{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T14:51:07Z","timestamp":1775141467537,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T00:00:00Z","timestamp":1643241600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The catastrophic impact of wildfires on the economy and ecosystems of Mediterranean countries in recent years, along with insufficient policies that favor disproportionally high funding for fire suppression, demand a more comprehensive understanding of fire regimes. Satellite remote sensing products support the generation of relevant burned-area (BA) information, since they provide the means for the systematic monitoring of large areas worldwide at low cost. This research study assesses the accuracy of the two publicly available MODIS BA products, MCD64A1 C6 and FireCCI51, at a national scale in a Mediterranean country. The research period covered four fire seasons, and a comparison was conducted against a higher-resolution Sentinel-2 dataset. The specific objectives were to assess their performance in detecting fire events occurring primarily in forest and semi-natural lands and to investigate their spatial and temporal uncertainties. Monthly fire observations were processed and analyzed to derive a comprehensive set of accuracy metrics. We found that fire size has an impact on their detection accuracy, with higher detection occurring in fires larger than 100 ha. Detection of smaller (&lt;100 ha) fires was favored by the 250 m FireCCI51 product, but not from MCD64A1 C6, which exhibited less than 50% detection probability in the same range. Their spatial estimates of burned area exhibited a fairly satisfactory agreement with the reference data, reaching an average of 78% in detection rate. MCD64A1 C6 exhibited a more consistent spatial performance overall and better temporal accuracy, whereas FireCCI51 did not substantially outperform the former despite its finer resolution. Additional research is required for a more rigorous assessment of the variability of these burned area products, yet this research provides further insight and has implications for their use in fire-related applications at the local to the national scale.<\/jats:p>","DOI":"10.3390\/rs14030602","type":"journal-article","created":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T22:01:57Z","timestamp":1643320917000},"page":"602","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["Assessing the Accuracy of MODIS MCD64A1 C6 and FireCCI51 Burned Area Products in Mediterranean Ecosystems"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1322-7699","authenticated-orcid":false,"given":"Thomas","family":"Katagis","sequence":"first","affiliation":[{"name":"Laboratory of Forest Management and Remote Sensing, School of Forestry and Natural Environment, Aristotle University of Thessaloniki, P.O. Box 248, 54124 Thessaloniki, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0056-5629","authenticated-orcid":false,"given":"Ioannis Z.","family":"Gitas","sequence":"additional","affiliation":[{"name":"Laboratory of Forest Management and Remote Sensing, School of Forestry and Natural Environment, Aristotle University of Thessaloniki, P.O. Box 248, 54124 Thessaloniki, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.rse.2018.08.005","article-title":"The Collection 6 MODIS burned area mapping algorithm and product","volume":"217","author":"Giglio","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_2","first-page":"101887","article-title":"A comparison of remotely-sensed and inventory datasets for burned area in Mediterranean Europe","volume":"82","author":"Turco","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"104320","DOI":"10.1016\/j.catena.2019.104320","article-title":"Fire severity and soil erosion susceptibility mapping using multi-temporal Earth Observation data: The case of Mati fatal wildfire in Eastern Attica, Greece","volume":"187","author":"Efthimiou","year":"2020","journal-title":"Catena"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1038\/s41598-017-00116-9","article-title":"On the key role of droughts in the dynamics of summer fires in Mediterranean Europe","volume":"7","author":"Turco","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1007\/s10021-017-0172-6","article-title":"Socioeconomic Factors Drive Fire-Regime Variability in the Mediterranean Basin","volume":"21","author":"Chergui","year":"2018","journal-title":"Ecosystems"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Pess\u00f4a, A.C.M., Anderson, L.O., Carvalho, N.S., Campanharo, W.A., Silva Junior, C.H.L., Rosan, T.M., Reis, J.B.C., Pereira, F.R.S., Assis, M., and Jacon, A.D. (2020). Intercomparison of burned area products and its implication for carbon emission estimations in the amazon. Remote Sens., 12.","DOI":"10.3390\/rs12233864"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"5480","DOI":"10.3390\/rs6065480","article-title":"An object-based approach for fire history reconstruction by using three generations of landsat sensors","volume":"6","author":"Katagis","year":"2014","journal-title":"Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.rse.2019.02.013","article-title":"Historical background and current developments for mapping burned area from satellite Earth observation","volume":"225","author":"Chuvieco","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"697","DOI":"10.5194\/essd-9-697-2017","article-title":"Global fire emissions estimates during 1997\u20132016","volume":"9","author":"Randerson","year":"2017","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"529","DOI":"10.5194\/essd-11-529-2019","article-title":"The Global Fire Atlas of individual fire size, duration, speed and direction","volume":"11","author":"Andela","year":"2019","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.rse.2013.12.008","article-title":"The