List of remote sensing (RS) multi-view datasets for exploring multi-view fusion learning. ๐ก ๐ ๐ก
This is a complementary source used in the following paper:
Common Practices and Taxonomy in Deep Multi-view Fusion for Remote Sensing Applications
Dataset | RS views | Temporal? | Task | Region | URL | Additional URL |
---|---|---|---|---|---|---|
University of Houston | UAV-based: HS and RGB optical, DSM (LiDAR) | ๐ | Image Segmentation | USA | https://hyperspectral.ee.uh.edu/?page_id=1075 | .. |
MSLCC | MS optical (S2), SAR (S1) | ๐ | Image Segmentation | Germany | https://www.dlr.de/eoc/en/desktopdefault.aspx/tabid-12760/22294_read-51180 | .. |
ISPRS 2D Challenge | UAV-based: MS optical, DSM | ๐ | Image Segmentation | Germany | https://www.isprs.org/education/benchmarks/UrbanSemLab | .. |
So2Sat LCZ42 (Zhu et al. 2020) | MS Optical (S2), SAR (S1) | ๐ | Image Classification | Global | https://mediatum.ub.tum.de/1483140 | https://doi.org/10.14459/2018mp1483140 |
Sen1Floods11 (Bonafilia et al. 2020) | MS optical (S2), SAR (S1) | ๐ | Image Segmentation | Global | https://github.com/cloudtostreet/Sen1Floods11 | .. |
AI4Food (Kondmann et al. 2021) | 2 MS optical (S2, PlanetFusion), SAR (S1) | ๐ | Image Classification | Germany | https://doi.org/10.34911/rdnt.z9y7vu | .. |
ForestNet (Irvin et al. 2020) | MS optical (L8), DSM (SRTM), weather (NCEP) | ๐ | Image Segmentation | Indonesia | https://stanfordmlgroup.github.io/projects/forestnet/ | .. |
LFMC from SAR (Rao et al) | MS Optical (L8), SAR (S1), weather, elevation, soil | ๐ | Pixel-wise Regression | USA | https://github.com/kkraoj/lfmc_from_sar | https://beta.source.coop/repositories/stanford/sar-moisture-conent/description/ |
Dams (Donchyts et al. 2021) | MS optical (S2) including VI, SAR (S1), DSM | ๐ | Image Segmentation | Global | https://www.kaggle.com/datasets/gdonchyts/global-dams-from-space | .. |
LandCoverNet (Alemohammad et al. 2021) | 2 MS optical (S2, L8), SAR (S1) | ๐ | Image Segmentation | Global | https://doi.org/10.34911/rdnt.d2ce8i | .. |
BigEarthNet-MM (Sumbul et al. 2021) | MS optical (S2), SAR (S1) | ๐ | Multi-label Classification | Europe | https://bigearth.net/ | .. |
EarthNet (Requena et al. 2021) | MS optical (S2), weather (E-OBS), DSM (EUDEM) | ๐ | Image Regression | Europe | https://www.earthnet.tech/ | https://www.earthnet.tech/en21x/download/ |
CropHarvest (Tseng et al. 2021) | MS optical+NDVI (S2), SAR (S1), weather (ERA5), DSM (SRTM) | ๐ | Pixel-wise Classification | Global | https://github.com/nasaharvest/cropharvest | .. |
RapidAI4EO (Marchisio et al. 2021) | MS optical (S2), MS optical (Planet) | ๐ | Image segmentation | Europe | https://rapidai4eo.radiant.earth/ | .. |
MultiSenGE (Wenger et al. 2022) | MS optical (S2), SAR (S1) | ๐ | Image Segmentation | France | https://zenodo.org/records/6375466 | .. |
DynamicEarthNet (Toker et al. 2022) | 2 MS optical (S2, PlanetFusion), SAR (S1) | ๐ | Image Segmentation | Global | https://mediatum.ub.tum.de/1483140 | https://doi.org/10.14459/2018mp1483140 |
