Mapping burned areas from Landsat TM/ETM+ data with a two-phase algorithm: Balancing omission and commission errors
Maps of burned area have been obtained from an automatic algorithm applied to a multitemporal series of Landsat TM/ETM+ images in two Mediterranean sites. The proposed algorithm is based on two phases: the first one intends to detect the more severely burned areas and minimize commission errors. The...
Saved in:
| Published in | Remote sensing of environment Vol. 115; no. 4; pp. 1003 - 1012 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
Elsevier Inc
15.04.2011
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0034-4257 1879-0704 1879-0704 |
| DOI | 10.1016/j.rse.2010.12.005 |
Cover
| Abstract | Maps of burned area have been obtained from an automatic algorithm applied to a multitemporal series of Landsat TM/ETM+ images in two Mediterranean sites. The proposed algorithm is based on two phases: the first one intends to detect the more severely burned areas and minimize commission errors. The second phase improves burned patches delimitation using a hybrid contextual algorithm based on logistic regression analysis, and tries to minimize omission errors. The algorithm was calibrated using six study sites and it was validated for the whole territory of Portugal (89,000
km
2) and for Southern California (70,000
km
2). In the validation exercise, 65 TM/ETM+ scenes for Portugal and 35 for California were used, all from the 2003 fire season. A good agreement with the official burned area perimeters was shown, with kappa values close to 0.85 and low omission and commission errors (<
16.5%). The proposed algorithm could be operationally used for historical mapping of burned areas from Landsat images, as well as from future medium resolution sensors, providing they acquire images in two bands of the Short Wave Infrared (1.5–2.2
μm).
► Burned area maps were generated from automatic processing of Landsat TM/ETM+ images. ► Algorithm was applied to 65 TM/ETM+ scenes in Portugal and 35 in California. ► Kappa values were close to 0.85, with low omission and commission errors (<
16.5%). |
|---|---|
| AbstractList | Maps of burned area have been obtained from an automatic algorithm applied to a multitemporal series of Landsat TM/ETM+ images in two Mediterranean sites. The proposed algorithm is based on two phases: the first one intends to detect the more severely burned areas and minimize commission errors. The second phase improves burned patches delimitation using a hybrid contextual algorithm based on logistic regression analysis, and tries to minimize omission errors. The algorithm was calibrated using six study sites and it was validated for the whole territory of Portugal (89,000km2) and for Southern California (70,000km2). In the validation exercise, 65 TM/ETM+ scenes for Portugal and 35 for California were used, all from the 2003 fire season. A good agreement with the official burned area perimeters was shown, with kappa values close to 0.85 and low omission and commission errors (<16.5%). The proposed algorithm could be operationally used for historical mapping of burned areas from Landsat images, as well as from future medium resolution sensors, providing they acquire images in two bands of the Short Wave Infrared (1.5-2.2 mu m). Maps of burned area have been obtained from an automatic algorithm applied to a multitemporal series of Landsat TM/ETM+ images in two Mediterranean sites. The proposed algorithm is based on two phases: the first one intends to detect the more severely burned areas and minimize commission errors. The second phase improves burned patches delimitation using a hybrid contextual algorithm based on logistic regression analysis, and tries to minimize omission errors. The algorithm was calibrated using six study sites and it was validated for the whole territory of Portugal (89,000km²) and for Southern California (70,000km²). In the validation exercise, 65 TM/ETM+ scenes for Portugal and 35 for California were used, all from the 2003 fire season. A good agreement with the official burned area perimeters was shown, with kappa values close to 0.85 and low omission and commission errors (<16.5%). The proposed algorithm could be operationally used for historical mapping of burned areas from Landsat images, as well as from future medium resolution sensors, providing they acquire images in two bands of the Short Wave Infrared (1.5–2.2μm). Maps of burned area have been obtained from an automatic algorithm applied to a multitemporal series of Landsat TM/ETM+ images in two Mediterranean sites. The proposed algorithm is based on two phases: the first one intends to detect the more severely burned areas and minimize commission errors. The second phase improves burned patches delimitation using a hybrid contextual algorithm based on logistic regression analysis, and tries to minimize omission errors. The algorithm was calibrated using six study sites and it was validated for the whole territory of Portugal (89,000 km 2) and for Southern California (70,000 km 2). In the validation exercise, 65 TM/ETM+ scenes for Portugal and 35 for California were used, all from the 2003 fire season. A good agreement with the official burned area perimeters was shown, with kappa values close to 0.85 and low omission and commission errors (< 16.5%). The proposed algorithm could be operationally used for historical mapping of burned areas from Landsat images, as well as from future medium resolution sensors, providing they acquire images in two bands of the Short Wave Infrared (1.5–2.2 μm). ► Burned area maps were generated from automatic processing of Landsat TM/ETM+ images. ► Algorithm was applied to 65 TM/ETM+ scenes in Portugal and 35 in California. ► Kappa values were close to 0.85, with low omission and commission errors (< 16.5%). |
