{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T02:28:34Z","timestamp":1773714514143,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T00:00:00Z","timestamp":1618963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100008419","name":"Bushfire Cooperative Research Centre","doi-asserted-by":"publisher","award":["Hotspots"],"award-info":[{"award-number":["Hotspots"]}],"id":[{"id":"10.13039\/100008419","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper introduces an enhanced version of the Biogeographical Region and Individual Geostationary HHMMSS Threshold (BRIGHT) algorithm. The algorithm runs in real-time and operates over 24 h to include both daytime and night-time detections. The algorithm was executed and tested on 12 months of Himawari-8 data from 1 April 2019 to 31 March 2020, for every valid 10-min observation. The resulting hotspots were compared to those from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). The modified BRIGHT hotspots matched with fire detections in VIIRS 96% and MODIS 95% of the time. The number of VIIRS and MODIS hotspots with matches in the coincident modified BRIGHT dataset was lower (at 33% and 46%, respectively). This paper demonstrates a clear link between the number of VIIRS and MODIS hotspots with matches and the minimum fire radiative power considered.<\/jats:p>","DOI":"10.3390\/rs13091627","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T21:25:10Z","timestamp":1619040310000},"page":"1627","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Real-Time Detection of Daytime and Night-Time Fire Hotspots from Geostationary Satellites"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2984-8959","authenticated-orcid":false,"given":"Chermelle B.","family":"Engel","sequence":"first","affiliation":[{"name":"STEM College, RMIT University, Melbourne, VIC 3000, Australia"},{"name":"Bushfire and Natural Hazards Cooperative Research Center, East Melbourne, VIC 3002, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3914-3717","authenticated-orcid":false,"given":"Simon D.","family":"Jones","sequence":"additional","affiliation":[{"name":"STEM College, RMIT University, Melbourne, VIC 3000, Australia"},{"name":"Bushfire and Natural Hazards Cooperative Research Center, East Melbourne, VIC 3002, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4333-2315","authenticated-orcid":false,"given":"Karin J.","family":"Reinke","sequence":"additional","affiliation":[{"name":"STEM College, RMIT University, Melbourne, VIC 3000, Australia"},{"name":"Bushfire and Natural Hazards Cooperative Research Center, East Melbourne, VIC 3002, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,21]]},"reference":[{"key":"ref_1","first-page":"1311","article-title":"Identification of subresolution high-temperature sources using a thermal ir sensor","volume":"47","author":"Matson","year":"1981","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1002\/qj.1986","article-title":"The meteorology of Black Saturday","volume":"139","author":"Engel","year":"2013","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1029\/2017MS001245","article-title":"Coupled Atmosphere-Fire Simulations of the Black Saturday Kilmore East Wildfires with the Unified Model","volume":"11","author":"Toivanen","year":"2019","journal-title":"J. Adv. Modeling Earth Syst."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1080\/01431169608949018","article-title":"A contextual algorithm for AVHRR fire detection","volume":"17","author":"Flasse","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_5","first-page":"563","article-title":"Global Fire Mapping and Fire Danger Estimation Using AVHRR Images","volume":"60","author":"Chuvieco","year":"1994","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"23851","DOI":"10.1029\/95JD00623","article-title":"Satellite remote sensing of fires during the SAFARI campaign using NOAA advanced very high resolution radiometer data","volume":"101","author":"Justice","year":"1996","journal-title":"J. Geophys. Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2235","DOI":"10.1080\/01431169408954240","article-title":"An improved approach to fire monitoring in West Africa using AVHRR data","volume":"15","author":"Kennedy","year":"1994","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1279","DOI":"10.1080\/014311600210173","article-title":"The Global Fire Product: Daily fire occurrence from April 1992 to December 1993 derived from NOAA AVHRR data","volume":"21","author":"Stropianna","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.1175\/BAMS-D-12-00097.1","article-title":"First-Light Imagery from Suomi NPP VIIRS","volume":"94","author":"Hillger","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.rse.2013.12.008","article-title":"The New VIIRS 375 m active fire detection data product: Algorithm description and initial assessment","volume":"143","author":"Schroeder","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1228","DOI":"10.1109\/36.701075","article-title":"The Moderate Resolution Imaging Spectroradiometer (MODIS): Land Remote Sensing for Global Change Research","volume":"36","author":"Justice","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"32215","DOI":"10.1029\/98JD01644","article-title":"Potential global fire monitoring from EOS-MODIS","volume":"103","author":"Kaufman","year":"1998","journal-title":"J. Geophys. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0034-4257(03)00184-6","article-title":"An Enhanced Contextual Fire Detection Algorithm for MODIS","volume":"87","author":"Giglio","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.rse.2016.02.054","article-title":"The collection 6 MODIS active fire detection algorithm and fire products","volume":"178","author":"Giglio","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/S0034-4257(03)00070-1","article-title":"Fire radiative energy for quantitative study of biomass burning: Derivation from the BIRD experimental satellite and comparison to MODIS fire products","volume":"86","author":"Wooster","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.rse.2005.09.019","article-title":"Spaceborne detection and characterization of fires during the bi-spectral infrared detection (BIRD) experimental small satellite mission (2001\u20132004)","volume":"100","author":"Zhukov","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2783","DOI":"10.1080\/01431169208904081","article-title":"Geostationary satellite detection of biomass burning in South America","volume":"13","author":"Prins","year":"1992","journal-title":"Int. