awesome-satellite-imagery-competitions/README.md

Awesome Satellite Imagery Competitions

List of machine learning competitions in the context of satellite imagery and remote sensing. Sorted by submission deadline.

• xView 2018 Detection Challenge (DIUx, Jul 2018)
  Object Detection (60 categories), 1 million instances, 0.3m resolution Worldview-3 imagery, COCO data format, pre-trained Tensorflow and Pytorch baseline models

• CrowdAI Mapping Challenge (Humanity & Inclusion NGO, May 2018)
  Semantic/Instance Segmentation (buildings), RGB imagery, COCO data format

• Open AI Challenge: Aerial Imagery of South Pacific Islands (Worldbank, May 2018)
  Object Detection (4 tree species), Semantic Segmentation (2 road types), 0.4m/0.8m UAV imagery, multiple AOIs in Tonga

• DEEPGLOBE - 2018 Satellite Challange (CVPR, Apr 2018)
  3 challenge tracks: Road Extraction, Building Detection, Land cover classification

• IEEE Data Fusion Contest 2018 (IEEE, -Mar 2018)
  Land cover classification (20 categories) by fusing data three sources: Multispectral LiDAR, Hyperspectral (1m), RGB imagery (0.05m)

• Spacenet challenge - Round 3 (CosmiQ Works, Radiant Solutions, NVIDIA, Feb 2018)
  Road Extraction, multiple city aois, 3/8band Worldview-3 imagery (0.3m), SpaceNet Challenge Asset Library

• Statoil/C-CORE Iceberg Classifier Challenge (Statoil/C-CORE, Jan 2018)
  Image Recognition (Predict if image chip contains ship or iceberg), 2-band HH/HV polarization SAR imagery, Kaggle kernels

• Functional Map of the World Challenge (IARPA, Dec 2017)
  Object Detection (63 categories), 1 million instances, 4/8 band, COCO data format, baseline algorithms

• NIST DSE Plant Identification with NEON Remote Sensing Data (inria.fr, Oct 2017)
  Extraction of tree position, species and crown parameters, Hyperspectral (1m), RGB imagery (0.25m), LiDAR point cloud and canopy height model

• Planet: Understanding the Amazon from Space (Planet, Jul 2017)
  Image recognition (Predict 1 of 13 land cover and 1 of 4 cloud condition labels per image chip), Amazonian rainforest, 4 band (RGB-NIR, 3-5m), Kaggle kernels

• Spacenet challenge - Round 2 (CosmiQ Works, Radiant Solutions, NVIDIA, May 2017)
  Building extraction, multiple city aois, 3/8band Worldview-3 imagery (0.3m), SpaceNet Challenge Asset Library

• DSTL Satellite Imagery Feature Detection challenge (Dstl, Feb 2017)
  Object Detection & Classification (10 categories). 3 band (RGB) and 16 band Worldview 3 imagery (0.3m - 7.5m), Kaggle kernels.

• Spacenet challenge - Round 1 (CosmiQ Works, Radiant Solutions, NVIDIA, Jan 2017)
  Building extraction, Rio de Janeiro, 3/8band Worldview-3 imagery (0.5m mosaic), SpaceNet Challenge Asset Library

• Multi-View Stereo 3D Mapping Challenge (IARPA, Nov 2016)
  Development of a Multi-View Stereo (MVS) 3D mapping algorithm that can convert high-resolution satellite images to 3D point clouds.

• Draper Satellite Image Chronology (Draper, Jun 2016)
  Predict the chronological order of images taken at the same locations over 5 days, Kaggle kernels

• Inria Aerial Image Labeling (inria.fr)
  Semantic Segmentation (buildings), multiple city aois, aerial imagery (0.3m)