A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000-2018
First global time-series dataset of Forel-Ule Index (water color) for large inland water bodies (2000-2018) derived from MODIS, providing an indicator of water colour variability and quality change.
doi.org
At a glance
- Region
- Global
- Coverage
- Global
- Access
- Free
- Category
- Research
- Last updated
- 2021
What's inside
- Remote Sensing
What you can do with it
Typical work that data of this type supports.
- 01
No-gauge areas
Monitor places with no ground stations.
Because it has: Remote Sensing
- 02
Long records
Use consistent records going back decades.
- 03
Hotspots and trends
Find where contamination is high and whether it is getting worse.
Where AI adds value
Ideas for machine learning and AI agents built on this kind of data.
- 01
Segmentation
Map water, crops and land use pixel by pixel with deep learning.
- 02
Data fusion
Blend satellite and ground data into one better estimate.
- 03
Risk maps
Predict contamination where no samples exist, from geology, land use and climate.
Machine access and documentation
Data paper
A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000-2018
Scientific Data 2021
Read the paperRelated water data
- A global daily gap-filled chlorophyll-a dataset in open oceans during 2001-2021Global | Free
- Allen Coral AtlasGlobal | Free
- Copernicus Global Flood Monitoring (GFM) - EODC Data PortalGlobal | Free
- FLODIS: Human displacements, fatalities, and economic damages linked to remotely observed floodsGlobal | Free
- GARS Lab: Global Lake Surface Water TemperatureGlobal | Free
- Global annual wetland dataset at 30 m with fine classification from 2000 to 2022Global | Free
Find more water data
Search and compare 1,900+ water data sources by region, type and access.