Loading…

On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection

Timely and continuous information about flood spatiotemporal evolution are fundamental to ensure an effective implementation of the relief and rescue operations in case of inundation events. In this framework, satellite remote sensing may provide a valuable contribution provided that robust data ana...

Full description

Saved in:
Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2019-03, Vol.11 (5), p.598
Main Authors: Lacava, Teodosio, Ciancia, Emanuele, Faruolo, Mariapia, Pergola, Nicola, Satriano, Valeria, Tramutoli, Valerio
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c361t-cbaccab9626e316f347de463ceb7142381b45fb40e7fb671f08bd6ba02b489753
cites cdi_FETCH-LOGICAL-c361t-cbaccab9626e316f347de463ceb7142381b45fb40e7fb671f08bd6ba02b489753
container_end_page
container_issue 5
container_start_page 598
container_title Remote sensing (Basel, Switzerland)
container_volume 11
creator Lacava, Teodosio
Ciancia, Emanuele
Faruolo, Mariapia
Pergola, Nicola
Satriano, Valeria
Tramutoli, Valerio
description Timely and continuous information about flood spatiotemporal evolution are fundamental to ensure an effective implementation of the relief and rescue operations in case of inundation events. In this framework, satellite remote sensing may provide a valuable contribution provided that robust data analysis methods are implemented and suitable data, in terms of spatial, spectral and temporal resolutions, are employed. In this paper, the Robust Satellite Techniques (RST) approach, a satellite-based differential approach, already applied at detecting flooded areas (and therefore christened RST-FLOOD) with good results on different polar orbiting optical sensors (i.e., Advanced Very High Resolution Radiometer – AVHRR – and Moderate Resolution Imaging Spectroradiometer – MODIS), has been fully implemented on time series of Suomi National Polar-orbiting Partnership (Suomi-NPP-SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data. The flooding event affecting the Metaponto Plain in Basilicata and Puglia regions (southern Italy) in December 2013 was selected as a case study and investigated by analysing five years (only December month) of VIIRS Imagery bands at 375 m spatial resolution. The achieved results clearly indicate the potential of the proposed approach, especially when compared with a satellite-based high resolution map of flooded area, as well as with the official flood hazard map of the area and the outputs of a recent published VIIRS-based method. Both flood extent and dynamics have been recognized with good reliability during the investigated period, with only a residual 11.5% of possible false positives over an inundated area extent of about 73 km2. In addition, a flooded area of about 18 km2 was found outside the hazard map, suggesting it requires updating to better manage flood risk and prevent future damages. Finally, the achieved results indicate that medium-resolution optical data, if analysed with robust methodologies like RST-FLOOD, can be suitable for detecting and monitoring floods also in case of small hydrological basins.
doi_str_mv 10.3390/rs11050598
format article
fullrecord <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_7298779ccfec4f81bf47a3cf647a4a42</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_7298779ccfec4f81bf47a3cf647a4a42</doaj_id><sourcerecordid>2303995968</sourcerecordid><originalsourceid>FETCH-LOGICAL-c361t-cbaccab9626e316f347de463ceb7142381b45fb40e7fb671f08bd6ba02b489753</originalsourceid><addsrcrecordid>eNpNkU-LFDEQxYMouIx78RMEvAmt-ddJ57jsOOvAwMju6jVU0pUxY09nTTIHv72tI2pdXlH8eK_gEfKas3dSWva-VM5Zz3o7PCNXghnRKWHF8__2l-S61iNbRkpumboi3_YzbV-RfsoN55ZgojnS-4fHbrPb79c0z_RLqslPSLdzLFBwpNsTHNJ8oPcwpnzChoU-nFNDuoYGNOZCN1PO40LeFIRK1wsSWsrzK_IiwlTx-o-uyOfNh8fbj91uf7e9vdl1QWreuuAhBPBWC42S6yiVGVFpGdAbroQcuFd99IqhiV4bHtngR-2BCa8Ga3q5ItuL75jh6J5KOkH54TIk9_uQy8FBaSlM6IywgzE2hIhBxcU5KgMyRL2IgiVsRd5cvJ5K_n7G2twxn8u8vO-EZNLa3uphod5eqFByrQXj31TO3K9u3L9u5E8ItX-l</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2303995968</pqid></control><display><type>article</type><title>On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection</title><source>Publicly