National Agricultural Statistics Service Cropland Research Articles

Spatial and temporal dimensions of agricultural land use changes, 2001–2012, East-Central Iowa

In central regions of the U. S. Corn Belt, agricultural production since 2001 has changed in response to federal policies implemented to encourage production of biofuels. Such changes have influenced agricultural practices, land uses, and their spatial character. This study examines site-specific temporal and spatial patterns of agricultural land use dynamics from 2001 to 2012 in a nine-county region of East-Central Iowa using the United States Department of Agriculture National Agricultural Statistics Service Cropland Data Layer. Results indicate that increases in corn production in response to US biofuel policies and high grain prices have been achieved mainly by altering crop rotation patterns. These changes may be correlated with market forces, although variations suggest a multiplicity of causes. This study also examines spatial relationships between cultivated fields and crop rotation practices with respect to underlying soils and terrain. Intensity of cultivated land use depends on topographic and pedologic properties, although motivations and constraints perceived by producers and managers as they plan their use of landscapes are important. The most intensively cultivated lands have shallower slopes and fewer pedologic limitations than others, and corn was planted in higher quality soil while soybeans were moved to lesser quality soils. Declining acreage in the Conservation Reserve Program since 2007 indicates that they may be used for other crops displaced by corn.

An Assessment of the Cultivated Cropland Class of NLCD 2006 Using a Multi-Source and Multi-Criteria Approach

We developed a method that analyzes the quality of the cultivated cropland class mapped in the USA National Land Cover Database (NLCD) 2006. The method integrates multiple geospatial datasets and a Multi Index Integrated Change Analysis (MIICA) change detection method that captures spectral changes to identify the spatial distribution and magnitude of potential commission and omission errors for the cultivated cropland class in NLCD 2006. The majority of the commission and omission errors in NLCD 2006 are in areas where cultivated cropland is not the most dominant land cover type. The errors are primarily attributed to the less accurate training dataset derived from the National Agricultural Statistics Service Cropland Data Layer dataset. In contrast, error rates are low in areas where cultivated cropland is the dominant land cover. Agreement between model-identified commission errors and independently interpreted reference data was high (79%). Agreement was low (40%) for omission error comparison. The majority of the commission errors in the NLCD 2006 cultivated crops were confused with low-intensity developed classes, while the majority of omission errors were from herbaceous and shrub classes. Some errors were caused by inaccurate land cover change from misclassification in NLCD 2001 and the subsequent land cover post-classification process.

Remote sensing to monitor cover crop adoption in southeastern Pennsylvania

In the Chesapeake Bay Watershed, winter cereal cover crops are often planted in rotation with summer crops to reduce the loss of nutrients and sediment from agricultural systems. Cover crops can also improve soil health, control weeds and pests, supplement forage needs, and support resilient cropping systems. In southeastern Pennsylvania, cover crops can be successfully established following corn (Zea mays L.) silage harvest and are strongly pro- moted for use in this niche. They are also planted following corn grain, soybean (Glycine max L.), and vegetable harvest. In Pennsylvania, the use of winter cover crops for agricultural con- servation has been supported through a combination of outreach, regulation, and incentives. On-farm implementation is thought to be increasing, but the actual extent of cover crops is not well quantified. Satellite imagery can be used to map green winter cover crop vegetation on agricultural fields and, when integrated with additional remote sensing data products, can be used to evaluate wintertime vegetative groundcover following specific summer crops. This study used Landsat and SPOT (System Probatoire d' Observation de la Terre) satellite imagery, in combination with the USDA National Agricultural Statistics Service Cropland Data Layer, to evaluate the extent and amount of green wintertime vegetation on agricultural fields in four Pennsylvania counties (Berks, Lebanon, Lancaster, and York) from 2010 to 2013. In December of 2010, a windshield survey was conducted to collect baseline data on winter cover crop implementation, with particular focus on identifying corn harvested for silage (expected earlier harvest date and lower levels of crop residue), versus for grain (expected later harvest date and higher levels of crop residue). Satellite spectral indices were successfully used to detect both the amount of green vegetative groundcover and the amount of crop residue on the surveyed fields. Analysis of wintertime satellite imagery showed consistent increases in vegetative groundcover over the four-year study period and determined that trends did not result from annual weather variability, indicating that farmers are increasing adoption of practices such as cover cropping that promote wintertime vegetation. Between 2010 and 2013, the occurrence of wintertime vegetation on agricultural fields increased from 36% to 67% of corn fields in Berks County, from 53% to 75% in Lancaster County, from 42% to 65% in Lebanon County, and from 26% to 52% in York County. Apparently, efforts to promote cover crop use in the Chesapeake Bay Watershed have coincided with a rapid increase in the occurrence of wintertime vegetation following corn harvest in southeastern Pennsylvania. However, despite these increases, between 25% and 48% of corn fields remained without substantial green vegetation over the wintertime, indicating further opportunity for cover crop adoption.