Ombria (Drakonakis et al. 2022) | MS optical (S2), SAR (S1) | ๐ | Image Segmentation | Global | https://github.com/geodrak/OMBRIA | .. |
PASTIS-R (Garnot et al. 2022) | MS optical (S2), SAR (S1) | ๐ | Image Segmentation | France | https://github.com/VSainteuf/pastis-benchmark | .. |
SEN12MS-CR-TS (Ebel et al. 2022) | MS optical (S2), SAR (S1) | ๐ | Image Segmentation | Global | https://patricktum.github.io/cloud_removal/ | https://patricktum.github.io/cloud_removal/sen12mscrts/ |
WHU-OPT-SAR (Li et al. 2022) | MS Optical (G1), SAR (G3) | ๐ | Image Segmentation | China | https://github.com/AmberHen/WHU-OPT-SAR-dataset | .. |
CloudSEN12 (Aybar et al. 2022) | MS optical (S2), SAR (S1), DSM (MERIT) | ๐ | Image Segmentation | Global | https://cloudsen12.github.io/ | .. |
Satlas (Bastani et al. 2022) | MS optical (S2 and NAIP) | ๐ | Multiple Tasks | Global | https://github.com/allenai/satlas | .. |
MultiEarth (Cha et al. 2022) | MS optical (S2 and L8), SAR (S1) | ๐ | Multiple Tasks | Global | https://sites.google.com/view/rainforest-challenge/multiearth-2023 | .. |
MDAS (Hu et al. 2023) | MS (S2) and HS (EnMAP, HySpex) optical, SAR (S1), DSM (DLR 3K) | ๐ | Pixel-wise Classification | Germany | https://mediatum.ub.tum.de/1657312 | https://doi.org/10.14459/2022mp1657312 |
TreeSatAI (Ahlswede et al. 2023) | 2 MS optical (S2, UAV), SAR (S1) | ๐ | Pixel-wise Classification | Germany | https://zenodo.org/record/6780578 | https://doi.org/10.5281/zenodo.6780578 |
BEN-GE (Mommert et al. 2023) | MS optical (S2), SAR (S1), DSM (GLO-30), weather (ERA5) | ๐ | Image Segmentation | Europe | https://github.com/HSG-AIML/ben-ge | .. |
Crop Yield Prediction (Perich et al. 2023) | MS optical (S2), weather | ๐ | Pixel-wise regression | Switzerland | https://www.research-collection.ethz.ch/handle/20.500.11850/595228 | .. |
Globe230k (Shi et al. 2023) | RGB+NDVI optical (S2), DEM (NASA), SAR (S1) | ๐ | Image Segmentation | Global | https://zenodo.org/records/8429200 | |
GreenEarthNet (Benson et al. 2024) | MS optical (S2), weather, elevation | ๐ | Image Regression | Europe | https://github.com/earthnet2021/earthnet-minicuber | |
SICKLE (Sani et al. 2024) | MS optical (S2 and L8), Radar (S1) | ๐ | Image Regression, Segmentation | India | https://sites.google.com/iiitd.ac.in/sickle/home | |
CropNet Dataset (Lin et al.) | Optical (S2), weather | ๐ | Image Regression | USA | https://huggingface.co/datasets/fudong03/Tiny-CropNet |
- The RS Views column contains the views (and source where it was obtained), Temporal? column indicates if the labels have a temporal scope.
Feel free to ask me to update some content!
Some abbrevations
Abbrevation | name |
---|---|
DSM | Digital Surface Map |
EnMAP | Environmental Mapping and Analysis Program |
G1 | Gaofen-1 |
G3 | Gaofen-3 |
L7 | Landsat-7 |
L8 | Landsat-8 |
NAIP | National Agriculture Imagery Program |
NCEP | National Centers for Environmental Prediction |
S1 | Sentinel-1 |
S2 | Sentinel-2 |
SRTM | Shuttle Radar Topography Mission |
UAV | Unnamed Aerial Vehicle |