- Dataset Availability
- 1986-01-01T00:00:00Z–2023-01-01T00:00:00Z
- Dataset Provider
- University of Montana / Montana Climate Office
- Earth Engine Snippet
-
ee.ImageCollection("UMT/Climate/IrrMapper_RF/v1_2") - Tags
Description
IrrMapper is an annual classification of irrigation status in the 11 Western United States made at Landsat scale (i.e., 30 m) using the Random Forest algorithm, covering years 1986 - present.
While the IrrMapper paper describes classification of four classes (i.e., irrigated, dryland, uncultivated, wetland), the dataset is converted to a binary classification of irrigated and non-irrigated.
'Irrigated' refers to the detection of any irrigation during the year. The IrrMapper random forest model was trained using an extensive geospatial database of land cover from each of four irrigated- and non-irrigated classes, including over 50,000 human-verified irrigated fields, 38,000 dryland fields, and over 500,000 square kilometers of uncultivated lands.
For version 1.2, the original training data was greatly expanded, a RF model built for each state, and a more thorough validation and uncertainty analysis undertaken. See the supplement to our paper on the impacts of irrigation on streamflow.
Bands
Resolution
30 meters
Bands
| Name | Description |
|---|---|
classification |
Irrigated pixels have the value of 1, the other pixels are masked out. |
Terms of Use
Terms of Use
Citations
Ketchum, D.; Jencso, K.; Maneta, M.P.; Melton, F.; Jones, M.O.; Huntington, J. IrrMapper: A Machine Learning Approach for High Resolution Mapping of Irrigated Agriculture Across the Western U.S., Remote Sens. 2020, 12, 2328. doi:10.3390/rs12142328
Ketchum, D., Hoylman, Z.H., Huntington, J. et al. Irrigation intensification impacts sustainability of streamflow in the Western United States. Commun Earth Environ 4, 479 (2023). doi:10.1038/s43247-023-01152-2
Explore with Earth Engine
Code Editor (JavaScript)
var dataset = ee.ImageCollection('UMT/Climate/IrrMapper_RF/v1_2');
var irr = dataset.filterDate('2023-01-01', '2023-12-31').mosaic();
var visualization = {
min: 0.0,
max: 1.0,
palette: ['blue']
};
Map.addLayer(irr, visualization, 'IrrMapper 2023');
Map.setCenter(-112.516, 45.262, 10);