64-2 Grassland Conversion to Cropland.

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Symposium--Use Of Remote Sensing For Crop and Pasture Statistics: I
Monday, November 4, 2013: 1:20 PM
Tampa Convention Center, Room 9
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Christopher Wright, GIS Center of Excellence, South Dakota State University, Brookings, SD
The U.S. Department of Agriculture’s Cropland Data Layer (CDL) provides new opportunities for monitoring land cover/land use change (LCLUC) related to U.S. agricultural policy, bioenergy development, and high commodity prices. Over the period 2006-2011, we used the CDL to assess conversion of grasslands to corn and soybeans along the western periphery of the U.S. Corn Belt. Here, we found rapid conversion rates (1-5% annually) as the Corn Belt expands westward and northward into North Dakota and South Dakota. In most counties in the eastern Dakotas, grassland conversion exceeded declining enrollment in the Conservation Reserve Program (CRP), indicating that such LCLUC is not confined solely to CRP lands. In Iowa, grassland conversion was concentrated on marginal lands characterized by high erosion potential and less-productive soils. In Minnesota, corn/soy production increased on lands previously too wet to farm absent an expansion of drainage practices. In the Prairie Pothole Region, where 50% of North American ducks breed, approximately 80% of LCLUC occurred within 0.5-km of a wetland. Although not originally designed for monitoring grasslands, we suggest that the CDL can be used judiciously to identify grassland conversion at farm- to sub-county scales. In conjunction with other national datasets like the National Wetlands Inventory and SSURGO database, the CDL can be employed to provide timely feedback to decision-makers and other stakeholders on the likely impacts of U.S. agricultural policies, as those programs are implemented. However, inherent drawbacks of the CDL, e.g., an inability to identify previously un-broken prairie, or to accurately distinguish grass pasture from grass hay, point to the need for a federal initiative to improve grassland remote sensing, classification, and monitoring nation-wide.
See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Symposium--Use Of Remote Sensing For Crop and Pasture Statistics: I