Wildfires Temperature Estimation by Complementary Use of Hyperspectral PRISMA and Thermal (ECOSTRESS & L8)
This paper deals with detection and temperature analysis and of wildfires using PRISMA imagery. Precursore IperSpettrale della Missione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by ASI (Agenzia Spaziale Italiana, Italian Space Agency) lau...
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description | This paper deals with detection and temperature analysis and of wildfires using PRISMA imagery. Precursore IperSpettrale della Missione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by ASI (Agenzia Spaziale Italiana, Italian Space Agency) launched in 2019. This mission provides hyperspectral images with a spectral range of 400–2,500 nm and an average spectral resolution less than 12 nm and a spatial resolution of 30 m/pixel. This study focuses on the wildfire temperature estimation over the Bootleg Fire, US 2021. The analysis starts by considering the Hyperspectral Fire Detection Index (HFDI) which is used to analyze the informative content of the images, along with the analysis of some specific visible, near‐infrared and shortwave‐infrared bands. This first analysis is used as input to perform a temperature estimation of the areas with active wildfire. Surface temperature is retrieved using PRISMA radiance and a linear mixing model based on two background components (vegetation and burn scar) and two active fire components. PRISMA temperatures are compared with LST (Land Surface Temperature) products from NASA's ECOSTRESS and Landsat 8 which imaged the Bootleg Fire before and after PRISMA. A critical discussion of the results obtained with PRISMA is presented, followed by the advantages and limitation of the proposed approach.
Plain Language Summary
This work explores new opportunities for wildfire mapping and monitoring basing on recent technological achievements in the field of remote sensing and data analysis. The input data of this research study are provided by the new satellite PRISMA (Precursore IperSpettrale della Missione Applicativa, Hyperspectral Precursor of the Application Mission) from ASI (Agenzia Spaziale Italiana, Italian Space Agency). This spacecraft represents an innovative remote sensing mission for the observation of the Earth, as it provides images with a revolutionary quantity of spectral information which go far beyond the visible spectrum. Using PRISMA data, we study the Bootleg Fire during 2021 in the US, providing a descriptive analysis of the wildfire and a quantitative estimation of the temperatures achieved during the event. To confirm the results of our approach, we also compare the outcomes to the data provided by two other satellite missions: ECOSTRESS (ECOsystem Spaceborne Thermal Radiometer Experiment) and Landsat 8. Hence, a critical discussion of the results ob |
doi_str_mv | 10.1029/2022JG007055 |
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Plain Language Summary
This work explores new opportunities for wildfire mapping and monitoring basing on recent technological achievements in the field of remote sensing and data analysis. The input data of this research study are provided by the new satellite PRISMA (Precursore IperSpettrale della Missione Applicativa, Hyperspectral Precursor of the Application Mission) from ASI (Agenzia Spaziale Italiana, Italian Space Agency). This spacecraft represents an innovative remote sensing mission for the observation of the Earth, as it provides images with a revolutionary quantity of spectral information which go far beyond the visible spectrum. Using PRISMA data, we study the Bootleg Fire during 2021 in the US, providing a descriptive analysis of the wildfire and a quantitative estimation of the temperatures achieved during the event. To confirm the results of our approach, we also compare the outcomes to the data provided by two other satellite missions: ECOSTRESS (ECOsystem Spaceborne Thermal Radiometer Experiment) and Landsat 8. Hence, a critical discussion of the results obtained with PRISMA is presented in order to report advantages and limitation of the proposed approach.