Available Content Database</source><creator>Lacava, Teodosio ; Ciancia, Emanuele ; Faruolo, Mariapia ; Pergola, Nicola ; Satriano, Valeria ; Tramutoli, Valerio</creator><creatorcontrib>Lacava, Teodosio ; Ciancia, Emanuele ; Faruolo, Mariapia ; Pergola, Nicola ; Satriano, Valeria ; Tramutoli, Valerio</creatorcontrib><description>Timely and continuous information about flood spatiotemporal evolution are fundamental to ensure an effective implementation of the relief and rescue operations in case of inundation events. In this framework, satellite remote sensing may provide a valuable contribution provided that robust data analysis methods are implemented and suitable data, in terms of spatial, spectral and temporal resolutions, are employed. In this paper, the Robust Satellite Techniques (RST) approach, a satellite-based differential approach, already applied at detecting flooded areas (and therefore christened RST-FLOOD) with good results on different polar orbiting optical sensors (i.e., Advanced Very High Resolution Radiometer – AVHRR – and Moderate Resolution Imaging Spectroradiometer – MODIS), has been fully implemented on time series of Suomi National Polar-orbiting Partnership (Suomi-NPP-SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data. The flooding event affecting the Metaponto Plain in Basilicata and Puglia regions (southern Italy) in December 2013 was selected as a case study and investigated by analysing five years (only December month) of VIIRS Imagery bands at 375 m spatial resolution. The achieved results clearly indicate the potential of the proposed approach, especially when compared with a satellite-based high resolution map of flooded area, as well as with the official flood hazard map of the area and the outputs of a recent published VIIRS-based method. Both flood extent and dynamics have been recognized with good reliability during the investigated period, with only a residual 11.5% of possible false positives over an inundated area extent of about 73 km2. In addition, a flooded area of about 18 km2 was found outside the hazard map, suggesting it requires updating to better manage flood risk and prevent future damages. Finally, the achieved results indicate that medium-resolution optical data, if analysed with robust methodologies like RST-FLOOD, can be suitable for detecting and monitoring floods also in case of small hydrological basins.</description><identifier>ISSN: 2072-4292</identifier><identifier>EISSN: 2072-4292</identifier><identifier>DOI: 10.3390/rs11050598</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Archives &amp; records ; Basins ; Damage prevention ; Data analysis ; Environmental risk ; flood ; Flood hazards ; Flood management ; Flood mapping ; Flooded areas ; Flooding ; Floods ; High resolution ; Hydrologic data ; Hydrology ; Imaging radiometers ; Information science ; Infrared imaging ; Infrared radiometers ; JPSS ; near real time ; Optical measuring instruments ; Precipitation ; Radiometers ; Radiometry ; Remote sensing ; Rescue operations ; Risk management ; Rivers ; Robustness ; RST-FLOOD ; satellite remote sensing ; Satellites ; Sensors ; SNPP ; Spatial data ; Spatial resolution ; Spectroradiometers ; Surface water ; VIIRS</subject><ispartof>Remote sensing (Basel, Switzerland), 2019-03, Vol.11 (5), p.598</ispartof><rights>2019. This work is licensed under https://creativecommons.org/licenses/by/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-c361t-cbaccab9626e316f347de463ceb7142381b45fb40e7fb671f08bd6ba02b489753</citedby><cites>FETCH-LOGICAL-c361t-cbaccab9626e316f347de463ceb7142381b45fb40e7fb671f08bd6ba02b489753</cites><orcidid>0000-0001-7619-6685 ; 0000-0003-3875-7909 ; 0000-0002-6732-4419 ; 0000-0003-0335-2565 ; 0000-0001-5291-8241</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2303995968/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2303995968?