000166113 001__ 166113
000166113 005__ 20260120151004.0
000166113 0247_ $$2doi$$a10.1117/1.JRS.19.044514
000166113 0248_ $$2sideral$$a147462
000166113 037__ $$aART-2025-147462
000166113 041__ $$aeng
000166113 100__ $$0(orcid)0000-0003-2610-7749$$aGarcía-Martín, Alberto$$uUniversidad de Zaragoza
000166113 245__ $$aFuel type mapping with X-band SAR in military training areas for wildfire risk assessment
000166113 260__ $$c2025
000166113 5060_ $$aAccess copy available to the general public$$fUnrestricted
000166113 5203_ $$aIntense firing activities at Spanish Army Training Centers create a significant wildfire risk, requiring the implementation of a specific Plan Against Forest Fires and an Operational Action Protocol, both of which rely on accurate fuel type (FT) maps. We evaluate the usefulness of the backscattering coefficient provided by PAZ, the X-band SAR Spanish Ministry of Defense’s first Earth observation satellite, for FT mapping to support wildfire management in the “San Gregorio” Training Center (Zaragoza, Spain). The methodology involved three phases: (i) processing satellite images from the first PAZ Announcement of Opportunity (AO-001); (ii) delineating field plots for correlation with satellite imagery; and (iii) classifying FTs using multinomial logistic regression. Results indicate that PAZ images are effective for discriminating among the main FTs (grassland, shrubland, and woodland), achieving an overall accuracy of 82.1%. However, they are not suitable for the detailed mapping of the Prometheus fuel categories, with an overall accuracy of 42.9%, primarily due to the limited penetration capabilities of the X-band.
000166113 536__ $$9info:eu-repo/grantAgreement/ES/DGA/S51-23R$$9info:eu-repo/grantAgreement/ES/MCIN-AEI/PID2020-118886RB-I00-AEI-10.13039-501100011033
000166113 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000166113 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000166113 700__ $$aDomingo, Darío
000166113 700__ $$0(orcid)0000-0002-8954-7517$$aLamelas, María Teresa$$uUniversidad de Zaragoza
000166113 700__ $$ade la Riva, Juan
000166113 700__ $$aEscribano, Francisco
000166113 700__ $$0(orcid)0000-0001-6288-2780$$aMontealegre, Antonio Luis$$uUniversidad de Zaragoza
000166113 700__ $$0(orcid)0000-0001-7403-1764$$aMontorio, Raquel$$uUniversidad de Zaragoza
000166113 700__ $$0(orcid)0000-0003-4831-4060$$aPérez-Cabello, Fernando$$uUniversidad de Zaragoza
000166113 7102_ $$13006$$2010$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Análisis Geográfico Regi.
000166113 773__ $$g19, 4 (2025), 044514$$pJournal of Applied Remote Sensing$$tJournal of Applied Remote Sensing$$x1931-3195
000166113 8564_ $$s1176252$$uhttps://zaguan.unizar.es/record/166113/files/texto_completo.pdf$$yPostprint
000166113 8564_ $$s1548491$$uhttps://zaguan.unizar.es/record/166113/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000166113 909CO $$ooai:zaguan.unizar.es:166113$$particulos$$pdriver
000166113 951__ $$a2026-01-20-14:17:54
000166113 980__ $$aARTICLE