| Author | Chuvieco, Emilio Bastarrika, Aitor Martín, M. Pilar |
| Author_xml | – sequence: 1 givenname: Aitor surname: Bastarrika fullname: Bastarrika, Aitor organization: Department of Surveying Engineering, University of the Basque Country, Spain – sequence: 2 givenname: Emilio surname: Chuvieco fullname: Chuvieco, Emilio email: emilio.chuvieco@uah.es organization: Department of Geography, University of Alcalá, Spain – sequence: 3 givenname: M. Pilar surname: Martín fullname: Martín, M. Pilar organization: Center of Human and Social Sciences, National Research Council (CSIC), Spain |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23884749$$DView record in Pascal Francis |
| BookMark | eNqNkU1v1DAQhi1UJLaFH8DNFwQSytafsQMnqMqHtCsuy9ma2E7rVRIHO8uq_x5HWzhwWDhZYz3vaOaZS3QxxtEj9JKSNSW0vt6vU_ZrRpaarQmRT9CKatVURBFxgVaEcFEJJtUzdJnznhAqtaIrlLcwTWG8w-0hjd5hSB4y7lIc8AZGl2HGu-317W77FjuYAR_DfI8Bz8dYTfeQPYb-LqbyObzDH6GH0S7N4hByDnHEpQW2cfhd-pRiys_R0w767F88vlfo-6fb3c2XavPt89ebD5vKcs1lRRvatrzRTltOwXedsx0BLYE7WZOmbi2VzitWd4IKZZUXRFnZEQtMtJI7foXYqe9hnODhCH1vphQGSA-GErNoM3tTtJlFm6HMFG0l9PoUmlL8cfB5NmV46_uymo-HbHRNuFJK80K-OUtSRQljNePi32gtqeCc0wV99YhCttB3aVGa_wzOuNZCiaZw6sTZFHNOvjM2zDAXy3OC0J_dkP6V_B8r708ZX-71M_hksg1-tN6F5O1sXAxn0r8AFqzQ7w |
| CODEN | RSEEA7 |
| CitedBy_id | crossref_primary_10_2478_s13533_012_0167_y crossref_primary_10_3390_rs6065480 crossref_primary_10_1016_j_jag_2022_103120 crossref_primary_10_1088_1742_6596_1528_1_012048 crossref_primary_10_1071_WF20072 crossref_primary_10_1080_01431161_2020_1823039 crossref_primary_10_3390_rs13071345 crossref_primary_10_1109_TGRS_2020_3004353 crossref_primary_10_5194_nhess_14_1017_2014 crossref_primary_10_1007_s00267_016_0715_1 crossref_primary_10_1016_j_rse_2016_01_023 crossref_primary_10_1016_j_rse_2015_01_022 crossref_primary_10_1002_widm_1522 crossref_primary_10_1016_j_envsci_2024_103818 crossref_primary_10_1080_01431161_2013_816452 crossref_primary_10_3390_rs61212360 crossref_primary_10_1016_j_rsase_2024_101153 crossref_primary_10_1007_s11069_015_2115_x crossref_primary_10_3390_rs14194714 crossref_primary_10_1016_j_isprsjprs_2018_05_007 crossref_primary_10_1016_j_jag_2019_102011 crossref_primary_10_3390_rs13091623 crossref_primary_10_3390_rs4020424 crossref_primary_10_1029_2023WR036450 crossref_primary_10_1109_LGRS_2011_2167953 crossref_primary_10_1007_s10661_021_09494_0 crossref_primary_10_1186_s13021_015_0029_2 crossref_primary_10_3390_rs16101749 crossref_primary_10_4995_raet_2018_8618 crossref_primary_10_1088_1742_6596_1577_1_012017 crossref_primary_10_3390_rs11222695 crossref_primary_10_1111_risa_13524 crossref_primary_10_3390_rs6021654 crossref_primary_10_3390_rs9111193 crossref_primary_10_3390_rs12111862 crossref_primary_10_1016_j_rse_2021_112649 crossref_primary_10_3390_f13111787 crossref_primary_10_3390_rs13132492 crossref_primary_10_1109_JSTARS_2016_2575366 crossref_primary_10_1016_j_rse_2014_01_008 crossref_primary_10_3390_rs11030326 crossref_primary_10_1016_j_scitotenv_2019_133603 crossref_primary_10_1007_s10651_023_00590_7 crossref_primary_10_1016_j_isprsjprs_2024_08_019 crossref_primary_10_1016_j_rse_2019_111493 crossref_primary_10_3390_rs17050830 crossref_primary_10_3390_land12020379 crossref_primary_10_1007_s40333_021_0008_2 crossref_primary_10_1016_j_foreco_2017_05_021 crossref_primary_10_1016_j_scitotenv_2017_05_194 crossref_primary_10_3390_rs13214298 crossref_primary_10_1016_j_rse_2014_02_001 crossref_primary_10_1109_TGRS_2021_3110280 crossref_primary_10_3390_s20185423 crossref_primary_10_1016_j_ecoinf_2024_102591 crossref_primary_10_1016_j_csr_2015_10_009 crossref_primary_10_3390_rs11222669 crossref_primary_10_3390_rs13040816 crossref_primary_10_3390_rs9050486 crossref_primary_10_3390_rs11050489 crossref_primary_10_3390_ijgi10080546 crossref_primary_10_1016_j_swevo_2017_11_003 crossref_primary_10_1080_19475705_2023_2190856 crossref_primary_10_1016_j_rse_2012_12_004 crossref_primary_10_1080_01431161_2015_1070322 crossref_primary_10_1016_j_rse_2019_111288 crossref_primary_10_1007_s10661_024_13095_y crossref_primary_10_1016_j_rse_2019_02_013 crossref_primary_10_1080_22797254_2019_1581583 crossref_primary_10_1016_j_rse_2023_113522 crossref_primary_10_1016_j_jag_2017_09_011 crossref_primary_10_1016_j_rse_2022_113203 crossref_primary_10_3390_rs8010044 crossref_primary_10_1016_j_jhydrol_2019_03_103 crossref_primary_10_3390_fire4030034 crossref_primary_10_3389_ffgc_2022_1052299 