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The CloudCast Dataset
许可协议: CC-BY-SA 4.0

Overview

CloudCast: A large-scale dataset and baseline for forecasting clouds

The CloudCast dataset contains 70080 cloud-labeled satellite images with 10 different cloud types corresponding to multiple layers of the atmosphere. The raw satellite images come from a satellite constellation in geostationary orbit centred at zero degrees longitude and arrive in 15-minute intervals from the European Organisationfor Meteorological Satellites (EUMETSAT). The resolution of these images is 3712 x 3712 pixels for the full-disk of Earth, which implies that every pixel corresponds to a space of dimensions 3x3km. This is the highest possible resolution from European geostationary satellites when including infrared channels. Some pre- and post-processing of the raw satellite images are also being done by EUMETSAT before being exposed to the public, such as removing airplanes. We collect all the raw multispectral satellite images and annotate them individually on a pixel-level using a segmentation algorithm. The full dataset then has a spatial resolution of 928 x 1530 pixels recorded with 15-min intervals for the period 2017-2018, where each pixel represents an area of 3×3 km. To enable standardized datasets for benchmarking computer vision methods, this includes a full-resolution gray-scaled dataset centered and projected dataset over Europe (728×728).

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Citation

If you use this dataset in your research or elsewhere, please cite/reference the following paper:
CloudCast: A Satellite-Based Dataset and Baseline for Forecasting Clouds

Data dictionary

There are 24 folders in the dataset containing the following information:

| File | Definition | Note |
| --- | --- |
| X.npy | Numpy encoded array containing the actual 728x728 image with pixel values as labels, see below. | |
| GEO.npz| Numpy array containing geo coordinates where the image was taken (latitude and longitude). | |
| TIMESTAMPS.npy| Numpy array containing timestamps for each captured image. | Images are captured in 15-minute intervals. |

Cloud types

0 = No clouds or missing data
1 = Very low clouds
2 = Low clouds
3 = Mid-level clouds
4 = High opaque clouds
5 = Very high opaque clouds
6 = Fractional clouds
7 = High semitransparant thin clouds
8 = High semitransparant moderately thick clouds
9 = High semitransparant thick clouds
10 = High semitransparant above low or medium clouds

Examples




数据概要
数据格式
image,
数据量
70.086K
文件大小
739.95MB
发布方
Christian Lillelund
| 数据量 70.086K | 大小 739.95MB
The CloudCast Dataset
许可协议: CC-BY-SA 4.0

Overview

CloudCast: A large-scale dataset and baseline for forecasting clouds

The CloudCast dataset contains 70080 cloud-labeled satellite images with 10 different cloud types corresponding to multiple layers of the atmosphere. The raw satellite images come from a satellite constellation in geostationary orbit centred at zero degrees longitude and arrive in 15-minute intervals from the European Organisationfor Meteorological Satellites (EUMETSAT). The resolution of these images is 3712 x 3712 pixels for the full-disk of Earth, which implies that every pixel corresponds to a space of dimensions 3x3km. This is the highest possible resolution from European geostationary satellites when including infrared channels. Some pre- and post-processing of the raw satellite images are also being done by EUMETSAT before being exposed to the public, such as removing airplanes. We collect all the raw multispectral satellite images and annotate them individually on a pixel-level using a segmentation algorithm. The full dataset then has a spatial resolution of 928 x 1530 pixels recorded with 15-min intervals for the period 2017-2018, where each pixel represents an area of 3×3 km. To enable standardized datasets for benchmarking computer vision methods, this includes a full-resolution gray-scaled dataset centered and projected dataset over Europe (728×728).

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Citation

If you use this dataset in your research or elsewhere, please cite/reference the following paper:
CloudCast: A Satellite-Based Dataset and Baseline for Forecasting Clouds

Data dictionary

There are 24 folders in the dataset containing the following information:

| File | Definition | Note |
| --- | --- |
| X.npy | Numpy encoded array containing the actual 728x728 image with pixel values as labels, see below. | |
| GEO.npz| Numpy array containing geo coordinates where the image was taken (latitude and longitude). | |
| TIMESTAMPS.npy| Numpy array containing timestamps for each captured image. | Images are captured in 15-minute intervals. |

Cloud types

0 = No clouds or missing data
1 = Very low clouds
2 = Low clouds
3 = Mid-level clouds
4 = High opaque clouds
5 = Very high opaque clouds
6 = Fractional clouds
7 = High semitransparant thin clouds
8 = High semitransparant moderately thick clouds
9 = High semitransparant thick clouds
10 = High semitransparant above low or medium clouds

Examples




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