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dc.contributor.authorValero Pérez, Mario Miguel
dc.contributor.authorJimenez, Daniel
dc.contributor.authorButler, Bret W.
dc.contributor.authorMata Miquel, Cristian
dc.contributor.authorRios Rubiras, Oriol
dc.contributor.authorPastor Ferrer, Elsa
dc.contributor.authorPlanas Cuchi, Eulàlia
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Química
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2018-11-28T09:14:12Z
dc.date.issued2018
dc.identifier.citationValero, M., Jimenez, D., Butler, B., Mata, C., Rios, O., Pastor, E., Planas, E. On the use of compact thermal cameras for quantitative wildfire monitoring. A: International Conference on Forest Fire Research. "Advances in Forest Fire Research 2018". 2018, p. 1077-1086.
dc.identifier.isbn978-989-26-16-506
dc.identifier.urihttp://hdl.handle.net/2117/125160
dc.description.abstractIn recent times, there have been significant developments in remote sensing techniques applied to forest fire research. In particular, infrared (IR) imagery has proved effective to measure variables such as rate of spread, fire radiative power and Byram’s intensity. Remote sensing methodologies prov ide spatially explicit data in a cost - effective manner and reduce the need for intensive surveying campaigns. Concurrently, IR technology has seen remarkable maturing and thermal cameras have become increasingly light, compact and affordable. New models we igh only a few hundreds of grams, they have the size of a phone and they can be easily installed aboard remotely piloted aircraft (RPAS). Whereas these advances may be the base for powerful quantitative fire monitoring systems, there are some practical iss ues that need to be addressed before the full potential of this technology can be achieved. In this paper, we present our experience with two modern compact thermal cameras, and we explain how we overcame the difficulties we found. Two medium - scale experim ental burns were recorded and computer vision algorithms were used to track the fire perimeter and measure its rate of spread (ROS). For performance reasons, one of the cameras encapsulated raw radiometric information in binary files with a non - standard pr oprietary video format. Adequate processing of this format was required to obtain brightness temperature distributions with a high temporal resolution (27 frames per second). On the other hand, the second camera stored IR frames as JPEG images with no radi ometric information and with a low temporal resolution (approximately 1 frame per second, not constant). Additionally, this camera was operated from a small drone and significant jitter was present in the recorded video. To make data from the second camera usable, we applied video stabilization algorithms and we retrieved the exact time of acquisition of each frame from the metadata saved with each image. Ultimately, pre - processed IR data from both cameras was successfully used to detect the fire front, tra ck the fire perimeter and compute rates of spread. All these tasks were performed automatically. Still, human interaction was required to georeference the imagery using ground control points. Georeferencing aerial imagery automatically remains one of the m ain challenges for the achievement of a fully automated fire monitoring system. Nevertheless, results obtained here were satisfactory. The algorithms for fire front detection, fire perimeter tracking and ROS estimation worked successfully, even when availa ble data had significant limitations. The information retrieved from IR imagery through these algorithms can be further combined with other remote sensing products that provide details about fuel, weather and terrain. Moreover, observed data may be used to adjust data - driven fire spread simulators in real time so that they can produce accurate forecasts about the fire evolution, at least in the short term. These technological developments make important contributions towards the accomplishment of affordable , yet reliable, operational decision - support systems (DSS) that can be deployed during an emergency
dc.format.extent10 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria química
dc.subject.lcshForest fires
dc.subject.lcshImage processing
dc.subject.otherDecision Support Systems
dc.subject.otherFire Monitoring
dc.subject.otherFire Segmentation
dc.subject.otherRemote Sensing
dc.subject.otherThermal Infrared Cameras
dc.subject.otherUnmanned Aerial Vehicles
dc.titleOn the use of compact thermal cameras for quantitative wildfire monitoring
dc.typeConference report
dc.subject.lemacIncendis forestals
dc.subject.lemacImatges -- Processament
dc.contributor.groupUniversitat Politècnica de Catalunya. CERTEC - Centre d'Estudis del Risc Tecnològic
dc.identifier.doi10.14195/978-989-26-16-506_119
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://digitalis.uc.pt/en/livro/use_compact_thermal_cameras_quantitative_wildfire_monitoring
dc.rights.accessRestricted access - publisher's policy
drac.iddocument23529306
dc.description.versionPostprint (author's final draft)
dc.date.lift10000-01-01
upcommons.citation.authorValero, M., Jimenez, D., Butler, B., Mata, C., Rios, O., Pastor, E., Planas, E.
upcommons.citation.contributorInternational Conference on Forest Fire Research
upcommons.citation.publishedtrue
upcommons.citation.publicationNameAdvances in Forest Fire Research 2018
upcommons.citation.startingPage1077
upcommons.citation.endingPage1086


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