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| Type: | Resource | |
| Storage: | The size of this resource is 684.4 MB | |
| Created: | Apr 29, 2024 at 7:21 p.m. | |
| Last updated: | Oct 15, 2024 at 2:12 p.m. | |
| Citation: | See how to cite this resource | |
| Content types: | Multidimensional Content |
| Sharing Status: | Public |
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| Views: | 174 |
| Downloads: | 34 |
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Abstract
Agriculture plays a vital role in the US, generating billions of dollars in revenue and providing essential resources such as food, fiber, and fuel. At the same time, this sector consumes more water than all other sectors combined, and contributes significantly to greenhouse gas emissions. Accurately mapping cropland areas at a high spatial resolution, and understanding cultivation trends are crucial for promoting sustainable land management. However, it is not always clear where these crops are cultivated at a fine spatial resolution. Existing data sources either provide extensive temporal coverage with low spatial detail or vice versa. To address this, we employed a data-fusion approach, combining strengths of existing data sources. We produced annual irrigated and harvested areas for 30 major crops in the US from 1981 to 2019 at 2.5 arc minutes by combining county level US Department of Agriculture records with gridded land use datasets. We evaluated our dataset by comparing it with existing large-scale gridded cropland data, revealing alignment and divergence across data products depending on the year, area, and crop. Our dataset serves as a critical tool for analyzing and understanding long-term trends in cropland cultivation, thereby contributing to more informed and sustainable agricultural practices
Subject Keywords
Coverage
Spatial
Temporal
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Content
Data Services
Additional Metadata
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| Note | The data and the associated manuscript is currently under peer-review. Subsequent versions of the data may differ. If accepted for publication, the final version of the data, along with the corresponding manuscript, will be uploaded here. |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| Foundation for Food and Agriculture Research | Achieving sustainable groundwater management through innovative governance and optimal agricultural water use under conflicting objectives | FF-NIA19-0000000084 |
| United States Department of Agriculture | Targeted Conservation: A coupled hydro-economic modeling approach to maximizing water availability across the Mississippi River Basin | 2022-67019-37180 |
| National Science Foundation | CAREER: CAS- Climate: Advancing Water Sustainability and Economic Resilience through Research and Education: An Integrated Systems Approach | 2144169 |
| National Science Foundation | INFEWS/Track 1: Mesoscale Data Fusion to Map and Model the U.S. FEW system (INFEWSion) | 1639529 |
Contributors
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
| Name | Organization | Address | Phone | Author Identifiers |
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| Gambhir Lamsal | Virginia Polytechnic Institute and State University (Virginia Tech) | Virgnia, US | ||
| Landon Marston | Virginia Polytechnic Institute and State University | Virginia, US |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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