The Contest: Goals and Organization

 

The 2017 IEEE GRSS Data Fusion Contest, organized by the IEEE GRSS Image Analysis and Data Fusion Technical Committee, aimed at promoting progress on fusion and analysis methodologies for multisource remote sensing data.

 

Instructions: 

 

Overview

The 2017 Data Fusion Contest will consist in a classification benchmark. The task to perform is classification of land use (more precisely, Local Climate Zones or LCZ) in various urban environments. Several cities have been selected all over the world to test the ability of both LCZ prediction and domain adaptation. Input data are multi-temporal, multi-source and multi-mode (image and semantic layers). 5 cities are considered for training: Berlin, Hong Kong, Paris, Rome and Sao Paulo.

Content

Each city folder contains:grid/        sampling gridlandsat_8/    Landsat 8 images at various dates (resampled at 100m res., split in selected bands)lcz/        Local Climate Zones as rasters (see below)osm_raster/    Rasters with areas (buildings, land-use, water) derived from OpenStreetMap layersosm_vector/    Vector data with OpenStreetMap zones and linessentinel_2/    Sentinel2 image (resampled at 100m res., split in selected bands)

 

Local Climate Zones

The lcz/ folder contains:`<city>_lcz_GT.tif`: The ground-truth for local climate zones, as a raster. It is single-band, in byte format. The pixel values range from 1 to 17 (maximum number of classes). Unclassified pixels have 0 value.`<city>_lcz_col.tif`: Color, georeferenced LCZ map, for visualization convenience only.Class nembers are the following:10 urban LCZs corresponding to various built types:

  • 1. Compact high-rise;
  • 2. Compact midrise;
  • 3. Compact low-rise;
  • 4. Open high-rise;
  • 5. Open midrise;
  • 6. Open low-rise;
  • 7. Lightweight low-rise;
  • 8. Large low-rise;
  • 9. Sparsely built;
  • 10. Heavy industry.

7 rural LCZs corresponding to various land cover types:

  • 11. Dense trees;
  • 12. Scattered trees;
  • 13. Bush and scrub;
  • 14. Low plants;
  • 15. Bare rock or paved;
  • 16. Bare soil or sand;
  • 17. Water

 

More...

More info:http://www.grss-ieee.org/community/technical-committees/data-fusion/data-fusion-contest/

Discuss:https://www.linkedin.com/groups/IEEE-Geoscience-Remote-Sensing-Society-3678437

 

Acknowledgments

The 2017 IEEE GRSS Data Fusion Contest is organized by the Image Analysis and Data Fusion Technical Committee of IEEE GRSSLandsat 8 data available from the U.S. Geological Survey (https://www.usgs.gov/).OpenStreetMap Data © OpenStreetMap contributors, available under the Open Database Licence - http://www.openstreetmap.org/copyright. Original Copernicus Sentinel Data 2016 available from  the European Space Agency (https://sentinel.esa.int).The Contest is being organized in collaboration with the WUDAPT (http://www.wudapt.org/) and GeoWIKI (http://geo-wiki.org/) initiatives. The IADF TC chairs would like to thank the organizers and the IEEE GRSS for continuously supporting the annual Data Fusion Contest through funding and resources.

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The Data Fusion Contest 2016: Goals and Organization

The 2016 IEEE GRSS Data Fusion Contest, organized by the IEEE GRSS Image Analysis and Data Fusion Technical Committee, aimed at promoting progress on fusion and analysis methodologies for multisource remote sensing data.

New multi-source, multi-temporal data including Very High Resolution (VHR) multi-temporal imagery and video from space were released. First, VHR images (DEIMOS-2 standard products) acquired at two different dates, before and after orthorectification:

Instructions: 

 

After unzip, each directory contains:

  • original GeoTiff for panchromatic (VHR) and multispectral (4bands) images,

  • quick-view image for both in png format,

  • capture parameters (RPC file).

 

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