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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of geophysical research. Biogeosciences 2022-12, Vol.127 (12), p.n/a
Hauptverfasser: Amici, S., Spiller, D., Ansalone, L., Miller, L.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page n/a
container_issue 12
container_start_page
container_title Journal of geophysical research. Biogeosciences
container_volume 127
creator Amici, S.
Spiller, D.
Ansalone, L.
Miller, L.
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
format Article
fullrecord <record><control><sourceid>proquest_osti_</sourceid><recordid>TN_cdi_osti_scitechconnect_1987314</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2758477599</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3725-5a5f2ddabce91c1d27c2c04bfef81e68c4ae1c517517ac4643ce2f5f76fb02493</originalsourceid><addsrcrecordid>eNp9kF1LwzAUhosoOObu_AFBQRSsJmnTtJejzM0xmewDL0OWnrCOfpl0SP-9GRXxysOBc3h5OLzn9bxrgp8IpskzxZTOpxhzzNiZN6AkSvw4icj5786CS29k7QG7ip1EyMA7fORFpnMDFm2gbMDI9mgATWybl7LN6wrtOpTWZVNACVUrTYe2FlCt0axztG1AtUYW6H31un4bI1llaLMHUzrpfpIu15vVZL1Gd2gRP1x5F1oWFkY_c-htXyabdOYvltPXdLzwVcAp85lkmmaZ3ClIiCIZ5YoqHO406JhAFKtQAlGMcNdShVEYKKCaaR7pHaZhEgy9m_5u7Z4QVuUtqL2qq8pZFSSJeUBCB932UGPqzyPYVhzqo6mcL0E5i0POWXI69dhTytTWGtCiMS4X0wmCxSl18Td1hwc9_pUX0P3Livl0NaU0iFjwDeS4gTc</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2758477599</pqid></control><display><type>article</type><title>Wildfires Temperature Estimation by Complementary Use of Hyperspectral PRISMA and Thermal (ECOSTRESS &amp; L8)</title><source>Wiley Online Library Free Content</source><source>Access via Wiley Online Library</source><source>Alma/SFX Local Collection</source><creator>Amici, S. ; Spiller, D. ; Ansalone, L. ; Miller, L.</creator><creatorcontrib>Amici, S. ; Spiller, D. ; Ansalone, L. ; Miller, L. ; Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)</creatorcontrib><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><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 &amp; 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 &amp; 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 &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>Aquatic Science &amp; 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 &amp; 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>
fulltext fulltext
identifier ISSN: 2169-8953
ispartof Journal of geophysical research. Biogeosciences, 2022-12, Vol.127 (12), p.n/a
issn 2169-8953
2169-8961
language eng
recordid cdi_osti_scitechconnect_1987314
source Wiley Online Library Free Content; Access via Wiley Online Library; Alma/SFX Local Collection
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)
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T00%3A56%3A37IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_osti_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Wildfires%20Temperature%20Estimation%20by%20Complementary%20Use%20of%20Hyperspectral%20PRISMA%20and%20Thermal%20(ECOSTRESS%20&%20L8)&rft.jtitle=Journal%20of%20geophysical%20research.%20Biogeosciences&rft.au=Amici,%20S.&rft.aucorp=Pacific%20Northwest%20National%20Laboratory%20(PNNL),%20Richland,%20WA%20(United%20States)&rft.date=2022-12&rft.volume=127&rft.issue=12&rft.epage=n/a&rft.issn=2169-8953&rft.eissn=2169-8961&rft_id=info:doi/10.1029/2022JG007055&rft_dat=%3Cproquest_osti_%3E2758477599%3C/proquest_osti_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2758477599&rft_id=info:pmid/&rfr_iscdi=true