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An Automatic Process Chain for Detecting Burn Scars Using Sentinel-2 Data

Bettinger, Michaela and Martinis, Sandro and Plank, Simon Manuel (2019) An Automatic Process Chain for Detecting Burn Scars Using Sentinel-2 Data. South-Eastern European Journal of Earth Observation and Geomatics, pp. 1-4. Aristotle University of Thessaloniki, Greece. ISSN 2241-1224.

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The advantage of the new Sentinel-2 mission is its high geometric resolution (10 m) with a high temporal resolution (~ 5 days) at the same time. To make use of this for the monitoring of burn scars, this paper presents a new method for the automatic detection of burn scars on the basis of Sentinel-2 data. In order to develop a globally applicable method, 108 mono- and bi-temporal features of seven global distributed test sites are analysed in a discriminant analysis to examine their potential for the identification of burned areas. Based on these results, a two-phase algorithm is proposed. The first phase serves to identify seed pixels which have a high probability to be related to burned areas. Due to its simplicity, a threshold-based approach is used for this purpose. In the second phase, a refinement of the burned areas is accomplished by examining the neighbourhood of the seed pixels through a region growing method based on Support Vector Machines. The validation of the proposed approach shows encouraging high user accuracies of 95 - 99%. The producers accuracies vary between 80 - 90%.

Item URL in elib:https://elib.dlr.de/116008/
Document Type:Article
Title:An Automatic Process Chain for Detecting Burn Scars Using Sentinel-2 Data
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Martinis, SandroUNSPECIFIEDhttps://orcid.org/0000-0002-6400-361XUNSPECIFIED
Plank, Simon ManuelUNSPECIFIEDhttps://orcid.org/0000-0002-5793-052XUNSPECIFIED
Journal or Publication Title:South-Eastern European Journal of Earth Observation and Geomatics
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-4
Publisher:Aristotle University of Thessaloniki, Greece
Keywords:burn scar detection, Sentinel-2, automatic approach, rapid mapping, Support Vector Machine
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Remote Sensing and Geo Research
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Deposited By: Raettich, Michaela
Deposited On:04 Dec 2017 11:40
Last Modified:14 Jan 2022 09:20

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