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,25734,27905,27906,36993,44571,74875</link.rule.ids></links><search><creatorcontrib>Lacava, Teodosio</creatorcontrib><creatorcontrib>Ciancia, Emanuele</creatorcontrib><creatorcontrib>Faruolo, Mariapia</creatorcontrib><creatorcontrib>Pergola, Nicola</creatorcontrib><creatorcontrib>Satriano, Valeria</creatorcontrib><creatorcontrib>Tramutoli, Valerio</creatorcontrib><title>On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection</title><title>Remote sensing (Basel, Switzerland)</title><description>Timely and continuous information about flood spatiotemporal evolution are fundamental to ensure an effective implementation of the relief and rescue operations in case of inundation events. In this framework, satellite remote sensing may provide a valuable contribution provided that robust data analysis methods are implemented and suitable data, in terms of spatial, spectral and temporal resolutions, are employed. In this paper, the Robust Satellite Techniques (RST) approach, a satellite-based differential approach, already applied at detecting flooded areas (and therefore christened RST-FLOOD) with good results on different polar orbiting optical sensors (i.e., Advanced Very High Resolution Radiometer – AVHRR – and Moderate Resolution Imaging Spectroradiometer – MODIS), has been fully implemented on time series of Suomi National Polar-orbiting Partnership (Suomi-NPP-SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data. The flooding event affecting the Metaponto Plain in Basilicata and Puglia regions (southern Italy) in December 2013 was selected as a case study and investigated by analysing five years (only December month) of VIIRS Imagery bands at 375 m spatial resolution. The achieved results clearly indicate the potential of the proposed approach, especially when compared with a satellite-based high resolution map of flooded area, as well as with the official flood hazard map of the area and the outputs of a recent published VIIRS-based method. Both flood extent and dynamics have been recognized with good reliability during the investigated period, with only a residual 11.5% of possible false positives over an inundated area extent of about 73 km2. In addition, a flooded area of about 18 km2 was found outside the hazard map, suggesting it requires updating to better manage flood risk and prevent future damages. Finally, the achieved results indicate that medium-resolution optical data, if analysed with robust methodologies like RST-FLOOD, can be suitable for detecting and monitoring floods also in case of small hydrological basins.</description><subject>Archives &amp; records</subject><subject>Basins</subject><subject>Damage prevention</subject><subject>Data analysis</subject><subject>Environmental risk</subject><subject>flood</subject><subject>Flood hazards</subject><subject>Flood management</subject><subject>Flood mapping</subject><subject>Flooded areas</subject><subject>Flooding</subject><subject>Floods</subject><subject>High resolution</subject><subject>Hydrologic data</subject><subject>Hydrology</subject><subject>Imaging radiometers</subject><subject>Information science</subject><subject>Infrared imaging</subject><subject>Infrared radiometers</subject><subject>JPSS</subject><subject>near real time</subject><subject>Optical measuring instruments</subject><subject>Precipitation</subject><subject>Radiometers</subject><subject>Radiometry</subject><subject>Remote sensing</subject><subject>Rescue operations</subject><subject>Risk management</subject><subject>Rivers</subject><subject>Robustness</subject><subject>RST-FLOOD</subject><subject>satellite remote sensing</subject><subject>Satellites</subject><subject>Sensors</subject><subject>SNPP</subject><subject>Spatial data</subject><subject>Spatial resolution</subject><subject>Spectroradiometers</subject><subject>Surface