Spatial Extent of Data
USGS Data Source
USGS Thesaurus Keywords
Place Keywords
Machine learning with satellite imagery to document the historical transition from topographic to dense sub-surface agricultural drainage networks (tile drains)
Image library of (1) tile-drained landscapes and (2) tile-drain types used for training a machine-learning model that identifies (1) tile-drained landscapes and (2) differentiates two types of tile-drained areas visible in satellite imagery. These images were sourced from WorldView, Quickbird, and GeoEye satellite imagery (copyright DigitalGlobe) and cropped to features of interest. Imagery has a ground resolution of 0.34 - 0.65 m.
| Author(s) |
Tanja N Williamson  ,
Dayle J Hoefling
|
| Publication Date | 2023-05-18 |
| Beginning Date of Data | 2008 |
| Ending Date of Data | 2020 |
| Data Contact | |
| DOI | https://doi.org/10.5066/P9KSZ382 |
| Citation | Williamson, T.N., and Hoefling, D.J., 2023, Machine learning with satellite imagery to document the historical transition from topographic to dense sub-surface agricultural drainage networks (tile drains): U.S. Geological Survey data release, https://doi.org/10.5066/P9KSZ382. |
| Metadata Contact | |
| Metadata Date | 2023-06-01 |
| Related Publication | Loading... |
| Citations of these data | Loading https://doi.org/10.1002/jeq2.20493 |
| Access | public |
| License | http://www.usa.gov/publicdomain/label/1.0/ |
Loading...
Harvest Source: ScienceBase
Harvest Date: 2023-06-06T04:44:30.502Z
Harvest Date: 2023-06-06T04:44:30.502Z