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Automated Geospatial Data Processing

Develop a solution to automate CDB generation for compilation and correlation of 2D & 3D geospatial data.



Planning to Submit: 13 Submissions: 0

Objective: Further automate the production process for geospatial data in CDB format to accelerate content creation and meet warfighter needs for tactical terrain data in open standard formats. Open Geospatial Consortium (OGC) industry standards enable interoperability of geospatial data across systems and applications that SOF warfighters use.

What is CDB?: CDB is an OGC standard structure for persistent, global-scale data stores optimized for very high-speed access and visualization of 2D and 3D imagery, terrain, geographic objects, moving objects & entities, and material textures & characteristics.

Who Should Participate?: Software engineers and developers working on OGC CDB and C2/M&S interoperability are encouraged to participate.

How Can You Can Participate:
1. Review challenge objectives and specifications
2. Review evaluation criteria
3. Develop a white paper to outlining an approach that meets requirements: Click Here to Download White Paper Template
4. Submit the concept white paper describing your solution

– There is no minimum/maximum page count for this submission
– Participants are to provide their technology concept in the format best suited to convey the information as clearly and succinctly as possible

1. Open Geospatial Consortium CDB Standard: Click Here to Review
2. “Overview of the OGC CDB Standard for 3D Synthetic Environment Modeling and Simulation,” Saeedi, S.; Liang, S.; Graham, D.; Lokuta, M.F.; Mostafavi, M.A. International Society for Photogrammetry and Remote Sensing, International Journal of Geo-Information. 2017, 6, 306.

Concept papers will be evaluated against the following criteria:

  1. Overview diagram describing the workflow process enabled by the proposed tool
  2. Description of an approach to designing and developing a software solution to address the “Data challenges for automated CDB production” outlined below
  3. Technical merit
  4. Feasibility of implementation
  5. Degree to which the approach presents a new, novel, or provocative standards-based solution

To stimulate advances in technology and innovation, solutions including reusable code and open source software are preferred.

Data challenges for automated CDB production:

  1. Within a given pool of data, which may include folders, sub-folders, and/or multiple files:
    1. Recognize CDB-ready data such as raster elevation, raster imagery, and vector feature sets
    2. Appropriately place the source files within the CDB data structure according to metadata-specified resolution / Level of Detail (LoD)
    3. Without overwriting high-resolution data tiles, construct quad tree reduced resolution / LoD data sets
  2. Read metadata to determine the geographic space (datum, ellipsoid, projection) and format of provided data, and translate if necessary to the correct geographic space and format for the target CDB data set
  3. Convert vector data attribution to target CDB attribution format(s)
  4. Clean, balance, and conflate sensor-collected data, for example remove spikes and holes in elevation data, radiometrically balance image mosaics, and conflate vector feature sets retaining attribution
  5. Convert source data in a variety of formats to CDB-specified data formats

Chalenge Deliverables:
Please provide a concept paper describing your solution. There is no minimum/maximum page count for this submission  Participants are to provide their technology concept in the format best suited to convey the information as clearly and succinctly as possible.

Prizes will be announced and awarded within 30 days of the challenge closing date.

Prize Award Amount:

1st Place: $18,280
2nd Place: $12,280
3rd Place: $7,280

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