crossref_primary_10_1016_j_rsase_2017_02_001 crossref_primary_10_3390_ijgi9100564 crossref_primary_10_26833_ijeg_455595 crossref_primary_10_1016_j_rse_2014_03_021 crossref_primary_10_1016_j_isprsjprs_2021_01_015 crossref_primary_10_1016_j_rsase_2016_07_002 crossref_primary_10_2111_REM_D_13_00078_1 crossref_primary_10_1016_j_rse_2017_06_025 crossref_primary_10_3390_rs6010470 crossref_primary_10_1016_j_rse_2022_113298 crossref_primary_10_1016_j_rse_2017_06_027 crossref_primary_10_1016_j_rse_2023_113753 crossref_primary_10_1016_j_engappai_2024_108280 crossref_primary_10_3390_rs11020104 crossref_primary_10_4995_raet_2020_13082 crossref_primary_10_3390_rs70201320 crossref_primary_10_1016_j_rse_2019_02_004 crossref_primary_10_3390_rs11060622 crossref_primary_10_3390_rs10081196 crossref_primary_10_1071_WF23020 crossref_primary_10_1016_j_jag_2014_10_009 crossref_primary_10_1071_WF22050 crossref_primary_10_1109_TGRS_2011_2128327 crossref_primary_10_1016_j_jhydrol_2016_03_034 crossref_primary_10_3390_rs14133122 crossref_primary_10_1016_j_scitotenv_2015_02_081 crossref_primary_10_3390_rs14174354 crossref_primary_10_3390_rs13081509 crossref_primary_10_3390_rs13112214 crossref_primary_10_14358_PERS_21_00057R2 crossref_primary_10_1080_01431161_2014_883091 crossref_primary_10_3390_rs12040674 crossref_primary_10_1080_17538947_2021_1962994 crossref_primary_10_3390_rs16132500 crossref_primary_10_1016_j_rse_2019_111340 crossref_primary_10_1029_2020EF001960 crossref_primary_10_1016_j_rse_2013_02_019 crossref_primary_10_3390_rs6109873 crossref_primary_10_1007_s11676_018_0669_7 crossref_primary_10_1016_j_jag_2017_02_003 crossref_primary_10_1016_j_jsames_2021_103179 crossref_primary_10_1016_j_rse_2019_111345 crossref_primary_10_1016_j_rse_2021_112575 crossref_primary_10_1088_1742_6596_801_1_012045 crossref_primary_10_1109_JSTARS_2013_2292853 crossref_primary_10_1016_j_isprsjprs_2019_12_014 crossref_primary_10_5194_essd_12_3229_2020 crossref_primary_10_3390_rs13020220 crossref_primary_10_1109_LGRS_2015_2441135 crossref_primary_10_3390_land12051087 crossref_primary_10_1051_matecconf_201822904012 crossref_primary_10_1080_17445647_2012_743866 crossref_primary_10_3390_rs13245131 crossref_primary_10_3390_app12010009 crossref_primary_10_1016_j_isprsjprs_2019_11_026 crossref_primary_10_1117_1_JRS_12_026026 crossref_primary_10_3390_rs9070743 crossref_primary_10_5721_EuJRS20164945 crossref_primary_10_1016_j_rse_2017_10_009 crossref_primary_10_1016_j_ecolind_2020_106151 crossref_primary_10_3390_rs12172681 crossref_primary_10_1016_j_jenvman_2017_03_058 crossref_primary_10_30897_ijegeo_1516280 crossref_primary_10_3390_rs6031803 crossref_primary_10_3390_rs13245164 crossref_primary_10_3390_rs16203765 crossref_primary_10_1016_j_rse_2018_12_011 crossref_primary_10_1071_WF14124 crossref_primary_10_1016_j_rse_2015_03_011 crossref_primary_10_1016_j_rse_2011_06_010 crossref_primary_10_3390_rs10050750 crossref_primary_10_3390_f10050363 crossref_primary_10_3390_f14010032 crossref_primary_10_1016_j_scitotenv_2017_10_182 crossref_primary_10_3390_rs5115680 crossref_primary_10_3390_rs6032050 crossref_primary_10_1007_s11069_015_1792_9 crossref_primary_10_3390_rs14071727 crossref_primary_10_1016_j_rse_2019_111525 crossref_primary_10_1007_s10694_023_01531_3 crossref_primary_10_1590_0102_77863220004 crossref_primary_10_1117_1_JRS_11_046023 crossref_primary_10_1007_s11769_024_1432_y crossref_primary_10_3390_rs11091074 crossref_primary_10_3390_rs13091608 crossref_primary_10_1088_1755_1315_622_1_012021 crossref_primary_10_3390_rs10060940 crossref_primary_10_3390_rs14030657 crossref_primary_10_5194_essd_10_2015_2018 crossref_primary_10_3390_rs11222638 crossref_primary_10_3390_rs6021275 crossref_primary_10_1016_j_rse_2015_01_005 crossref_primary_10_1071_WF17069 crossref_primary_10_1016_j_rsase_2023_101020 crossref_primary_10_4996_fireecology_1101055 crossref_primary_10_3390_rs15061489 crossref_primary_10_3390_rs4030726 crossref_primary_10_1016_j_isprsjprs_2012_03_001 crossref_primary_10_1016_j_apgeog_2022_102854 |
| ContentType | Journal Article |
| Copyright | 2010 Elsevier Inc. 2015 INIST-CNRS |
| Copyright_xml | – notice: 2010 Elsevier Inc. – notice: 2015 INIST-CNRS |
| DBID | AAYXX CITATION IQODW 7SU 8FD C1K FR3 H8D KR7 L7M 7S9 L.6 7SN 7ST F1W H96 L.G SOI ADTOC UNPAY |
| DOI | 10.1016/j.rse.2010.12.005 |
| DatabaseName | CrossRef Pascal-Francis Environmental Engineering Abstracts Technology Research Database Environmental Sciences and Pollution Management Engineering Research Database Aerospace Database Civil Engineering Abstracts Advanced Technologies Database with Aerospace AGRICOLA AGRICOLA - Academic Ecology Abstracts Environment Abstracts ASFA: Aquatic Sciences and Fisheries Abstracts Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources Aquatic Science & Fisheries Abstracts (ASFA) Professional Environment Abstracts Unpaywall for CDI: Periodical Content Unpaywall |