New VIIRS 375m active fire detection data product: Algorithm description and initial assessment","volume":"143","author":"Schroeder","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_12","first-page":"64","article-title":"Ten years of global burned area products from spaceborne remote sensing\u2014A review: Analysis of user needs and recommendations for future developments","volume":"26","author":"Mouillot","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Balch, J.K., St. Denis, L.A., Mahood, A.L., Mietkiewicz, N.P., Williams, T.M., McGlinchy, J., and Cook, M.C. (2020). Fired (Fire events delineation): An open, flexible algorithm and database of us fire events derived from the modis burned area product (2001\u20132019). Remote Sens., 12.","DOI":"10.3390\/rs12213498"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2018.12.011","article-title":"Development of a Sentinel-2 burned area algorithm: Generation of a small fire database for sub-Saharan Africa","volume":"222","author":"Roteta","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"111801","DOI":"10.1016\/j.rse.2020.111801","article-title":"The Landsat Burned Area algorithm and products for the conterminous United States","volume":"244","author":"Hawbaker","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"111493","DOI":"10.1016\/j.rse.2019.111493","article-title":"A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data","volume":"236","author":"Ramo","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2007GL031567","article-title":"A new, global, multi-annual (2000\u20132007) burnt area product at 1 km resolution","volume":"35","author":"Tansey","year":"2008","journal-title":"Geophys. Res. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1007\/s11027-006-1012-8","article-title":"Establishing A Earth Observation Product Service For The Terrestrial Carbon Community: The Globcarbon Initiative","volume":"11","author":"Plummer","year":"2006","journal-title":"Mitig. Adapt. Strateg. Glob. Chang."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.rse.2015.03.011","article-title":"Global burned area mapping from ENVISAT-MERIS and MODIS active fire data","volume":"163","author":"Chuvieco","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.5194\/bg-7-1171-2010","article-title":"Assessing variability and long-term trends in burned area by merging multiple satellite fire products","volume":"7","author":"Giglio","year":"2010","journal-title":"Biogeosciences"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"180132","DOI":"10.1038\/sdata.2018.132","article-title":"FRY, a global database of fire patch functional traits derived from space-borne burned area products","volume":"5","author":"Laurent","year":"2018","journal-title":"Sci. Data"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1016\/j.rse.2016.07.022","article-title":"A MODIS-based burned area assessment for Russian croplands: Mapping requirements and challenges","volume":"184","author":"Hall","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.rse.2018.10.028","article-title":"Detection rates and biases of fire observations from MODIS and agency reports in the conterminous United States","volume":"220","author":"Fusco","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1080\/17538947.2018.1433727","article-title":"Spatial and temporal intercomparison of four global burned area products","volume":"12","author":"Humber","year":"2019","journal-title":"Int. J. Digit. Earth"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.3390\/rs6021275","article-title":"Validation of the two standard MODIS satellite burned-area products and an empirically-derived merged product in South Africa","volume":"6","author":"Tsela","year":"2014","journal-title":"Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"111490","DOI":"10.1016\/j.rse.2019.111490","article-title":"Global validation of the collection 6 MODIS burned area product","volume":"235","author":"Boschetti","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1109\/TGRS.2008.2009000","article-title":"Southern Africa Validation of the MODIS, L3JRC, and GlobCarbon Burned-Area Products","volume":"47","author":"Roy","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/j.rse.2016.09.016","article-title":"A stratified random sampling design in space and time for regional to global scale burned area product validation","volume":"186","author":"Boschetti","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"112115","DOI":"10.1016\/j.rse.2020.112115","article-title":"A comprehensive characterization of MODIS daily burned area mapping accuracy across fire sizes in tropical savannas","volume":"252","author":"Campagnolo","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"035015","DOI":"10.1088\/1748-9326\/abd3d1","article-title":"Evaluating accuracy of four MODIS-derived burned area products for tropical peatland and non-peatland fires","volume":"16","author":"Vetrita","year":"2021","journal-title":"Environ. Res. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Chen, D., Shevade, V., Baer, A., and Loboda, T.V. (2021). Missing Burns in the High Northern Latitudes: The Case for Regionally Focused Burned Area Products. Remote Sens., 13.","DOI":"10.3390\/rs13204145"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"345","DOI":"10.5721\/EuJRS20154820","article-title":"A comparison of remote sensing products and forest fire statistics for improving fire information in Mediterranean Europe","volume":"48","author":"Vilar","year":"2015","journal-title":"Eur. J. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3653","DOI":"10.1080\/01431161.2011.631950","article-title":"Comparison of burnt area estimates derived from satellite products and national statistics in Europe","volume":"33","author":"Loepfe","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"12001","DOI":"10.1088\/1755-1315\/932\/1\/012001","article-title":"Accuracy estimation of two global burned area products at national scale","volume":"932","author":"Katagis","year":"2021","journal-title":"IOP Conf. Ser. Earth Environ. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1071\/WF12003","article-title":"On the relationships between forest fires and weather conditions in Greece from long-term national observations (1894\u20132010)","volume":"22","author":"Koutsias","year":"2013","journal-title":"Int. J. Wildl. Fire"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1071\/WF18004","article-title":"Analysis of forest fire fatalities in Southern Europe: Spain, Portugal, Greece and Sardinia (Italy)","volume":"28","author":"Xanthopoulos","year":"2019","journal-title":"Int. J. Wildl. Fire"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"33","DOI":"10.3832\/ifor0817-006","article-title":"Perceptions of forest experts on climate change and fire management in European Mediterranean forests","volume":"7","author":"Raftoyannis","year":"2014","journal-title":"IForest"},{"key":"ref_38","unstructured":"San-Miguel-Ayanz, J., Durrant, T., Boca, R., Maianti, P., Libert\u00e1, G., Vivancos, T.A.-, Oom, D., Branco, A., de Rigo, D., and Ferrari, D. (2020). Forest Fires Europe Middle East and North Africa 2019, Publications Office of the European Union. EUR30402 EN."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.rse.2005.04.007","article-title":"Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data","volume":"97","author":"Roy","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1038\/s41597-019-0312-2","article-title":"A global wildfire dataset for the analysis of fire regimes and fire behaviour","volume":"6","author":"Oom","year":"2019","journal-title":"Sci. Data"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2015","DOI":"10.5194\/essd-10-2015-2018","article-title":"Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies","volume":"10","author":"Chuvieco","year":"2018","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1111\/geb.12440","article-title":"A new global burned area product for climate assessment of fire impacts","volume":"25","author":"Chuvieco","year":"2016","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_43","unstructured":"(2021, September 01). National Observatory of Forest Fires (NOFFi). Available online: http:\/\/epadap.web.auth.gr\/?lang=en."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"3229","DOI":"10.5194\/essd-12-3229-2020","article-title":"Development of a standard database of reference sites for validating global burned area products","volume":"12","author":"Franquesa","year":"2020","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_45","first-page":"221","article-title":"Automated Burned Scar Mapping Using Sentinel-2 Imagery","volume":"12","author":"Stavrakoudis","year":"2020","journal-title":"J. Geogr. Inf. Syst."},{"key":"ref_46","unstructured":"(2020, October 01). AppEEARS Team Application for Extracting and Exploring Analysis Ready Samples (AppEEARS). Ver. 2.46. NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC), USGS\/Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD, USA, Available online: https:\/\/lpdaacsvc.cr.usgs.gov\/appeears."},{"key":"ref_47","unstructured":"(2020, October 01). ESA Climate Change Initiative-Fire_cci Burned Area Dataset. Available online: https:\/\/geogra.uah.es\/fire_cci\/firecci51.php."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Melchiorre, A., Boschetti, L., Melchiorre, A., and Boschetti, L. (2018). Global Analysis of Burned Area Persistence Time with MODIS Data. Remote Sens., 10.","DOI":"10.3390\/rs10050750"},{"key":"ref_49","unstructured":"(2020, October 20). MODIS\/Terra+Aqua Land Cover Type Yearly L3 Global 500 m SIN Grid (MCD12Q1 v006), Available online: https:\/\/lpdaac.usgs.gov\/products\/mcd12q1v006\/."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.rse.2014.01.008","article-title":"Validation of the 2008 MODIS-MCD45 global burned area product using stratified random sampling","volume":"144","author":"Padilla","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Fleiss, J.L., Levin, B., and Paik, M.C. (2003). Statistical Methods for Rates and Proportions, John Wiley & Sons, Inc.","DOI":"10.1002\/0471445428"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"4181","DOI":"10.1038\/s41598-017-03739-0","article-title":"Size-dependent validation of MODIS MCD64A1 burned area over six vegetation types in boreal Eurasia: Large underestimation in croplands","volume":"7","author":"Zhu","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1071\/WF09138","article-title":"Global assessment of the temporal reporting accuracy and precision of the MODIS burned area product","volume":"19","author":"Boschetti","year":"2010","journal-title":"Int. J. Wildl. Fire"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Fornacca, D., Ren, G., and Xiao, W. (2017). Performance of Three MODIS fire products (MCD45A1, MCD64A1, MCD14ML), and ESA Fire_CCI in a mountainous area of Northwest Yunnan, China, characterized by frequent small fires. Remote Sens., 9.","DOI":"10.3390\/rs9111131"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/602\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:08:40Z","timestamp":1760134120000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/602"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,27]]},"references-count":54,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["rs14030602"],"URL":"https:\/\/doi.org\/10.3390\/rs14030602","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,27]]}}}