{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T18:22:53Z","timestamp":1732040573242},"reference-count":65,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,6,4]],"date-time":"2021-06-04T00:00:00Z","timestamp":1622764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["ICER-1664175"],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000104","name":"National Aeronautics and Space Administration","doi-asserted-by":"publisher","award":["80NSSC19K1091"],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Producing high-resolution near-real-time forecasts of fire behavior and smoke impact that are useful for fire and air quality management requires accurate initialization of the fire location. One common representation of the fire progression is through the fire arrival time, which defines the time that the fire arrives at a given location. Estimating the fire arrival time is critical for initializing the fire location within coupled fire-atmosphere models. We present a new method that utilizes machine learning to estimate the fire arrival time from satellite data in the form of burning\/not burning\/no data rasters. The proposed method, based on a support vector machine (SVM), is tested on the 10 largest California wildfires of the 2020 fire season, and evaluated using independent observed data from airborne infrared (IR) fire perimeters. The SVM method results indicate a good agreement with airborne fire observations in terms of the fire growth and a spatial representation of the fire extent. A 12% burned area absolute percentage error, a 5% total burned area mean percentage error, a 0.21 False Alarm Ratio average, a 0.86 Probability of Detection average, and a 0.82 S\u00f8rensen\u2019s coefficient average suggest that this method can be used to monitor wildfires in near-real-time and provide accurate fire arrival times for improving fire modeling even in the absence of IR fire perimeters.<\/jats:p>","DOI":"10.3390\/rs13112203","type":"journal-article","created":{"date-parts":[[2021,6,7]],"date-time":"2021-06-07T05:56:40Z","timestamp":1623045400000},"page":"2203","source":"Crossref","is-referenced-by-count":16,"title":["Machine Learning Estimation of Fire Arrival Time from Level-2 Active Fires Satellite Data"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-2395-220X","authenticated-orcid":false,"given":"Angel","family":"Farguell","sequence":"first","affiliation":[{"name":"Wildfire Interdisciplinary Research Center, San Jose State University, San Jose, CA 95192, USA"},{"name":"Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-8489-5766","authenticated-orcid":false,"given":"Jan","family":"Mandel","sequence":"additional","affiliation":[{"name":"Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA"}]},{"given":"James","family":"Haley","sequence":"additional","affiliation":[{"name":"Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA"}]},{"given":"Derek V.","family":"Mallia","sequence":"additional","affiliation":[{"name":"Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT 84112, USA"}]},{"given":"Adam","family":"Kochanski","sequence":"additional","affiliation":[{"name":"Wildfire Interdisciplinary Research Center, San Jose State University, San Jose, CA 95192, USA"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-2078-9884","authenticated-orcid":false,"given":"Kyle","family":"Hilburn","sequence":"additional","affiliation":[{"name":"Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80521, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"940","DOI":"10.1126\/science.1128834","article-title":"Warming and Earlier Spring Increase Western U.S. Forest Wildfire Activity","volume":"313","author":"Westerling","year":"2006","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1016\/j.foreco.2009.09.002","article-title":"Trends in global wildfire potential in a changing climate","volume":"259","author":"Liu","year":"2010","journal-title":"For. 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