{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T16:08:26Z","timestamp":1768320506425,"version":"3.49.0"},"reference-count":83,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2014,2,20]],"date-time":"2014-02-20T00:00:00Z","timestamp":1392854400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Forest fires constitute a natural disturbance factor and an agent of environmental change with local to global impacts on Earth\u2019s processes and functions. Accurate knowledge of forest fuel extent and properties can be an effective component for assessing the impacts of possible future wildfires on ecosystem services. Our study aims to evaluate and compare the spectral and spatial information inherent in the EO-1 Hyperion, Quickbird and Landsat TM imagery. The analysis was based on a support vector machine classification approach in order to discriminate and map Mediterranean fuel types. The fuel classification scheme followed a site-specific fuel model within the study area, which is suitable for fire behavior prediction and spatial simulation. The overall accuracy of the Quickbird-based fuel type mapping was higher than 74% with a quantity disagreement of 9% and an allocation disagreement of 17%. Both classifications from the Hyperion and Landsat TM fuel type maps presented approximately 70% overall accuracy and 16% allocation disagreement. The McNemar\u2019s test indicated that the overall accuracy differences between the  three produced fuel type maps were not significant (p &lt; 0.05). Based on both overall and individual higher accuracies obtained with the use of the Quickbird image, this study suggests that the high spatial resolution might be more decisive than the high spectral resolution in Mediterranean fuel type mapping.<\/jats:p>","DOI":"10.3390\/rs6021684","type":"journal-article","created":{"date-parts":[[2014,2,20]],"date-time":"2014-02-20T11:08:24Z","timestamp":1392894504000},"page":"1684-1704","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["A Comparative Analysis of EO-1 Hyperion, Quickbird and Landsat TM Imagery for Fuel Type Mapping of a Typical Mediterranean Landscape"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7123-5358","authenticated-orcid":false,"given":"Giorgos","family":"Mallinis","sequence":"first","affiliation":[{"name":"Department of Forestry and Management of the Environment and Natural Resources,  School of Agricultural Sciences and Forestry, Democritus University of Thrace,  Orestiada 68200, Greece"}]},{"given":"Georgia","family":"Galidaki","sequence":"additional","affiliation":[{"name":"Forestry and Natural Environment, School of Agriculture, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0056-5629","authenticated-orcid":false,"given":"Ioannis","family":"Gitas","sequence":"additional","affiliation":[{"name":"Forestry and Natural Environment, School of Agriculture, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2014,2,20]]},"reference":[{"key":"ref_1","first-page":"11","article-title":"Analysis of large fires in European Mediterranean landscapes: Lessons learned and perspectives","volume":"294","author":"Moreno","year":"2014","journal-title":"For. 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