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Addressing Challenges for Mapping Irrigated Fields in Subhumid Temperate Regions by Integrating Remote Sensing and Hydroclimatic Data
Authors: Tianfang Xu Jillian M Deines Anthony Kendall Bruno Basso David William Hyndman
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Resource type: Composite Resource
Storage: The size of this resource is 74.8 MB
Created: Feb 09, 2019 at 9:58 p.m.
Last updated: Feb 10, 2019 at 8:46 p.m.
DOI: 10.4211/hs.3766845be72d45969fca21530a67bb2d
Citation: See how to cite this resource
Content types: Geographic Raster Content 
Sharing Status: Published
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Abstract

Preferred citation:
Xu, T., Deines, J., Kendall, A., Basso, B., and Hyndman, DW. 2019. Addressing Challenges for Mapping Irrigated Fields in Subhumid Temperate Regions by Integrating Remote Sensing and Hydroclimatic Data. Remote Sensing.

We developed annual, 30-m resolution maps of irrigated corn and soybeans for southwestern Michigan from 2001 to 2016 using a machine learning method (random forest). Please see Xu et al. 2019 for full details. The rasters are in UINT 8 format, with 0 indicates rainfed, 1 indicates irrigated, and 3 indicates masked (not row crops according to NLCD before 2007 and not corn or soybeans according to CDL since 2007).

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Resource Level Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Place/Area Name:
Southwestern Michigan
North Latitude
42.7839°
East Longitude
-84.6000°
South Latitude
41.7595°
West Longitude
-86.8279°

Temporal

Start Date:
End Date:

Content

How to Cite

Xu, T., J. M. Deines, A. Kendall, B. Basso, D. W. Hyndman (2019). Addressing Challenges for Mapping Irrigated Fields in Subhumid Temperate Regions by Integrating Remote Sensing and Hydroclimatic Data, HydroShare, https://doi.org/10.4211/hs.3766845be72d45969fca21530a67bb2d

This resource is shared under the Creative Commons Attribution CC BY.

  http://creativecommons.org/licenses/by/4.0/
CC-BY

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