| DatabaseTitle | CrossRef Aerospace Database Civil Engineering Abstracts Technology Research Database Environmental Engineering Abstracts Engineering Research Database Advanced Technologies Database with Aerospace Environmental Sciences and Pollution Management AGRICOLA AGRICOLA - Academic Aquatic Science & Fisheries Abstracts (ASFA) Professional Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources Ecology Abstracts Environment Abstracts ASFA: Aquatic Sciences and Fisheries Abstracts |
| DatabaseTitleList | Aquatic Science & Fisheries Abstracts (ASFA) Professional AGRICOLA Aerospace Database |
| Database_xml | – sequence: 1 dbid: UNPAY name: Unpaywall url: https://proxy.k.utb.cz/login?url=https://unpaywall.org/ sourceTypes: Open Access Repository |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Geography Geology Environmental Sciences |
| EISSN | 1879-0704 |
| EndPage | 1012 |
| ExternalDocumentID | oai:zenodo.org:3422189 23884749 10_1016_j_rse_2010_12_005 S0034425710003433 |
| GeographicLocations | Iberian Peninsula Southern California United States Europe Southern Europe California Portugal ANE, Portugal MED, Western Mediterranean INE, USA, California |
| GeographicLocations_xml | – name: California – name: Portugal – name: INE, USA, California – name: ANE, Portugal – name: MED, Western Mediterranean |
| GroupedDBID | --K --M -~X .DC .~1 0R~ 123 1B1 1RT 1~. 1~5 29P 4.4 41~ 457 4G. 53G 5VS 6TJ 7-5 71M 8P~ 9JM 9JN AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXUO ABEFU ABFNM ABFYP ABJNI ABLST ABMAC ABPPZ ABQEM ABQYD ABXDB ABYKQ ACDAQ ACGFS ACIWK ACLVX ACPRK ACRLP ACSBN ADBBV ADEZE ADMUD AEBSH AEKER AENEX AFFNX AFKWA AFRAH AFTJW AFXIZ AGHFR AGUBO AGYEJ AHEUO AHHHB AIEXJ AIKHN AITUG AJBFU AJOXV AKIFW ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ ASPBG ATOGT AVWKF AXJTR AZFZN BKOJK BLECG BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 FA8 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q G8K GBLVA HMA HMC HVGLF HZ~ H~9 IHE IMUCA J1W KCYFY KOM LY3 LY9 M41 MO0 N9A O-L O9- OAUVE OHT OZT P-8 P-9 P2P PC. Q38 R2- RIG RNS ROL RPZ SDF SDG SDP SEN SEP SES SEW SPC SPCBC SSE SSJ SSZ T5K TN5 TWZ VOH WH7 WUQ XOL ZCA ZMT ~02 ~G- ~KM AAHBH AATTM AAXKI AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO ADVLN AEIPS AEUPX AFPUW AIIUN AKBMS AKRWK AKYEP ANKPU CITATION EFKBS ~HD ABDPE ADXHL AEGFY AFJKZ AGCQF AGQPQ AGRNS AIGII APXCP BNPGV IQODW SSH 7SU 8FD ABUFD C1K FR3 H8D KR7 L7M 7S9 L.6 7SN 7ST F1W H96 L.G SOI ADTOC UNPAY |
| ID | FETCH-LOGICAL-c3835-191bb398d8c31aeffdcf0a85a3d56096bc15de726f4147c7e407c5f0ca24b53d3 |
| IEDL.DBID | .~1 |
| ISSN | 0034-4257 1879-0704 |
| IngestDate | Sun Oct 26 03:35:23 EDT 2025 Tue Oct 07 09:20:14 EDT 2025 Sun Sep 28 03:24:54 EDT 2025 Tue Oct 07 09:51:41 EDT 2025 Mon Jul 21 09:17:40 EDT 2025 Thu Apr 24 22:53:47 EDT 2025 Wed Oct 01 02:18:03 EDT 2025 Fri Feb 23 02:25:46 EST 2024 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 4 |
| Keywords | Logistic regression Landsat TM/ETM+ images Contextual algorithms Burned areas Burned ground algorithms detection Thematic Mapper maps Space remote sensing Landsat regression analysis cartography North America Landsat satellite fires Fire Mediterranean region Multidate observation errors |
| Language | English |
| License | https://www.elsevier.com/tdm/userlicense/1.0 CC BY 4.0 other-oa |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c3835-191bb398d8c31aeffdcf0a85a3d56096bc15de726f4147c7e407c5f0ca24b53d3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| OpenAccessLink | https://proxy.k.utb.cz/login?url=https://zenodo.org/record/3422189 |
| PQID | 1651433314 |
| PQPubID | 23500 |
| PageCount | 10 |
| ParticipantIDs | unpaywall_primary_10_1016_j_rse_2010_12_005 proquest_miscellaneous_860377783 proquest_miscellaneous_1710226234 proquest_miscellaneous_1651433314 pascalfrancis_primary_23884749 crossref_citationtrail_10_1016_j_rse_2010_12_005 crossref_primary_10_1016_j_rse_2010_12_005 elsevier_sciencedirect_doi_10_1016_j_rse_2010_12_005 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 20110415 |
| PublicationDateYYYYMMDD | 2011-04-15 |
| PublicationDate_xml | – month: 04 year: 2011 text: 20110415 day: 15 |
| PublicationDecade | 2010 |
| PublicationPlace | New York, NY |
| PublicationPlace_xml | – name: New York, NY |
| PublicationTitle | Remote sensing of environment |
| PublicationYear | 2011 |
| Publisher | Elsevier Inc Elsevier |
| Publisher_xml | – name: Elsevier Inc – name: Elsevier |
| References | Key, Benson (bb0095) 1999 Pereira, Setzer (bb0150) 1993; 14 Chuvieco (bb0030) 2008 Pinty, Verstraete (bb0165) 1992; 101 Rydberg, Borgefors (bb0230) 2001; 39 Smith, Drake, Wooster, Hudak, Holden, Gibbons (bb0245) 2007; 28 Martín, M.P. (1998). Cartografía e inventario de incendios forestales en la Península Ibérica a partir de imágenes NOAA-AVHRR. Ph.D. dissertation Universidad de Alcalá, Alcalá de Henares Palacios-Orueta, Chuvieco, Parra, Carmona-Moreno (bb0135) 2005; 104 Breiman, Friedman, Olshen, Stone (bb0020) 1984 Koutsias, Karteris (bb0105) 2000; 21 Riaño, Ruiz, Isidoro, Ustin, Riaño (bb0185) 2007; 13 Chander, Markham, Helder (bb0025) 2009; 113 Silva, Cadima, Pereira, Gregoire (bb0235) 2004; 25 Garcia, Chuvieco (bb0070) 2004; 92 Martín, Gómez, Chuvieco (bb0125) 2005 Roy, Boschetti, Justice (bb0215) 2008; 112 Russel-Smith, Ryan, Cheal (bb0225) 2002; 104 Pu, Gong (bb0170) 2004; 70 Kasischke, French (bb0090) 1995; 51 Smith, Wooster, Powell, Usher (bb0240) 2002; 23 Barbosa, Gregoire, Pereira (bb0015) 1999; 69 Chuvieco, Englefield, Trishchenko, Luo (bb0050) 2008; 112 Homer, Dewitz, Fry, Coan, Hossain, Larson (bb0080) 2007; 73 Chuvieco, Riaño, Danson, Martín (bb0045) 2006; 111 Mitri, Gitas (bb0130) 2004; 25 Trigg, Flasse (bb0265) 2001; 22 Roy, Boschetti (bb0205) 2009; 47 Global Climate Observing System (GCOS) (bb0075) 2006 Chuvieco, Congalton (bb0035) 1988; 4 Pavlidis, Liow (bb0140) 1990; 12 Pereira, Sa, Sousa, Martín, Chuvieco (bb0155) 1999 Vafeidis, Drake (bb0270) 2005; 26 Chuvieco, Opazo, Sione, Del Valle, Anaya, Di Bella (bb0055) 2008; 18 Randerson, van der Werf, Collatz, Giglio, Still, Kasibhatla (bb0180) 2005 Fernández, Illera, Casanova (bb0060) 1997; 60 Baraldi, Parmiggiani (bb0010) 1996; 34 Tansey, Grégoire, Defourny, Leigh, Peckel, Bogaert (bb0250) 2008; 35 Maggi, Stroppiana (bb0115) 2002; 28 Quintano, Fernández-Manso, Fernández-Manso, Shimabukuro (bb0175) 2006; 27 Koutsias, Karteris (bb0100) 1998; 19 Russel-Smith, Ryan, Durieu (bb0220) 1997; 35 Adams, Bischof (bb0005) 1994; 16 Fraser, Fernandes, Latifovic (bb0065) 2003; 18 Richards (bb0190) 1993 Roy, Jin, Lewis, Justice (bb0210) 2005; 97 Rouse, Haas, Schell, Deering, Harlan (bb0200) 1974 Thonicke, Spessa, Prentice, Harrison, Dong, Carmona-Moreno (bb0260) 2010; 7 Tansey, Grégoire, Defourny, Leigh, Peckel, Bogaert (bb0255) 2008; 35 Pereira, Sa, Sousa, Silva, Santos, Carreiras (bb0160) 1999 Koutsias, Karteris (bb0110) 2000; 21 Chuvieco, Martín, Palacios (bb0040) 2002; 23 Pereira (bb0145) 1999; 37 Rosenqvist, Milne, Lucas, Imhoff, Dobson (bb0195) 2003; 6 Zhang, Pavlic, Chen, Fraser, Leblanc, Cihlar (bb0275) 2005; 31 Hudak, Brockett (bb0085) 2004; 25 |
| References_xml | – volume: 104 start-page: 189 year: 2005 end-page: 209 ident: bb0135 article-title: Biomass burning emissions: A review of models using remote-sensing data publication-title: Environmental Monitoring and Assessment. Environmental Monitoring and Assessment – volume: 25 start-page: 2863 year: 2004 end-page: 2870 ident: bb0130 article-title: A performance evaluation of a burned area object-based classification model when applied to topographically and non-topographically corrected TM imagery publication-title: International Journal of Remote Sensing – volume: 7 start-page: 697 year: 2010 end-page: 743 ident: bb0260 article-title: The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: Results from a process-based model publication-title: Biogeosciences – volume: 12 start-page: 225 year: 1990 end-page: 233 ident: bb0140 article-title: Integrating region growing and edge detection publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence – start-page: 139 year: 1999 end-page: 155 ident: bb0155 article-title: Regional-scale burnt area mapping in Southern Europe using NOAA-AVHRR 1 publication-title: Remote Sensing of Large Wildfires in the European Mediterranean Basin – volume: 51 start-page: 263 year: 1995 end-page: 275 ident: bb0090 article-title: Locating and estimating the areal extent of wildfires in Alaskan boreal forests using multiple-season AVHRR NDVI composite data publication-title: Remote Sensing of Environment – volume: 35 start-page: L01401 year: 2008 ident: bb0250 article-title: A new, global, multi-annual (2000–2007) burnt area product at 1 publication-title: Geophysical Research Letters – volume: 23 start-page: 5103 year: 2002 end-page: 5110 ident: bb0040 article-title: Assessment of different spectral indices in the red-near-infrared spectral domain for burned land discriminations publication-title: International Journal of Remote Sensing – volume: 47 year: 2009 ident: bb0205 article-title: Southern Africa validation of the MODIS, L3JRC and GlobCarbon burned-area products publication-title: IEEE Transactions on Geoscience and Remote Sensing – reference: Martín, M.P. (1998). Cartografía e inventario de incendios forestales en la Península Ibérica a partir de imágenes NOAA-AVHRR. Ph.D. dissertation Universidad de Alcalá, Alcalá de Henares – volume: 92 start-page: 414 year: 2004 end-page: 423 ident: bb0070 article-title: Assessment of the potential of SAC-C/MMRS imagery for mapping burned areas in Spain publication-title: Remote Sensing of Environment – volume: 19 start-page: 3499 year: 1998 end-page: 3514 ident: bb0100 article-title: Logistic regression modelling of multitemporal Thematic Mapper data for burned area mapping publication-title: International Journal of Remote Sensing – volume: 4 start-page: 41 year: 1988 end-page: 53 ident: bb0035 article-title: Mapping and inventory of forest fires from digital processing of TM data publication-title: Geocarto International – volume: 112 start-page: 3690 year: 2008 end-page: 3707 ident: bb0215 article-title: The collection 5 MODIS burned area product — Global evaluation by comparison with the MODIS active fire product publication-title: Remote Sensing of Environment – volume: 13 start-page: 40 year: 2007 end-page: 50 ident: bb0185 article-title: Global spatial patterns and