water</subject><subject>VIIRS</subject><issn>2072-4292</issn><issn>2072-4292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNkU-LFDEQxYMouIx78RMEvAmt-ddJ57jsOOvAwMju6jVU0pUxY09nTTIHv72tI2pdXlH8eK_gEfKas3dSWva-VM5Zz3o7PCNXghnRKWHF8__2l-S61iNbRkpumboi3_YzbV-RfsoN55ZgojnS-4fHbrPb79c0z_RLqslPSLdzLFBwpNsTHNJ8oPcwpnzChoU-nFNDuoYGNOZCN1PO40LeFIRK1wsSWsrzK_IiwlTx-o-uyOfNh8fbj91uf7e9vdl1QWreuuAhBPBWC42S6yiVGVFpGdAbroQcuFd99IqhiV4bHtngR-2BCa8Ga3q5ItuL75jh6J5KOkH54TIk9_uQy8FBaSlM6IywgzE2hIhBxcU5KgMyRL2IgiVsRd5cvJ5K_n7G2twxn8u8vO-EZNLa3uphod5eqFByrQXj31TO3K9u3L9u5E8ItX-l</recordid><startdate>20190301</startdate><enddate>20190301</enddate><creator>Lacava, Teodosio</creator><creator>Ciancia, Emanuele</creator><creator>Faruolo, Mariapia</creator><creator>Pergola, Nicola</creator><creator>Satriano, Valeria</creator><creator>Tramutoli, Valerio</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7QR</scope><scope>7SC</scope><scope>7SE</scope><scope>7SN</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-7619-6685</orcidid><orcidid>https://orcid.org/0000-0003-3875-7909</orcidid><orcidid>https://orcid.org/0000-0002-6732-4419</orcidid><orcidid>https://orcid.org/0000-0003-0335-2565</orcidid><orcidid>https://orcid.org/0000-0001-5291-8241</orcidid></search><sort><creationdate>20190301</creationdate><title>On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection</title><author>Lacava, Teodosio ; Ciancia, Emanuele ; Faruolo, Mariapia ; Pergola, Nicola ; Satriano, Valeria ; Tramutoli, Valerio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c361t-cbaccab9626e316f347de463ceb7142381b45fb40e7fb671f08bd6ba02b489753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Archives &amp; records</topic><topic>Basins</topic><topic>Damage prevention</topic><topic>Data analysis</topic><topic>Environmental risk</topic><topic>flood</topic><topic>Flood hazards</topic><topic>Flood management</topic><topic>Flood mapping</topic><topic>Flooded areas</topic><topic>Flooding</topic><topic>Floods</topic><topic>High resolution</topic><topic>Hydrologic data</topic><topic>Hydrology</topic><topic>Imaging radiometers</topic><topic>Information science</topic><topic>Infrared imaging</topic><topic>Infrared radiometers</topic><topic>JPSS</topic><topic>near real time</topic><topic>Optical measuring instruments</topic><topic>Precipitation</topic><topic>Radiometers</topic><topic>Radiometry</topic><topic>Remote sensing</topic><topic>Rescue operations</topic><topic>Risk management</topic><topic>Rivers</topic><topic>Robustness</topic><topic>RST-FLOOD</topic><topic>satellite remote sensing</topic><topic>Satellites</topic><topic>Sensors</topic><topic>SNPP</topic><topic>Spatial data</topic><topic>Spatial resolution</topic><topic>Spectroradiometers</topic><topic>Surface water</topic><topic>VIIRS</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lacava, Teodosio</creatorcontrib><creatorcontrib>Ciancia, Emanuele</creatorcontrib><creatorcontrib>Faruolo, Mariapia</creatorcontrib><creatorcontrib>Pergola, Nicola</creatorcontrib><creatorcontrib>Satriano, Valeria</creatorcontrib><creatorcontrib>Tramutoli, Valerio</creatorcontrib><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Ecology Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ProQuest Engineering Database</collection><collection>ProQuest advanced technologies &amp; aerospace journals</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest Earth, Atmospheric &amp; Aquatic Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Remote sensing (Basel, Switzerland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lacava, Teodosio</au><au>Ciancia, Emanuele</au><au>Faruolo, Mariapia</au><au>Pergola, Nicola</au><au>Satriano, Valeria</au><au>Tramutoli, Valerio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection</atitle><jtitle>Remote sensing (Basel, Switzerland)</jtitle><date>2019-03-01</date><risdate>2019</risdate><volume>11</volume><issue>5</issue><spage>598</spage><pages>598-</pages><issn>2072-4292</issn><eissn>2072-4292</eissn><abstract>Timely and continuous