) and fire severity in the Las Hurdes wildfire of Pinus pinaster forest, which occurred in July 2009, in Extremadura (Spain), from a time series of fifteen Landsat 5 TM images corresponding to 27 post-fire months. The differenced Normalized Burn Ratio (dNBR) was used to evaluate burn severity. The mono-window algorithm was applied to estimate LST from the Landsat thermal band. The burned zones underwent a significant increase in LST after fire. Statistically significant differences have been detected between the LST within regions of burn severity categories. More substantial changes in LST are observed in zones of greater fire severity, which can be explained by the lower emissivity of combustion products found in the burned area and changes in the energy balance related to vegetation removal. As time progresses over the 27 months after fire, LST differences decrease due to vegetation regeneration. The differences in LST and Normalized Difference Vegetation Index (NDVI) values between burn severity categories in each image are highly correlated (r = 0.84). Spatial patterns of severity and post-fire LST obtained from Landsat time series enable an evaluation of the relationship between these variables to predict the natural dynamics of burned areas.
000060629 536__ $$9info:eu-repo/grantAgreement/ES/DGA-CAIXA/GA-LC-042-2011$$9info:eu-repo/grantAgreement/ES/MINECO/CGL2012-34383
000060629 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000060629 590__ $$a3.18$$b2014
000060629 591__ $$aREMOTE SENSING$$b5 / 28 = 0.179$$c2014$$dQ1$$eT1
000060629 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000060629 700__ $$0(orcid)0000-0003-4831-4060$$aPérez-Cabello, F.$$uUniversidad de Zaragoza
000060629 700__ $$0(orcid)0000-0002-0477-0796$$aMimbrero, M.R.$$uUniversidad de Zaragoza
000060629 700__ $$0(orcid)0000-0001-7403-1764$$aLlovería, R.M.$$uUniversidad de Zaragoza
000060629 700__ $$0(orcid)0000-0003-2610-7749$$aGarcía-Martín, A.
000060629 7102_ $$13006$$2010$$aUniversidad de Zaragoza$$bDepartamento de Geografía y Ordenación del Territorio$$cAnálisis Geográfico Regional
000060629 773__ $$g6, 7 (2014), 6136-6162$$pRemote sens. (Basel)$$tRemote sensing (Basel)$$x2072-4292
000060629 8564_ $$s3027372$$uhttp://zaguan.unizar.es/record/60629/files/texto_completo.pdf$$yVersión publicada
000060629 8564_ $$s103904$$uhttp://zaguan.unizar.es/record/60629/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000060629 909CO $$ooai:zaguan.unizar.es:60629$$particulos$$pdriver
000060629 951__ $$a2018-05-31-09:48:48
000060629 980__ $$aARTICLE