Burnt Area Monthly Product - Sentinel-3 - Europe

This data set represents the monthly, accumulated results of the final (10-day) version of the fire perimeters from the "Burnt Area Daily NRT Incremental Product - Europe, Sentinel-3" dataset.

The burn perimeters are spatially and temporally correlated, so that interrelated detections from consecutive observations are combined into a single feature.

A perimeter is interpreted as belonging to a given event if a spatial overlap exists within a time frame of 15 days. Besides the geometry, attribute information is also combined while considering the size of the perimeter as a weighting factor.

Each feature contains information about the final fire perimeter, Date/Time of the first detection, and the averaged burn severity.

Date (Creation): 2022-04-01T00:00:00

Citation identifier: https://geoservice.dlr.de/catalogue/srv/metadata/c657789d-5d9f-4af1-bbfb-c20ab631726e

Presentation form: Digital map

Purpose: This dataset contains the quality enhanced burnt areas (detected using Sentinel-3 imagery) for Europe, combined for single months.

Status: ongoing

Author

German Aerospace Center (DLR) - Michael Nolde

Author

German Aerospace Center (DLR) - Florian Fichtner

Author

German Aerospace Center (DLR) - Torsten Riedlinger

Distributor

German Aerospace Center (DLR) - ( )

Maintenance and update frequency: Monthly

Keywords

opendata
Burnt Area
Sentinel-3
Europe
Near-Realtime
Burn Severity
time-series
monthly
inspireidentifiziert

GEMET - INSPIRE themes, version 1.0

Natural risk zones

Spatial scope

European

Use limitation: Nutzungseinschränkungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Use Limitations: DLR not liable for damage resulting from use.

Access constraints: Other restrictions

Other constraints: Es gelten keine Zugriffsbeschränkungen

Use constraints: Other restrictions

Other constraints: Nutzungsbedingungen: Lizenz, https://creativecommons.org/licenses/by-nc/4.0 / terms of use: https://creativecommons.org/licenses/by/4.0/

Other constraints: {"id": "cc-by/4.0",

"name": "Creative Commons Namensnennung – 4.0 International (CC BY 4.0)",

"url": " http://dcat-ap.de/def/licenses/cc-by/4.0 ",

"quelle": "Copyright DLR (year)"}

Spatial representation type: Vector

Denominator: 600000

Language: English

Character set: UTF8

Topic category

Environment

Begin date: 2016-04-01

Unique resource identifier: EPSG:3035

Topology level: Geometry only

Geometric object type: Surface

Distribution format

GeoPackage ()

OnLine resource

BURNTAREA_S3_EFR_P1M ( OGC:WMS )

WMS Access: Burnt Areas Europe Monthly

OnLine resource: https://geoservice.dlr.de/eoc/demo/wms?SERVICE=WMS%26REQUEST=GetCapabilities ( OGC:WMS-http-get-capabilities )

OnLine resource: EOC Geoservice map context ( WWW:LINK-1.0-http--link )

OnLine resource: Burnt Areas - EOC News ( WWW:LINK-1.0-http--link )

OnLine resource: UKIS Data Tutorials - Burnt Area Products ( WWW:LINK-1.0-http--link )

Hierarchy level: Series

Domain consistency

Measure identification: INSPIRE / Conformity_001

Conformance result

Date (Publication): 2010-12-08

Explanation: See the referenced specification

Pass: Yes

Statement: The product is based on mid resolution, optical data from the Sentinel-3 A/B OLCI sensor level 1 NRT product. It utilizes information from the red and near-infrared domain, in combination with thermal anomaly data from the MODIS and VIIRS sensors

Description: Burnt Area Daily NRT Processing:

Processing:

The burnt area segmentation method is based on the morphological snakes algorithm in combination with a region growing approach. A differential NDVI mosaic is used as the basis for the segmentation.

The methodology is described here: https://www.mdpi.com/2072-4292/12/13/2162/html .

An application of the methodology is found here: https://www.mdpi.com/2072-4292/13/24/4975/html

Quality Assurance:

The product has been thoroughly tested against reference datasets provided by NASA, ESA and the Joint Research Center of the European Union

(JRC). The results of the inter-comparison can be found in the following publication:

Michael Nolde, Simon Plank, Torsten Riedlinger. (2020, July 6). An Adaptive and Extensible System for Satellite-Based, Large Scale Burnt Area

Monitoring in Near-Real Time. Remote Sens. 2020, 12, 2162. https://doi.org/10.3390/rs1213216 2