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1175\/1520-0477(1994)075<0757:IGITFO>2.0.CO;2","article-title":"Introducing GOES-I: The First of a New Generation of Geostationary Operational Environmental Satellites","volume":"75","author":"Menzel","year":"1994","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"31821","DOI":"10.1029\/98JD01720","article-title":"An overview of GOES-8 diurnal fire and smoke results for SCAR-B and 1995 fire season in South America","volume":"103","author":"Prins","year":"1998","journal-title":"J. Geophys. Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/j.rse.2012.09.001","article-title":"On timeliness and accuracy of wildfire detection by the GOES WF-ABBA algorithm over California during the 2006 fire season","volume":"127","author":"Koltunov","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1876","DOI":"10.1016\/j.rse.2010.03.012","article-title":"New GOES imager algorithms for cloud and active fire detection and fire radiative power assessment across North, South and Central America","volume":"114","author":"Xu","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1016\/j.rse.2007.05.004","article-title":"Quantifying the impact of cloud obscuration on remote sensing of active fires in the Brazilian Amazon","volume":"2008","author":"Schroeder","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2711","DOI":"10.1016\/j.rse.2008.01.005","article-title":"Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data","volume":"112","author":"Schroeder","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_24","unstructured":"Schmidt, C.S., Hoffman, J., Prins, E.M., and Lindstrom, S. (2018, October 02). GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document for Fire\/Hot Spot Characterization, Available online: https:\/\/www.star.nesdis.noaa.gov\/goesr\/docs\/ATBD\/Fire.pdf."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1016\/j.rse.2016.07.021","article-title":"The development and first validation of the GOES Early Fire Detection (GOES-EFD) algorithm","volume":"184","author":"Koltunov","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Aminou, D., Jacquet, B., and Pasternak, F. (1997). Characteristics of the Meteosat Second Generation (MSG) Radiometer\/Imager: SEVIRI, SPIE.","DOI":"10.1117\/12.298084"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Roberts, G., Wooster, M.J., Perry, G.L.W., Drake, N., Rebelo, L.-M., and Dipotso, F. (2005). Retrieval of biomass combustion rates and totals from fire radiative power observations: Application to southern Africa using geostationary SEVIRI imagery. J. Geophys. Res., 110.","DOI":"10.1029\/2005JD006018"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1109\/TGRS.2008.915751","article-title":"Fire Detection and Fire Characterization over Africa Using Meteosat SEVIRI","volume":"46","author":"Roberts","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1016\/j.rse.2014.06.020","article-title":"Development of a multi-temporal Kalman filter approach to geostationary active fire detection & fire radiative power (FRP) estimation","volume":"152","author":"Roberts","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"13217","DOI":"10.5194\/acp-15-13217-2015","article-title":"LSA SAF Meteosat FRP products\u2014Part 1: Algorithms, product contents, and analysis","volume":"15","author":"Wooster","year":"2015","journal-title":"Atmos. Chem. Phys."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"151","DOI":"10.2151\/jmsj.2016-009","article-title":"An introduction to Himawari 8\/9\u2014Japan\u2019s New-Generation Geostationary Meteorological Satellites","volume":"94","author":"Bessho","year":"2016","journal-title":"J. Meteorol. Soc. Jpn."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.rse.2017.02.024","article-title":"Major advances in geostationary fire radiative power (FRP) retrieval over Asia and Australia stemming from use of Himawari-8 AHI","volume":"193","author":"Xu","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Hally, B., Wallace, L., Reinke, K., and Jones, S. (2017). A Broad-Area Method for the Diurnal Characterisation of Upwelling Medium Wave Infrared Radiation. Remote Sens., 9.","DOI":"10.3390\/rs9020167"},{"key":"ref_34","unstructured":"Engel, C.B., Jones, S.D., and Reinke, K. (2020). A Seasonal-Window Ensemble-Based Thresholding Technique Used to Detect Active Fires in Geostationary Remotely Sensed Data. IEEE Trans. Geosci. Remote Sens., 1\u201310."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1080\/01431168808954841","article-title":"An improved method for detecting clear sky and cloudy radiances from AVHRR data","volume":"9","author":"Saunders","year":"1988","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2007.02.010","article-title":"Early fire detection using non-linear multitemporal prediction of thermal imagery","volume":"110","author":"Koltunov","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1080\/01431160802220193","article-title":"Image construction using multitemporal observations and Dynamic Detection Models","volume":"30","author":"Koltunov","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.rse.2019.03.039","article-title":"A cloud detection algorithm for satellite imagery based on deep learning","volume":"229","author":"Jeppesen","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2020.112045","article-title":"Accurate cloud detection in high-resolution remote sensing imagery by weakly supervised deep learning","volume":"250","author":"Li","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_40","unstructured":"Australia, E. (2000). Revision of the Interim Biogeographic Regionalisation of Australia (IBRA) and the Development of Version 5.1\u2014Summary Report, Department of Environment and Heritage."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/S0034-4257(03)00079-8","article-title":"Thermal remote sensing of urban climates","volume":"86","author":"Voogt","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"13241","DOI":"10.5194\/acp-15-13241-2015","article-title":"LSA SAF Meteosat FRP products\u2014Part 2: Evaluation and demonstration for use in the Copernicus Atmosphere Monitoring Service","volume":"15","author":"Roberts","year":"2015","journal-title":"Atmos. Chem. Phys."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/0034-4257(89)90023-0","article-title":"Application of Remote Sensing and Geographic Information Systems to Forest Fire Hazard Mapping","volume":"29","author":"Chuvieco","year":"1989","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1627\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:50:47Z","timestamp":1760161847000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1627"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,21]]},"references-count":43,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13091627"],"URL":"https:\/\/doi.org\/10.3390\/rs13091627","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,21]]}}}