information about flood spatiotemporal evolution are fundamental to ensure an effective implementation of the relief and rescue operations in case of inundation events. In this framework, satellite remote sensing may provide a valuable contribution provided that robust data analysis methods are implemented and suitable data, in terms of spatial, spectral and temporal resolutions, are employed. In this paper, the Robust Satellite Techniques (RST) approach, a satellite-based differential approach, already applied at detecting flooded areas (and therefore christened RST-FLOOD) with good results on different polar orbiting optical sensors (i.e., Advanced Very High Resolution Radiometer – AVHRR – and Moderate Resolution Imaging Spectroradiometer – MODIS), has been fully implemented on time series of Suomi National Polar-orbiting Partnership (Suomi-NPP-SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data. The flooding event affecting the Metaponto Plain in Basilicata and Puglia regions (southern Italy) in December 2013 was selected as a case study and investigated by analysing five years (only December month) of VIIRS Imagery bands at 375 m spatial resolution. The achieved results clearly indicate the potential of the proposed approach, especially when compared with a satellite-based high resolution map of flooded area, as well as with the official flood hazard map of the area and the outputs of a recent published VIIRS-based method. Both flood extent and dynamics have been recognized with good reliability during the investigated period, with only a residual 11.5% of possible false positives over an inundated area extent of about 73 km2. In addition, a flooded area of about 18 km2 was found outside the hazard map, suggesting it requires updating to better manage flood risk and prevent future damages. Finally, the achieved results indicate that medium-resolution optical data, if analysed with robust methodologies like RST-FLOOD, can be suitable for detecting and monitoring floods also in case of small hydrological basins.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/rs11050598</doi><orcidid>https://orcid.org/0000-0001-7619-6685</orcidid><orcidid>https://orcid.org/0000-0003-3875-7909</orcidid><orcidid>https://orcid.org/0000-0002-6732-4419</orcidid><orcidid>https://orcid.org/0000-0003-0335-2565</orcidid><orcidid>https://orcid.org/0000-0001-5291-8241</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2072-4292
ispartof Remote sensing (Basel, Switzerland), 2019-03, Vol.11 (5), p.598
issn 2072-4292
2072-4292
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_7298779ccfec4f81bf47a3cf647a4a42
source Publicly Available Content Database
subjects Archives & records
Basins
Damage prevention
Data analysis
Environmental risk
flood
Flood hazards
Flood management
Flood mapping
Flooded areas
Flooding
Floods
High resolution
Hydrologic data
Hydrology
Imaging radiometers
Information science
Infrared imaging
Infrared radiometers
JPSS
near real time
Optical measuring instruments
Precipitation
Radiometers
Radiometry
Remote sensing
Rescue operations
Risk management
Rivers
Robustness
RST-FLOOD
satellite remote sensing
Satellites
Sensors
SNPP
Spatial data
Spatial resolution
Spectroradiometers
Surface water
VIIRS
title On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-17T23%3A25%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=On%20the%20Potential%20of%20RST-FLOOD%20on%20Visible%20Infrared%20Imaging%20Radiometer%20Suite%20Data%20for%20Flooded%20Areas%20Detection&rft.jtitle=Remote%20sensing%20(Basel,%20Switzerland)&rft.au=Lacava,%20Teodosio&rft.date=2019-03-01&rft.volume=11&rft.issue=5&rft.spage=598&rft.pages=598-&rft.issn=2072-4292&rft.eissn=2072-4292&rft_id=info:doi/10.3390/rs11050598&rft_dat=%3Cproquest_doaj_%3E2303995968%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c361t-cbaccab9626e316f347de463ceb7142381b45fb40e7fb671f08bd6ba02b489753%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2303995968&rft_id=info:pmid/&rfr_iscdi=true