temporal trends of burned area between 1981 and 2000 using NOAA-NASA Pathfinder publication-title: Global Change Biology – volume: 35 year: 2008 ident: bb0255 article-title: A new, global, multi-annual (2000–2007) burnt area product at 1 publication-title: Geophysical Research Letters – volume: 111 year: 2006 ident: bb0045 article-title: Use of a radiative transfer model to simulate the post-fire spectral response to burn severity publication-title: Journal of Geophysical Research - Biosciences – volume: 97 start-page: 137 year: 2005 end-page: 162 ident: bb0210 article-title: Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data publication-title: Remote Sensing of Environment – volume: 37 start-page: 217 year: 1999 end-page: 226 ident: bb0145 article-title: A comparative evaluation of NOAA/AVHRR vegetation indexes for burned surface detection and mapping publication-title: IEEE Transactions on Geoscience and Remote Sensing – volume: 22 start-page: 2641 year: 2001 end-page: 2647 ident: bb0265 article-title: An evaluation of different bi-spectral spaces for discriminating burned shrub-savannah publication-title: International Journal of Remote Sensing – volume: 31 start-page: 289 year: 2005 end-page: 296 ident: bb0275 article-title: A semi-automatic segmentation procedure for feature extraction in remotely sensed imagery publication-title: Computers and Geosciences – volume: 101 start-page: 15 year: 1992 end-page: 20 ident: bb0165 article-title: GEMI: a non-linear index to monitor global vegetation from satellites publication-title: Vegetatio – volume: 28 start-page: 2753 year: 2007 end-page: 2775 ident: bb0245 article-title: Production of Landsat ETM+ reference imagery of burned areas within Southern African savannahs: comparison of methods and application to MODIS publication-title: International Journal of Remote Sensing – volume: 112 start-page: 2381 year: 2008 end-page: 2396 ident: bb0050 article-title: Generation of long time series of burn area maps of the boreal forest from NOAA–AVHRR composite data publication-title: Remote Sensing of Environment – year: 2006 ident: bb0075 publication-title: Systematic Observation Requirements for Satellite-based products for Climate – Supplemental Details to the GCOS Implementation Plan – volume: 104 start-page: 91 year: 2002 end-page: 106 ident: bb0225 article-title: Fire regimes and the conservation of sandstone heath in monsoonal northern Australia: Frequency, interval, patchiness publication-title: Biological Conservation – volume: 39 start-page: 2514 year: 2001 end-page: 2520 ident: bb0230 article-title: Integrated method for boundary delineation of agricultural fields in multispectral satellite images publication-title: IEEE Transactions on Geoscience and Remote Sensing – start-page: 193 year: 2005 end-page: 198 ident: bb0125 article-title: Performance of a burned-area index (BAIM) for mapping Mediterranean burned scars from MODIS data publication-title: Proceedings of the 5th International Workshop on Remote Sensing and GIS applications to Forest Fire Management: Fire Effects Assessment – volume: 14 start-page: 2061 year: 1993 end-page: 2078 ident: bb0150 article-title: Spectral characteristics of fire scars in Landsat-5 TM images of Amazonia publication-title: International Journal of Remote Sensing – volume: 18 start-page: 37 year: 2003 end-page: 47 ident: bb0065 article-title: Multi-temporal mapping of burned forest over Canada using satellite-based change metrics publication-title: Geocarto International – volume: 21 start-page: 673 year: 2000 end-page: 687 ident: bb0105 article-title: Burned area mapping using logistic regression modeling of a single post-fire Landsat-5 Thematic Mapper image publication-title: International Journal of Remote Sensing – volume: 73 start-page: 337 year: 2007 end-page: 341 ident: bb0080 article-title: Completion of the 2001 National Land Cover Database for the Conterminous United States publication-title: Photogrammetric Engineering and Remote Sensing – volume: 69 start-page: 253 year: 1999 end-page: 263 ident: bb0015 article-title: An algorithm for extracting burned areas from time series of AVHRR GAC data applied at a continental scale – An overview publication-title: Remote Sensing of Environment – volume: 18 start-page: 64 year: 2008 end-page: 79 ident: bb0055 article-title: Global Burned Land Estimation in Latin America using MODIS Composite Data publication-title: Ecological Applications – volume: 25 start-page: 4889 year: 2004 end-page: 4913 ident: bb0235 article-title: Assessing the feasibility of a global model for multi-temporal burned area mapping using SPOT-VEGETATION data publication-title: International Journal of Remote Sensing – year: 1993 ident: bb0190 article-title: Remote Sensing Digital Image Analysis. An Introduction – volume: 23 start-page: 1733 year: 2002 end-page: 1739 ident: bb0240 article-title: Texture based feature extraction: application to burn scar detection in Earth observation satellite sensor imagery publication-title: International Journal of Remote Sensing – volume: 26 start-page: 2441 year: 2005 end-page: 2459 