IEEE Data Fusion Contest 2018 (IEEE, -Mar 2018)
植被分类 (20 类) ,数据集有三种: 多谱线 LiDAR, 高光谱(1m), RGB 图像(0.05m)
http://www.grss-ieee.org/community/technical-committees/data-fusion/data-fusion-contest/
Functional Map of the World Challenge (IARPA, Dec 2017)
物体检测 (63 类), 100万个实例, 4/8 波段, COCO 数据格式, baseline algorithms
https://www.iarpa.gov/challenges/fmow.html
Urban 3D Challenge (USSOCOM, Dec 2017) 建筑物占地面积检测, 50cm 2D RGB 正的 photos and 3D data generated from satellite imagery, 3 cities, open source software for winning solutions, data hosted on SpaceNet Challenge Asset Library
https://www.topcoder.com/urban3d
NIST DSE Plant Identification with NEON Remote Sensing Data (inria.fr, Oct 2017)
提取树的位置、种类和冠状参数, 高光谱(1m), RGB 图像 (0.25m), 激光雷达点云和冠层高度模型。
https://www.ecodse.org/
Planet: Understanding the Amazon from Space (Planet, Jul 2017)
图像识别(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
https://www.kaggle.com/c/planet-understanding-the-amazon-from-space
参考:https://oldpan.me/archives/awesome-satellite-imagery-competitions
https://github.com/chrieke/awesome-satellite-imagery-datasets