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  UrMo Digital - Traffic Area Map (TAM) - Brunswick, Germany

This inventory of traffic areas in the city of Brunswick, Germany, is based on image sequences acquired during six flight campaigns at different times of the day and year in 2019 and 2020. Each aerial image is segmented by a neural network into the classes (1) Parking area, (2) Road, and (3) Access way, with the latter two classes differing in terms of their primary transportation function (mobility versus access). The individual segmentations are subsequently merged, since in addition to dedicated parking areas, those traffic areas that are regularly used for parking a motorized vehicle (e.g., at the curbside) are also to be classified as such. Furthermore, the multitemporal fusion enhances the robustness and completeness of the traffic area map (TAM). Potential applications include: urban planning, traffic modeling, and parking management.

For more information about the project, the reader is referred to: https://elib.dlr.de/191145/1/Hellekes_et_al_2022_Parking_space_inventory_from_above.pdf

 
Citation proposal
Jens Hellekes (German Aerospace Center (DLR)). UrMo Digital - Traffic Area Map (TAM) - Brunswick, Germany. https://gdk.gdi-de.org/geonetwork/srv/api/records/d47a2d18-8443-4428-837f-b079d171a7e7
 

Simple

Date ( Creation )
2022-08-01T00:00:00
Edition
Identifier
https://geoservice.dlr.de/catalogue/srv/metadata/d47a2d18-8443-4428-837f-b079d171a7e7
Presentation form
Digital map
Other citation details
Purpose
To provide an inventory of traffic areas in the city of Brunswick, Germany. The resulting map serves applications like urban planning, transport modeling, and traffic management.
Status
Completed

  Point of contact

German Aerospace Center (DLR)  

  Distributor

German Aerospace Center (DLR) - ( )  

  Author

German Aerospace Center (DLR) - Jens Hellekes  

Maintenance and update frequency
Not planned
Keywords
  • DLR
  • EOC
  • Aerial Imagery
  • Image Segmentation
  • Traffic Area Map
  • Parking Space Detection
  • Multitemporal Fusion
  • Brunswick
  • Germany
GEMET - INSPIRE themes, version 1.0 ( Theme )
  • Transport networks
Spatial scope ( Theme )
  • local
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
Use constraints
Other restrictions
Other constraints
Nutzungsbedingungen: Lizenz, https://creativecommons.org/licenses/by-nc/4.0 / Terms of use: License, https://creativecommons.org/licenses/by-nc/4.0
Other constraints

{"id": "cc-by-nc-4.0",

"name": "Creative Commons Namensnennung - Nicht kommerziell 4.0 International (CC BY-NC 4.0)",

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

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

Spatial representation type
Grid
Denominator
200
Metadata language
German
Character set
UTF8
Topic category
  • Transportation
N
S
E
W


Number of dimensions
2
Dimension name
Column
Dimension size
90000
Resolution
0.1  m
Dimension name
Row
Dimension size
56000
Resolution
0.1  m
Cell geometry
Area
Transformation parameter availability
false
Distribution format
  • Cloud Optimized GeoTIFF ( )

    Specification

OnLine resource
URMO_TAM_3K_BRUNSWICK  

WMS Access: inventory of traffic areas in the city of Brunswick, Germany

OnLine resource
3K_MOS_BRUNSWICK  

WMS Access: aerial imagery mosaic for the city of Brunswick, Germany

OnLine resource
UrMo Digital - Forschen für die städtische Mobilität der Zukunft  

Webpage with links and description for accessing more information about the project

OnLine resource
HTTP download  

HTTP download (UrMo Digital)

Hierarchy level
Dataset

Domain consistency

Measure identification
INSPIRE / Conformity_001

Conformance result

Date ( Publication )
2010-12-08
Explanation
See the referenced specification
Pass
true
Statement
The traffic are map for Brunswick, Germany is based on aerial images acquired with the DLR 3K camera system at varying times of the day and year between 2019 and 2020, covering about 36 km² with a spatial resolution of 0.1 m.
Description

UrMo Digital - Traffic Area Map Processing

Data:

The classification is based on image sequences acquired during six flight campaigns at different times of the day and year in 2019 and 2020. Imagery was acquired with the 3K camera system at 10 cm ground sampling distance

Processing:

Each aerial image is segmented by a neural network, multi-temporal fusion is used to improve robustness and detect curbside parking areas.

gmd:MD_Metadata

File identifier
d47a2d18-8443-4428-837f-b079d171a7e7   XML
Metadata language
English
Character set
UTF8
Hierarchy level
Dataset
Hierarchy level name
dataset
Date stamp
2024-06-20T13:08:04
Metadata standard name
ISO 19115-1:2014/19139

  Point of contact

German Aerospace Center (DLR)  

 
 

  Overviews

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  Provided by

  Views

  • INSPIRE
  • Simple
  • Full
  • XML
d47a2d18-8443-4428-837f-b079d171a7e7   Access to the portal Read here the full details and access to the data.

  Associated resources

Not available


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