Addressing Challenges for Mapping Irrigated Fields in Subhumid Temperate Regions by Integrating Remote Sensing and Hydroclimatic Data
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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.
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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
Temporal
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Content
Data Services
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/
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