Date of this Version
Andrew Laws. 2022. Multi-criteria evaluation model for classifying marginal cropland in Nebraska using historical crop yield and biophysical characteristics. UNL Digital Commons.
Marginal cropland is suboptimal due to historically low and variable productivity and limiting biophysical characteristics. To support future agricultural management and policy decisions in Nebraska, U.S.A, it is important to understand where cropland is marginal for its two most economically important crops: corn (Zea mays) and soybean (Glycine max). As corn and soybean are frequently planted in a crop rotation, it is important to consider if there is a relationship with cropland marginality. Based on the current literature, there exists a need for a flexible yet robust methodology for identifying marginal land at different scales, which takes advantage of high spatial and temporal resolution data and can be applied by researchers and outreach professionals alike. This research seeks to individually identify where cropland is marginal for corn and soybean as well as classify the extent of marginality that exists. This research also seeks to classify cropland as being part of a long-term corn-soybean crop and see if marginality differs between this cropland and the remainder of cropland. Two crop-specific multi-criteria evaluations (MCE), consisting of crop production, climate, and soil criteria, was performed using Google Earth Engine to identify and classify marginal cropland. Criteria were individually thresholded before addition to the MCEs. Cropland that was classified as part of a long-term corn-soybean crop rotation was identified by factoring in the balance of corn and soybean occurrence on long established cropland.
Most cropland in Nebraska has at least some marginality for corn while most has no marginality for soybean. Marginality classification is spatially distributed with increasing marginality from the northeast to the southwest. Cropland under a long-term crop rotation shows much less marginality compared to non-rotation cropland. This study improves upon previous attempts to identify marginal cropland in Nebraska by increasing spatial and temporal resolution, providing a programmatic and replicable methodology, and confining the classification to existing cropland. The implications of these findings are useful for policy makers and agricultural extension efforts in Nebraska to identify opportunities for conservation, solar energy capture, and biofuel production on cultivated land.
Advisor: Yi Qi
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