ident: bb0270 article-title: A two-step method for estimating the extent of burnt areas with the use of coarse-resolution data publication-title: International Journal of Remote Sensing – year: 1974 ident: bb0200 publication-title: Monitoring the vernal advancement and retrogradation (Greenwave effect) of natural vegetation – volume: 70 start-page: 841 year: 2004 end-page: 850 ident: bb0170 article-title: Determination of burnt scars using logistic regression and neural network techniques from a single post-fire Landsat-7 ETM+ image publication-title: Photogrammetric Engineering and Remote Sensing – volume: 113 start-page: 893 year: 2009 end-page: 903 ident: bb0025 article-title: Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors publication-title: Remote Sensing of Environment – volume: 25 start-page: 3231 year: 2004 end-page: 3243 ident: bb0085 article-title: Mapping fire scars in a southern African savannah using Landsat imagery publication-title: International Journal of Remote Sensing – start-page: 109 year: 2008 end-page: 142 ident: bb0030 article-title: Satellite observation of biomass burning: implications in global change research publication-title: Earth Observation and Global Change – volume: 35 start-page: 829 year: 1997 end-page: 846 ident: bb0220 article-title: A Landsat MSS-derived fire history of Kakadu National Park, monsoonal northern Australia 1980–94: seasonal extent, frequency and patchiness publication-title: Journal of Applied Ecology – volume: 16 start-page: 641 year: 1994 end-page: 647 ident: bb0005 article-title: Seeded region growing publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence – volume: 6 start-page: 441 year: 2003 end-page: 445 ident: bb0195 article-title: A review of remote sensing technology in support of the Kyoto Protocol publication-title: Environmental Science & Policy – volume: 34 start-page: 137 year: 1996 end-page: 148 ident: bb0010 article-title: Single linkage region growing algorithms based on the vector degree of match publication-title: IEEE Transactions on Geoscience and Remote Sensing – volume: 60 start-page: 153 year: 1997 end-page: 162 ident: bb0060 article-title: Automatic mapping of surfaces affected by forest fires in Spain using AVHRR NDVI composite image data publication-title: Remote Sensing of Environment – year: 2005 ident: bb0180 article-title: Fire emissions from C3 and C 4 vegetation and their influence on interannual variability of atmospheric CO2 and D13 CO2 publication-title: Global Biogeochemical Cycles – volume: 21 start-page: 673 year: 2000 end-page: 687 ident: bb0110 article-title: Burned area mapping using logistic regression modeling of a single post-fire Landsat-5 Thematic Mapper image publication-title: International Journal of Remote Sensing – volume: 28 start-page: 231 year: 2002 end-page: 245 ident: bb0115 article-title: Advantages and drawbacks of NOAA-AVHRR and SPOT-VGT for burnt area mapping in a tropical savanna ecosystem publication-title: Canadian Journal of Remote Sensing – year: 1999 ident: bb0095 article-title: The Normalized Burn Ratio (NBR): A Landsat TM radiometric measure of burn severity – volume: 27 start-page: 645 year: 2006 end-page: 662 ident: bb0175 article-title: Mapping burned areas in Mediterranean countries using spectral mixture analysis from a uni-temporal perspective publication-title: International Journal of Remote Sensing – start-page: 123 year: 1999 end-page: 138 ident: bb0160 article-title: Spectral characterisation and discrimination of burnt areas publication-title: Remote Sensing of Large Wildfires in the European Mediterranean Basin – year: 1984 ident: bb0020 article-title: Classification and regression trees |
| SSID | ssj0015871 |
| Score | 2.477023 |
| Snippet | Maps of burned area have been obtained from an automatic algorithm applied to a multitemporal series of Landsat TM/ETM+ images in two Mediterranean sites. The... |
| SourceID | unpaywall proquest pascalfrancis crossref elsevier |
| SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 1003 |
| SubjectTerms | Algorithms Animal, plant and microbial ecology Applied geophysics Biological and medical sciences Burned areas California Combustion Contextual algorithms Earth sciences Earth, ocean, space Error detection Errors Exact sciences and technology fire season Fundamental and applied biological sciences. Psychology General aspects. Techniques Internal geophysics Landsat Landsat TM/ETM+ images Logistic regression Mapping Portugal regression analysis remote sensing Southern California Teledetection and vegetation maps |
| SummonAdditionalLinks | – databaseName: Unpaywall dbid: UNPAY link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3db9MwELdGJ7RJiI_CRPmYPIknpow4dhyHt4E6JkQnHlppPFn-3ARdUiWtpu6v59wkHUNQxGOSsyP7zrrfne8DoTdeg1IUXEQ2T0zELBGRVrGOSO5JpjU31od859EZP52wz-fp-RY66HJhblwB5tjqCr_tiUZZAmoov4e2eQpwu4e2J2dfj7815RZZxJpqnqFpdgTiy7qby1UMV1W7JnorePxCh7o_654HM1XDjvimlcUdrLmzKGZqea2m01_Uzsmj2-SdJtrkx9Firo_MzW-1HDeu6DF62IJOfNxIyRO05Yo-2hve5rjBx_aQ13200zZGv1z20f1Pq86_y6eoHqlQyuEC6-AFtViFaHYcslPwl5AurOZ4PHo3HI8OcYg6xcHBixWeX5fR7BJUJVbTi7KCl1fv8YcQT2nCZCWIWfDXYZgCg_B3j66qyqp-hiYnw_HH06jt2BAZsHRT4DDRmubCCkOJct5b42MlUkUtIKuca0NS67KEe0ZYZjIH5qRJfWxUwnRKLd1DvaIs3HOEiRVg6nDQpYljnnFhPBirTMSa-zinYoDijpfStOXMQ1eNqezi1r5LYL8M7JckkcD-AXq7HjJranlsImadgMgWjDQgQ4Ku2TRs_44wrX8E0AiAAMsH6KCTLgl7Gq5nVOHKRS0JD-CVUsI20ARAmABkBRr8FxrBY5plmaADdLiW3n8v-MV_Ub9Eu413nUUkfYV682rhXgM8m-v99oD-BAAhN6E priority: 102 providerName: Unpaywall |