Estimating switchgrass productivity in the Great Plains using satellite vegetation index and site environmental variables

Switchgrass is being evaluated as a potential feedstock source for cellulosic biofuels and is being cultivated in several regions of the United States. The recent availability of switchgrass land cover maps derived from the National Agricultural Statistics Service cropland data layer for the conterminous United States provides an opportunity to assess the environmental conditions of switchgrass over large areas and across different geographic locations. The main goal of this study is to develop a data-driven multiple regression switchgrass productivity model and identify the optimal climate and environment conditions for the highly productive switchgrass in the Great Plains (GP). Environmental and climate variables used in the study include elevation, soil organic carbon, available water capacity, climate, and seasonal weather. Satellite-derived growing season averaged Normalized Difference Vegetation Index (GSN) was used as a proxy for switchgrass productivity. Multiple regression analyses indicate that there are strong correlations between site environmental variables and switchgrass productivity (r=0.95). Sufficient precipitation and suitable temperature during the growing season (i.e., not too hot or too cold) are favorable for switchgrass growth. Elevation and soil characteristics (e.g., soil available water capacity) are also an important factor impacting switchgrass productivity. An anticipated switchgrass biomass productivity map for the entire GP based on site environmental and climate conditions and switchgrass productivity model was generated. Highly productive switchgrass areas are mainly located in the eastern part of the GP. Results from this study can help land managers and biofuel plant investors better understand the general environmental and climate conditions influencing switchgrass growth and make optimal land use decisions regarding switchgrass development in the GP.

Recent land use change in the Western Corn Belt threatens grasslands and wetlands

In the US Corn Belt, a recent doubling in commodity prices has created incentives for landowners to convert grassland to corn and soybean cropping. Here, we use land cover data from the National Agricultural Statistics Service Cropland Data Layer to assess grassland conversion from 2006 to 2011 in the Western Corn Belt (WCB): five states including North Dakota, South Dakota, Nebraska, Minnesota, and Iowa. Our analysis identifies areas with elevated rates of grass-to-corn/soy conversion (1.0-5.4% annually). Across the WCB, we found a net decline in grass-dominated land cover totaling nearly 530,000 ha. With respect to agronomic attributes of lands undergoing grassland conversion, corn/soy production is expanding onto marginal lands characterized by high erosion risk and vulnerability to drought. Grassland conversion is also concentrated in close proximity to wetlands, posing a threat to waterfowl breeding in the Prairie Pothole Region. Longer-term land cover trends from North Dakota and Iowa indicate that recent grassland conversion represents a persistent shift in land use rather than short-term variability in crop rotation patterns. Our results show that the WCB is rapidly moving down a pathway of increased corn and soybean cultivation. As a result, the window of opportunity for realizing the benefits of a biofuel industry based on perennial bioenergy crops, rather than corn ethanol and soy biodiesel, may be closing in the WCB.

Changes of crop rotation in Iowa determined from the United States Department of Agriculture, National Agricultural Statistics Service cropland data layer product

Crop rotation is one of the important decisions made independently by numerous farm managers, and is a critical variable in models of crop growth and soil carbon. In Iowa and much of the Midwestern United States (US), the typical management decision is to rotate corn and soybean crops for a single field; therefore, the land-cover changes each year even though the total area of agricultural land-use remains the same. The price for corn increased from 2001 to 2010, which increased corn production in Iowa. We tested the hypothesis that the production increase was the result of changes in crop rotation in Iowa using the annual remote sensing classification (the cropland data layer) produced by the United States Department of Agriculture, National Agricultural Statistics Service. It was found that the area planted in corn increased from 4.7 million hectares in 2001 to 5.7 million hectares in 2007, which was correlated with the market price for corn. At the county level, there were differences in how the increase in corn production was accomplished. Northern and central counties had little land to expand cultivation and generally increased corn production by converting to a corn-corn rotation from the standard corn-soybean rotation. Southern counties in Iowa increased corn production by expanding into land that was not under recent cultivation. These changes affect the amount of soil carbon sequestration.

Sustainable agricultural residue removal for bioenergy: A spatially comprehensive US national assessment

This study provides a spatially comprehensive assessment of sustainable agricultural residue removal potential across the United States for bioenergy production. Earlier assessments determining the quantity of agricultural residue that could be sustainably removed for bioenergy production at the regional and national scale faced a number of computational limitations. These limitations included the number of environmental factors, the number of land management scenarios, and the spatial fidelity and spatial extent of the assessment. This study utilizes integrated multi-factor environmental process modeling and high fidelity land use datasets to perform the sustainable agricultural residue removal assessment. Soil type represents the base spatial unit for this study and is modeled using a national soil survey database at the 10–100m scale. Current crop rotation practices are identified by processing land cover data available from the USDA National Agricultural Statistics Service Cropland Data Layer database. Land management and residue removal scenarios are identified for each unique crop rotation and crop management zone. Estimates of county averages and state totals of sustainably available agricultural residues are provided. The results of the assessment show that in 2011 over 150 million metric tons of agricultural residues could have been sustainably removed across the United States. Projecting crop yields and land management practices to 2030, the assessment determines that over 207 million metric tons of agricultural residues will be able to be sustainably removed for bioenergy production at that time. This biomass resource has the potential for producing over 68 billion liters of cellulosic biofuels.