Key Points
Hyperspectral fire index for PRISMA data has been retrieved to create a wildfire detection map of Bootleg Fire, Oregon 2021
Hot temperatures of wildfire has been estimated by applying linear mixture analysis to PRISMA data
Multisensor approach has been used to characterize Bootleg wildfire temperature evolution</description><identifier>ISSN: 2169-8953</identifier><identifier>EISSN: 2169-8961</identifier><identifier>DOI: 10.1029/2022JG007055</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Analysis ; Bootleg wildfire 2021 ; Components ; Data analysis ; Detection ; ECOSTRESS ; ENVIRONMENTAL SCIENCES ; Fire detection ; Fires ; hot temperatures estimation ; hyperspectral ; Hyperspectral imaging ; Infrared analysis ; Land surface temperature ; Landsat ; Landsat satellites ; Precursors ; PRISMA ; PRISMA hyperspectral images ; Radiance ; Radiometers ; Remote observing ; Remote sensing ; Resolution ; Satellites ; Short wave radiation ; Space missions ; Spacecraft ; Spatial discrimination ; Spatial resolution ; Spectral resolution ; Surface temperature ; Temperature ; Visible spectrum ; wildfire detection ; Wildfires</subject><ispartof>Journal of geophysical research. Biogeosciences, 2022-12, Vol.127 (12), p.n/a</ispartof><rights>2022. American Geophysical Union. All Rights Reserved.</rights><rights>2022. This article is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3725-5a5f2ddabce91c1d27c2c04bfef81e68c4ae1c517517ac4643ce2f5f76fb02493</citedby><cites>FETCH-LOGICAL-c3725-5a5f2ddabce91c1d27c2c04bfef81e68c4ae1c517517ac4643ce2f5f76fb02493</cites><orcidid>0000-0002-6877-3187 ; 0000-0003-2410-646X ; 000000032410646X ; 0000000268773187</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2022JG007055$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2022JG007055$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,1417,1433,27924,27925,45574,45575,46409,46833</link.rule.ids><backlink>$$Uhttps://www.osti.gov/servlets/purl/1987314$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Amici, S.</creatorcontrib><creatorcontrib>Spiller, D.</creatorcontrib><creatorcontrib>Ansalone, L.</creatorcontrib><creatorcontrib>Miller, L.</creatorcontrib><creatorcontrib>Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)</creatorcontrib><title>Wildfires Temperature Estimation by Complementary Use of Hyperspectral PRISMA and Thermal (ECOSTRESS & L8)</title><title>Journal of geophysical research. Biogeosciences</title><description>This paper deals with detection and temperature analysis and of wildfires using PRISMA imagery. Precursore IperSpettrale della Missione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by ASI (Agenzia Spaziale Italiana, Italian Space Agency) launched in 2019. This mission provides hyperspectral images with a spectral range of 400–2,500 nm and an average spectral resolution less than 12 nm and a spatial resolution of 30 m/pixel. This study focuses on the wildfire temperature estimation over the Bootleg Fire, US 2021. The analysis starts by considering the Hyperspectral Fire Detection Index (HFDI) which is used to analyze the informative content of the images, along with the analysis of some specific visible, near‐infrared and shortwave‐infrared bands. This first analysis is used as input to perform a temperature estimation of the areas with active wildfire. Surface temperature is retrieved using PRISMA radiance and a linear mixing model based on two background components (vegetation and burn scar) and two active fire components. PRISMA temperatures are compared with LST (Land Surface Temperature) products from NASA's ECOSTRESS and Landsat 8 which imaged the Bootleg Fire before and after PRISMA. A critical discussion of the results obtained with PRISMA is presented, followed by the advantages and limitation of the proposed approach.
Plain Language Summary
This work explores new opportunities for wildfire mapping and monitoring basing on recent technological achievements in the field of remote sensing and data analysis. The input data of this research study are provided by the new satellite PRISMA (Precursore IperSpettrale della Missione Applicativa, Hyperspectral Precursor of the Application Mission) from ASI (Agenzia Spaziale Italiana, Italian Space Agency). This spacecraft represents an innovative remote sensing mission for the observation of the Earth, as it provides images with a revolutionary quantity of spectral information which go far beyond the visible spectrum. Using PRISMA data, we study the Bootleg Fire during 2021 in the US, providing a descriptive analysis of the wildfire and a quantitative estimation of the temperatures achieved during the event. To confirm the results of our approach, we also compare the outcomes to the data provided by two other satellite missions: ECOSTRESS (ECOsystem Spaceborne Thermal Radiometer Experiment) and Landsat 8. Hence, a critical discussion of the results obtained with PRISMA is presented in order to report advantages and limitation of the proposed approach.
