List of datasets, codes and contests related to remote sensing building extraction.The newest at the top of each category.
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Microsoft BuildingFootprints Canada & USA (Microsoft, Mar 2019)
12.6mil (Canada) & 125.2mil (USA) building footprints, GeoJSON format, delineation based on Bing imagery using ResNet34 architecture. -
Spacenet Challenge Round 4 - Off-nadir (CosmiQ Works, DigitalGlobe, Radiant Solutions, AWS, Dec 2018)
126k building footprints (Atlanta), 27 WorldView 2 images (0.3m res.) from 7-54 degrees off-nadir angle. Bi-cubicly resampled to same number of pixels in each image to counter courser native resolution with higher off-nadir angles, Paper: Weir et al. 2019 -
Inria Aerial Image Labeling (inria.fr)
Building footprint masks, RGB aerial imagery (0.3m res.), 5 cities
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xView 2 Building Damage Asessment Challenge (DIUx, Nov 2019)
550k building footprints & 4 damage scale categories, 20 global locations and 7 disaster types (wildfire, landslides, dam collapses, volcanic eruptions, earthquakes/tsunamis, wind, flooding), Worldview-3 imagery (0.3m res.), pre-trained baseline model. Paper: Gupta et al. 2019 -
CrowdAI Mapping Challenge (Humanity & Inclusion NGO, May 2018)
Buildings footprints, RGB satellite imagery, COCO data format -
DEEPGLOBE - 2018 Satellite Challange (CVPR, Apr 2018)
Three challenge tracks: Road Extraction, Building Detection, Land cover classification, Paper: Demir et al. 2018 -
广东政务数据创新大赛—智能算法赛 (Alibaba et al.Nov 2017)
使用2015年和2017年分别获取到的广东省某地的Quickbird卫星影像（包含蓝、绿、红和近红外四个波段），识别出两年之间新增的人工地上建筑物（不包括道路）。获胜团队的解决方案可以在天池官网上找到。 -
Spacenet Challenge Round 2 - Buildings (CosmiQ Works, Radiant Solutions, NVIDIA, May 2017)
685k building footprints, 3/8band Worldview-3 imagery (0.3m res.), 5 cities, SpaceNet Challenge Asset Library -
Spacenet Challenge Round 1 - Buildings (CosmiQ Works, Radiant Solutions, NVIDIA, Jan 2017)
Building footprints (Rio de Janeiro), 3/8band Worldview-3 imagery (0.5m res.), SpaceNet Challenge Asset Library
- Awesome Satellite Imagery Datasets
- Zhang Bin's Blog. remote sensing datasets
- The picture of this page is from Qi Wen et al.2019