IrrMapper是使用随机森林算法对美国西部11个州的灌溉状况进行的年度分类(即30米),涵盖1986年至今。虽然IrrMapper论文描述了四个等级的分类(即灌溉、旱地、非耕地、湿地),但数据集被转换为灌溉和非灌溉的二元分类。灌溉的 "指的是在这一年中检测到任何灌溉的情况。IrrMapper随机森林模型是用一个广泛的地理空间数据库来训练的,该数据库包括四个灌溉和非灌溉类的土地覆盖,包括50,000多块经人类验证的灌溉田,38,000块旱地,以及500,000多平方公里的未开垦土地。
IrrMapper Irrigated Lands
Dataset Availability
1986-01-01T00:00:00Z–2020-01-01T00:00:00
Dataset Provider
University of Montana / Montana Climate Office
Earth Engine Snippet
ee.ImageCollection("UMT/Climate/IrrMapper_RF/v1_0")
Resolution
30 meters
Bands
Name | Description |
classification |
Irrigated pixels have the value of 1, the other pixels are masked out. |
代码:
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);
数据引用:
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