Key Points
Hyperspectral fire index for PRISMA data has been retrieved to create a wildfire detection map of Bootleg Fire, Oregon 2021
Hot temperatures of wildfire has been estimated by applying linear mixture analysis to PRISMA data
Multisensor approach has been used to characterize Bootleg wildfire temperature evolution</description><subject>Analysis</subject><subject>Bootleg wildfire 2021</subject><subject>Components</subject><subject>Data analysis</subject><subject>Detection</subject><subject>ECOSTRESS</subject><subject>ENVIRONMENTAL SCIENCES</subject><subject>Fire detection</subject><subject>Fires</subject><subject>hot temperatures estimation</subject><subject>hyperspectral</subject><subject>Hyperspectral imaging</subject><subject>Infrared analysis</subject><subject>Land surface temperature</subject><subject>Landsat</subject><subject>Landsat satellites</subject><subject>Precursors</subject><subject>PRISMA</subject><subject>PRISMA hyperspectral images</subject><subject>Radiance</subject><subject>Radiometers</subject><subject>Remote observing</subject><subject>Remote sensing</subject><subject>Resolution</subject><subject>Satellites</subject><subject>Short wave radiation</subject><subject>Space missions</subject><subject>Spacecraft</subject><subject>Spatial discrimination</subject><subject>Spatial resolution</subject><subject>Spectral resolution</subject><subject>Surface temperature</subject><subject>Temperature</subject><subject>Visible spectrum</subject><subject>wildfire detection</subject><subject>Wildfires</subject><issn>2169-8953</issn><issn>2169-8961</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kF1LwzAUhosoOObu_AFBQRSsJmnTtJejzM0xmewDL0OWnrCOfpl0SP-9GRXxysOBc3h5OLzn9bxrgp8IpskzxZTOpxhzzNiZN6AkSvw4icj5786CS29k7QG7ip1EyMA7fORFpnMDFm2gbMDI9mgATWybl7LN6wrtOpTWZVNACVUrTYe2FlCt0axztG1AtUYW6H31un4bI1llaLMHUzrpfpIu15vVZL1Gd2gRP1x5F1oWFkY_c-htXyabdOYvltPXdLzwVcAp85lkmmaZ3ClIiCIZ5YoqHO406JhAFKtQAlGMcNdShVEYKKCaaR7pHaZhEgy9m_5u7Z4QVuUtqL2qq8pZFSSJeUBCB932UGPqzyPYVhzqo6mcL0E5i0POWXI69dhTytTWGtCiMS4X0wmCxSl18Td1hwc9_pUX0P3Livl0NaU0iFjwDeS4gTc</recordid><startdate>202212</startdate><enddate>202212</enddate><creator>Amici, S.</creator><creator>Spiller, D.</creator><creator>Ansalone, L.</creator><creator>Miller, L.</creator><general>Blackwell Publishing Ltd</general><general>American Geophysical Union</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope><scope>OIOZB</scope><scope>OTOTI</scope><orcidid>https://orcid.org/0000-0002-6877-3187</orcidid><orcidid>https://orcid.org/0000-0003-2410-646X</orcidid><orcidid>https://orcid.org/000000032410646X</orcidid><orcidid>https://orcid.org/0000000268773187</orcidid></search><sort><creationdate>202212</creationdate><title>Wildfires Temperature Estimation by Complementary Use of Hyperspectral PRISMA and Thermal (ECOSTRESS & L8)</title><author>Amici, S. ; Spiller, D. ; Ansalone, L. ; Miller, L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3725-5a5f2ddabce91c1d27c2c04bfef81e68c4ae1c517517ac4643ce2f5f76fb02493</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Analysis</topic><topic>Bootleg wildfire 2021</topic><topic>Components</topic><topic>Data analysis</topic><topic>Detection</topic><topic>ECOSTRESS</topic><topic>ENVIRONMENTAL SCIENCES</topic><topic>Fire detection</topic><topic>Fires</topic><topic>hot temperatures estimation</topic><topic>hyperspectral</topic><topic>Hyperspectral imaging</topic><topic>Infrared analysis</topic><topic>Land surface temperature</topic><topic>Landsat</topic><topic>Landsat satellites</topic><topic>Precursors</topic><topic>PRISMA</topic><topic>PRISMA hyperspectral images</topic><topic>Radiance</topic><topic>Radiometers</topic><topic>Remote observing</topic><topic>Remote sensing</topic><topic>Resolution</topic><topic>Satellites</topic><topic>Short wave radiation</topic><topic>Space missions</topic><topic>Spacecraft</topic><topic>Spatial discrimination</topic><topic>Spatial resolution</topic><topic>Spectral resolution</topic><topic>Surface temperature</topic><topic>Temperature</topic><topic>Visible spectrum</topic><topic>wildfire detection</topic><topic>Wildfires</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Amici, S.</creatorcontrib><creatorcontrib>Spiller, D.</creatorcontrib><creatorcontrib>Ansalone, L.</creatorcontrib><creatorcontrib>Miller, L.</creatorcontrib><creatorcontrib>Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)</creatorcontrib><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>OSTI.GOV - Hybrid</collection><collection>OSTI.GOV</collection><jtitle>Journal of geophysical research. Biogeosciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Amici, S.