{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T18:35:36Z","timestamp":1772822136518,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,12,11]],"date-time":"2019-12-11T00:00:00Z","timestamp":1576022400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>A comprehensive fire risk assessment is very important in dense urban areas as it provides an estimation of people at risk and property. Fire policy and mitigation strategies in developing countries are constrained by inadequate information, which is mainly due to a lack of capacity and resources for data collection, analysis, and modeling. In this research, we calculated the fire risk considering two aspects, urban infrastructure and the characteristics of a high-rise building for a dense urban area in Zanjan city. Since the resources for this purpose were rather limited, a variety of information was gathered and information fusion techniques were conducted by employing spatial analyses to produce fire risk maps. For this purpose, the spatial information produced using unmanned aerial vehicles (UAVs) and then attribute data (about 150 characteristics of each high-rise building) were gathered for each building. Finally, considering high-risk urban infrastructures, like the position of oil and gas pipes and electricity lines and the fire safety analysis of high-rise buildings, the vulnerability map for the area was prepared. The fire risk of each building was assessed and its risk level was identified. Results can help decision-makers, urban planners, emergency managers, and community organizations to plan for providing facilities and minimizing fire hazards and solve some related problems to reduce the fire risk. Moreover, the results of sensitivity analysis (SA) indicate that the social training factor is the most effective causative factor in the fire risk.<\/jats:p>","DOI":"10.3390\/ijgi8120579","type":"journal-article","created":{"date-parts":[[2019,12,12]],"date-time":"2019-12-12T03:20:16Z","timestamp":1576120816000},"page":"579","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":58,"title":["Fire Risk Assessment in Dense Urban Areas Using Information Fusion Techniques"],"prefix":"10.3390","volume":"8","author":[{"given":"Zohreh","family":"Masoumi","sequence":"first","affiliation":[{"name":"Department of Earth Sciences, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran"}]},{"given":"John","family":"van L.Genderen","sequence":"additional","affiliation":[{"name":"Department of Earth Observation Science, Faculty of Geoinformation Science and Earth Observation (ITC), University of Twente, 217,7500 Enschede, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7631-8670","authenticated-orcid":false,"given":"Jamshid","family":"Maleki","sequence":"additional","affiliation":[{"name":"Department of Geomatics Engineering, Faculty of Civil Engineering and Transportation, University of Isfahan, Isfahan 8174673441, Iran"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Twigg, J., Christie, N., Haworth, J., Osuteye, E., and Skarlatidou, A. 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