ESA WorldCover

Stream data with DDA:

import os, git
from dagshub.streaming import DagsHubFilesystem
url = 'https://<username>:<token>@dagshub.com/DagsHub-Datasets/esa-worldcover-dataset.git'
git.Git("./").clone(url)
fs = DagsHubFilesystem("esa-worldcover-dataset")
print(list(fs.scandir("esa-worldcover-dataset")))
print(list(fs.listdir("esa-worldcover-dataset/s3://esa-worldcover")))

Description:

The European Space Agency (ESA) WorldCover is a global land cover map with 11 different land cover classes produced at 10m resolution based on combination of both Sentinel-1 and Sentinel-2 data. In areas where Sentinel-2 images are covered by clouds for an extended period of time, Sentinel-1 data then provides complimentary information on the structural characteristics of the observed land cover. Therefore, the combination of Sentinel-1 and Sentinel-2 data makes it possible to update the land cover map almost in real time. WorldCover Map has been produced for 2020 (01 January to 31 December) with a global coverage as part of the 5th Earth Observation Envelope Programme (EOEP-5). It provides valuable information for applications such as biodiversity, food security, carbon assessment and climate modelling. More information can be found on the WorldCover website and the product User Manual.

Contact:

The European Space Agency (ESA) WorldCover is a global land cover map with 11 different land cover classes produced at 10m resolution based on combination of both Sentinel-1 and Sentinel-2 data. In areas where Sentinel-2 images are covered by clouds for an extended period of time, Sentinel-1 data then provides complimentary information on the structural characteristics of the observed land cover. Therefore, the combination of Sentinel-1 and Sentinel-2 data makes it possible to update the land cover map almost in real time. WorldCover Map has been produced for 2020 (01 January to 31 December) with a global coverage as part of the 5th Earth Observation Envelope Programme (EOEP-5). It provides valuable information for applications such as biodiversity, food security, carbon assessment and climate modelling. More information can be found on the WorldCover website and the product User Manual.

Update Frequency:

Not yet defined.

Managed By:

https://vito.be

Collabs:

• ASDI:
  • Tags: satellite imagery

Resources:

1. resource:
   • Description: ESA WorldCover in a S3 bucket
   • ARN: arn:aws:s3:::esa-worldcover
   • Region: eu-central-1
   • Type: S3 Bucket
   • RequesterPays: False

Tags:

aws-pds, earth observation, agriculture, satellite imagery, geospatial, natural resource, sustainability, cog, disaster response, mapping, synthetic aperture radar

Tutorials:

1. tutorial:
   • Title: Global Fire Spread Prediction System
   • URL: https://github.com/SatelliteVu/SatelliteVu-AWS-Disaster-Response-Hackathon
   • AuthorName: SatelliteVu
   • AuthorURL: https://www.satellitevu.com/

Tools & Applications:

1. tools & applications:

   • Title: WorldCover Viewer
   • URL: https://viewer.esa-worldcover.org/worldcover/ta
   • AuthorName: ESA/Vito
   • AuthorURL: https://esa-worldcover.org/en

2. tools & applications:

   • Title: TerraScope Viewer
   • URL: https://viewer.terrascope.be/
   • AuthorName: TerraScope
   • AuthorURL: https://terrascope.be/en/about-us

Publication:

1. publication:

   • Title: Release of the 10 m WorldCover map
   • URL: https://blog.vito.be/remotesensing/release-of-the-10-m-worldcover-map
   • AuthorName: Ruben Van De Kerchove

2. publication:

   • Title: Remote Sensing Mapping of Build-Up Land with Noisy Label via Fault-Tolerant Learning
   • URL: https://doi.org/10.3390/rs14092263
   • AuthorName: Gang Xu, Yongjun Fang, Min Deng, Geng Sun and Jie Chen.