</au><au>Spiller, D.</au><au>Ansalone, L.</au><au>Miller, L.</au><aucorp>Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Wildfires Temperature Estimation by Complementary Use of Hyperspectral PRISMA and Thermal (ECOSTRESS & L8)</atitle><jtitle>Journal of geophysical research. Biogeosciences</jtitle><date>2022-12</date><risdate>2022</risdate><volume>127</volume><issue>12</issue><epage>n/a</epage><issn>2169-8953</issn><eissn>2169-8961</eissn><abstract>This paper deals with detection and temperature analysis and of wildfires using PRISMA imagery. Precursore IperSpettrale della Missione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by ASI (Agenzia Spaziale Italiana, Italian Space Agency) launched in 2019. This mission provides hyperspectral images with a spectral range of 400–2,500 nm and an average spectral resolution less than 12 nm and a spatial resolution of 30 m/pixel. This study focuses on the wildfire temperature estimation over the Bootleg Fire, US 2021. The analysis starts by considering the Hyperspectral Fire Detection Index (HFDI) which is used to analyze the informative content of the images, along with the analysis of some specific visible, near‐infrared and shortwave‐infrared bands. This first analysis is used as input to perform a temperature estimation of the areas with active wildfire. Surface temperature is retrieved using PRISMA radiance and a linear mixing model based on two background components (vegetation and burn scar) and two active fire components. PRISMA temperatures are compared with LST (Land Surface Temperature) products from NASA's ECOSTRESS and Landsat 8 which imaged the Bootleg Fire before and after PRISMA. A critical discussion of the results obtained with PRISMA is presented, followed by the advantages and limitation of the proposed approach.
Plain Language Summary
This work explores new opportunities for wildfire mapping and monitoring basing on recent technological achievements in the field of remote sensing and data analysis. The input data of this research study are provided by the new satellite PRISMA (Precursore IperSpettrale della Missione Applicativa, Hyperspectral Precursor of the Application Mission) from ASI (Agenzia Spaziale Italiana, Italian Space Agency). This spacecraft represents an innovative remote sensing mission for the observation of the Earth, as it provides images with a revolutionary quantity of spectral information which go far beyond the visible spectrum. Using PRISMA data, we study the Bootleg Fire during 2021 in the US, providing a descriptive analysis of the wildfire and a quantitative estimation of the temperatures achieved during the event. To confirm the results of our approach, we also compare the outcomes to the data provided by two other satellite missions: ECOSTRESS (ECOsystem Spaceborne Thermal Radiometer Experiment) and Landsat 8. Hence, a critical discussion of the results obtained with PRISMA is presented in order to report advantages and limitation of the proposed approach.
Key Points
Hyperspectral fire index for PRISMA data has been retrieved to create a wildfire detection map of Bootleg Fire, Oregon 2021
Hot temperatures of wildfire has been estimated by applying linear mixture analysis to PRISMA data
Multisensor approach has been used to characterize Bootleg wildfire temperature evolution</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2022JG007055</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0002-6877-3187</orcidid><orcidid>https://orcid.org/0000-0003-2410-646X</orcidid><orcidid>https://orcid.org/000000032410646X</orcidid><orcidid>https://orcid.org/0000000268773187</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Bootleg wildfire 2021 Components Data analysis Detection ECOSTRESS ENVIRONMENTAL SCIENCES Fire detection Fires hot temperatures estimation hyperspectral Hyperspectral imaging Infrared analysis Land surface temperature Landsat Landsat satellites Precursors PRISMA PRISMA hyperspectral images Radiance Radiometers Remote observing Remote sensing Resolution Satellites Short wave radiation Space missions Spacecraft Spatial discrimination Spatial resolution Spectral resolution Surface temperature Temperature Visible spectrum wildfire detection Wildfires |
title | Wildfires Temperature Estimation by Complementary Use of Hyperspectral PRISMA and Thermal (ECOSTRESS & L8) |
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