| Title | Mapping burned areas from Landsat TM/ETM+ data with a two-phase algorithm: Balancing omission and commission errors |
| URI | https://dx.doi.org/10.1016/j.rse.2010.12.005 https://www.proquest.com/docview/1651433314 https://www.proquest.com/docview/1710226234 https://www.proquest.com/docview/860377783 https://zenodo.org/record/3422189 |
| UnpaywallVersion | submittedVersion |
| Volume | 115 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Baden-Württemberg Complete Freedom Collection (Elsevier) customDbUrl: eissn: 1879-0704 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0015871 issn: 0034-4257 databaseCode: GBLVA dateStart: 20110101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Elsevier SD Complete Freedom Collection [SCCMFC] customDbUrl: eissn: 1879-0704 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0015871 issn: 0034-4257 databaseCode: ACRLP dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals [SCFCJ] customDbUrl: eissn: 1879-0704 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0015871 issn: 0034-4257 databaseCode: AIKHN dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Science Direct customDbUrl: eissn: 1879-0704 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0015871 issn: 0034-4257 databaseCode: .~1 dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVLSH databaseName: Elsevier Journals customDbUrl: mediaType: online eissn: 1879-0704 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0015871 issn: 0034-4257 databaseCode: AKRWK dateStart: 19930101 isFulltext: true providerName: Library Specific Holdings |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnR1db9Mw0JqG0JDQBIVpZVAZiSem0Dh2Eoe3MnWUj1Y8tNJ4imwn3oZKEiWtpr7w27nLR6ESFImnKMnZiX1n34fvg5BXVgNTlIF0ksgzjkiYdLRytcMiy0KtA5NYjHeezoLJQny88q8OyEUXC4Nule3e3-zp9W7dPhm2szksbm8xxpcLpDhWJ1nhmPFTiBCrGLz5sXXzYL4Mm6p5XDgI3Z1s1j5eZZU23l1oEcQKdn_mTQ8LVcGM2abUxY4serTOCrW5U8vlb2zp8hE5buVJOmp--TE5SLMeORn_Cl-Dl-36rXrkqK15frPpkfvv66K-myekmirM0nBNNRo4E6rQUZ1i4An9jJHAakXn0-F4Pj2n6FBK0XZLFV3d5U5xA1yQquV1XsLD72_pO3SVNNhZDhSEpjgKXVCY3u42Lcu8rJ6SxeV4fjFx2mIMjgEl1gfkMa15JBNpOFOptYmxrpK-4gkITVGgDfOTNPQCK5gITZiCpmh86xrlCe3zhJ-QwyzP0lNCWSJBiwmATXqpsCKQxoIeKqSrA-tGXPaJ26EhNm2mciyYsYw7l7RvMWAuRszFzIsBc33yetukaNJ07AMWHW7jHVqLgY3sazbYoYPth0DqAR4voj552RFGDHOKJy8qS_N1FbMA5VLOmdgDg7KeB9IowNC_wMjA5WEYSt4n51vC-_eAn_3fgM_Ig8aCLhzmPyeHq3KdvgARbKUH9RobkHujD58mM7guZl9GX38CkrExTg |
| linkProvider | Elsevier |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnR1db9Mw0BpDqEgIQWGiA4aReGIKjWMncXiDqaNAs6dO2ptlO_E-1DVV0mrqC7-du3wUKkGReIxzduK7s-_Ddz5C3jkDQlFG0suSwHoiY9Iz2jceSxyLjYls5jDfOT2Lxufi20V4sUdOulwYDKts9_5mT69367Zl2GJzuLi-xhxfLpDjWH3JCuf3yH0RBjFaYB9-bOI8WCjjpmweFx6Cd0ebdZBXWeVNeBe6BLGE3Z-F06OFrgBlrql1saWM9lbzhV7f6dnsN7l0-oQ8bhVK-qn556dkL5_3ycHoV_4avGwXcNUnvbbo-dW6Tx58qav6rp-RKtV4TcMlNejhzKjGSHWKmSd0gqnAekmn6XA0TY8pRpRSdN5STZd3hbe4AjFI9eyyKKHx9iP9jLGSFgcrgIXQF0dhCAr47R7zsizK6jk5Px1NT8ZeW43Bs2DFhkA9ZgxPZCYtZzp3LrPO1zLUPAOtKYmMZWGWx0HkBBOxjXMwFW3ofKsDYUKe8QOyPy_m-QtCWSbBjIlATga5cCKS1oEhKqRvIucnXA6I35FB2faqcqyYMVNdTNqNAsoppJxigQLKDcj7TZdFc0_HLmDR0VZtMZsCObKr29EWH2w-BGoPCHmRDMjbjjEU4BSPXvQ8L1aVYhEqppwzsQMGlb0A1FGAoX-BkZHP4ziWfECON4z37wkf_t-E35DeeJpO1OTr2feX5GHjThceC1-R_WW5yl-DPrY0R_V6-wnN8jEz |
| linkToUnpaywall | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3db9MwELdGJ7RJiI_CRPmYPIknpow4dhyHt4E6JkQnHlppPFn-3ARdUiWtpu6v59wkHUNQxGOSsyP7zrrfne8DoTdeg1IUXEQ2T0zELBGRVrGOSO5JpjU31od859EZP52wz-fp-RY66HJhblwB5tjqCr_tiUZZAmoov4e2eQpwu4e2J2dfj7815RZZxJpqnqFpdgTiy7qby1UMV1W7JnorePxCh7o_654HM1XDjvimlcUdrLmzKGZqea2m01_Uzsmj2-SdJtrkx9Firo_MzW-1HDeu6DF62IJOfNxIyRO05Yo-2hve5rjBx_aQ13200zZGv1z20f1Pq86_y6eoHqlQyuEC6-AFtViFaHYcslPwl5AurOZ4PHo3HI8OcYg6xcHBixWeX5fR7BJUJVbTi7KCl1fv8YcQT2nCZCWIWfDXYZgCg_B3j66qyqp-hiYnw_HH06jt2BAZsHRT4DDRmubCCkOJct5b42MlUkUtIKuca0NS67KEe0ZYZjIH5qRJfWxUwnRKLd1DvaIs3HOEiRVg6nDQpYljnnFhPBirTMSa-zinYoDijpfStOXMQ1eNqezi1r5LYL8M7JckkcD-AXq7HjJranlsImadgMgWjDQgQ4Ku2TRs_44wrX8E0AiAAMsH6KCTLgl7Gq5nVOHKRS0JD-CVUsI20ARAmABkBRr8FxrBY5plmaADdLiW3n8v-MV_Ub9Eu413nUUkfYV682rhXgM8m-v99oD-BAAhN6E |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Mapping+burned+areas+from+Landsat+TM%2FETM%2B+data+with+a+two-phase+algorithm%3A+Balancing+omission+and+commission+errors&rft.jtitle=Remote+sensing+of+environment&rft.au=Bastarrika%2C+Aitor&rft.au=Chuvieco%2C+Emilio&rft.au=Mart%C3%ADn%2C+M.+Pilar&rft.date=2011-04-15&rft.pub=Elsevier+Inc&rft.issn=0034-4257&rft.eissn=1879-0704&rft.volume=115&rft.issue=4&rft.spage=1003&rft.epage=1012&rft_id=info:doi/10.1016%2Fj.rse.2010.12.005&rft.externalDocID=S0034425710003433 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0034-4257&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0034-4257&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0034-4257&client=summon |