IrrMapper Irrigated Lands

UMT/Climate/IrrMapper_RF/v1_0
Dataset Availability
1986-01-01T00:00:00 - 2020-01-01T00:00:00
Dataset Provider
Earth Engine Snippet
ee.ImageCollection("UMT/Climate/IrrMapper_RF/v1_0")
Tags
irrigated-land landsat-derived

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.

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

This work is licensed under a Creative Commons Attribution 4.0 International License.

Citations

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

Explore in Earth Engine

var dataset = ee.ImageCollection("UMT/Climate/IrrMapper_RF/v1_0");
var irr_2013 = dataset.filterDate('2013-01-01', '2013-12-31').select('classification');

var visualization = {
  min: 0.0,
  max: 1.0,
  palette: ['blue']
};
Map.addLayer(irr_2013, visualization, 'IrrMapper 2013');
Map.setCenter(-112.516, 45.262, 10);