LANID Landsat-based Irrigation Dataset (US, 1997-2017)
30 m resolution annual maps of irrigation distribution, frequency and change across the conterminous U.S. for 1997-2017, with derivative products (maximum extent, formerly/intermittently irrigated lands) and ground-reference validation points.
glbrc.org
At a glance
- Region
- United States (North America)
- Coverage
- Conterminous United States
- Access
- Free
- Category
- Research
- Last updated
- 2024
What's inside
- irrigated area
- irrigation frequency
- remote sensing
- agriculture
What you can do with it
Typical work that data of this type supports.
- 01
Irrigation scheduling
Decide when and how much to irrigate.
Because it has: irrigated area
- 02
Water accounting
Track how much water crops actually consume across a command area.
- 03
No-gauge areas
Monitor places with no ground stations.
Because it has: remote sensing
Where AI adds value
Ideas for machine learning and AI agents built on this kind of data.
- 01
Field-scale ET
Estimate crop water use per field by combining satellite and weather with ML.
- 02
Demand forecasts
Predict irrigation demand weeks ahead for canal and pump planning.
- 03
Segmentation
Map water, crops and land use pixel by pixel with deep learning.
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