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Geographic research on the Corn Belt and other regional landscapes of the central U.S. has not to date identified quantitatively the climatic, edaphic, topographic, and economic characteristics that determine rural land cover, and that therefore govern land cover change. Using the USDA/NASS Cropland Data Layer, this study identifies these characteristics using Multivariable Fractional Polynomials within a logistic regression framework. It maps the suitability distribution for corn, soybeans, spring and winter wheat, cotton, grassland, and forest land covers that dominate the central U.S., at a 56m resolution across 16 central U.S. states. The non-linear logistic regression models are successful in identifying determinants of land cover with relative operating characteristic (ROC) scores that range from 0.769 for soybeans to 0.888 for forest, with a combined corn/soybean model achieving an ROC of 0.871. For corn and soybean models, when prior land cover of a pixel is added, predictability and ROC scores increase substantially (0.07-0.10), indicating a strong temporal dependency in land cover dynamics due to crop rotation. This process also aids in the delineation of fields from pixels. Adding neighboring land covers further improves predictability and ROC scores only slightly (0.014-0.019), however, indicating a weak spatial dependency mechanism. By including annual crop prices within the logit models, economically marginal cropland that comes into crop production only when prices are high is identified in a spatially-explicit manner. This capacity improves further analyses of economic and environmental impacts of policies that effect crop prices.Abstract. Geographic research on the Corn Belt and other regional landscapes of the central U.S. has not to date identified quantitatively the climatic, edaphic, topographic, and economic characteristics that determine rural land cover, and that therefore govern land cover change.Using the USDA/NASS Cropland Data Layer, this study identifies these characteristics using Multivariable Fractional Polynomials within a logistic regression framework. It maps the suitability distribution for corn, soybeans, spring and winter wheat, cotton, grassland, and forest land covers that dominate the central U.S., at a 56m resolution across 16 central U.S. states. The non-linear logistic regression models are successful in identifying determinants of land cover with relative operating characteristic (ROC) scores that range from 0.769 for soybeans to 0.888 for forest, with a combined corn/soybean model achieving an ROC of 0.871. For corn and soybean models, when prior land cover of a pixel is added, predictability and ROC scores increase substantially (0.07-0.10), indicating a strong temporal dependency in land cover dynamics due to crop rotation. This process also aids in the delineation of fields from pixels.Adding neighboring land covers further improves predictability and ROC scores only slightly (0.014-0.019), however, indicating a weak spatial dependency mechanism. By including annua...

Over the past century, channelization, agricultural tiling, and land use changes have resulted in significant stream channel degradation of the Cache River in southern Illinois. With the increasing interest in restoration of the watershed's bottomland forests and swamps, we sought to characterize geomorphic change over the past 110 years to inform restoration and management. A previously surveyed stretch of river was resurveyed in the fall of 2011, following a record flood in the spring of that year. Results suggest that the slope of the channel in this section of the river has increased 345% between 1903 and 1972 (p < 0.01), but has not changed significantly since (p = 0.12). Within that same time period, bank heights increased between 1 and 7 m and bed elevation decreased between 1 and 5 m. Changes in resurveyed cross sections appear to be primarily due to recent flood scour. It appears as though early 20th Century stream channel modifications had immediate effects on the geomorphology of the channel; however, channel geometry is now at or near equilibrium. This case study of the Cache River watershed demonstrates how and why successful restoration will require integration of geomorphic processes of the system.