US Cropland Research Articles

Innovations through crop switching happen on the diverse margins of US agriculture

Crop switching, in which farmers grow a crop that is novel to a given field, can help agricultural systems adapt to changing environmental, cultural, and market forces. Yet while regional crop production trends receive significant attention, relatively little is known about the local-scale crop switching that underlies these macrotrends. We characterized local crop-switching patterns across the United States using the US Department of Agriculture (USDA) Cropland Data Layer, an annual time series of high resolution (30 m pixel size) remote-sensed cropland data from 2008 to 2022. We found that at multiple spatial scales, crop switching was most common in sparsely cultivated landscapes and in landscapes with high crop diversity, whereas it was low in homogeneous, highly agricultural areas such as the Midwestern corn belt, suggesting a number of potential social and economic mechanisms influencing farmers' crop choices. Crop-switching rates were high overall, occurring on more than 6% of all US cropland in the average year. Applying a framework that classified crop switches based on their temporal novelty (crop introduction versus discontinuation), spatial novelty (locally divergent versus convergent switching), and categorical novelty (transformative versus incremental switching), we found distinct spatial patterns for these three novelty dimensions, indicating a dynamic and multifaceted set of cropping changes across US farms. Collectively, these results suggest that innovation through crop switching is playing out very differently in various parts of the country, with potentially significant implications for the resilience of agricultural systems to changes in climate and other systemic trends.

Annual time-series 1 km maps of crop area and types in the conterminous US (CropAT-US): cropping diversity changes during 1850–2021

Abstract. Agricultural activities have been recognized as an important driver of land cover and land use change (LCLUC) and have significantly impacted the ecosystem feedback to climate by altering land surface properties. A reliable historical cropland distribution dataset is crucial for understanding and quantifying the legacy effects of agriculture-related LCLUC. While several LCLUC datasets have the potential to depict cropland patterns in the conterminous US, there remains a dearth of a relatively high-resolution datasets with crop type details over a long period. To address this gap, we reconstructed historical cropland density and crop type maps from 1850 to 2021 at a resolution of 1 km × 1 km by integrating county-level crop-specific inventory datasets, census data, and gridded LCLUC products. Different from other databases, we tracked the planting area dynamics of all crops in the US, excluding idle and fallow farm land and cropland pasture. The results showed that the crop acreages for nine major crops derived from our map products are highly consistent with the county-level inventory data, with a residual less than 0.2×103 ha (0.2 kha) in most counties (>75 %) during the entire study period. Temporally, the US total crop acreage has increased by 118×106 ha (118 Mha) from 1850 to 2021, primarily driven by corn (30 Mha) and soybean (35 Mha). Spatially, the hot spots of cropland distribution shifted from the Eastern US to the Midwest and the Great Plains, and the dominant crop types (corn and soybean) expanded northwestward. Moreover, we found that the US cropping diversity experienced a significant increase from the 1850s to the 1960s, followed by a dramatic decline in the recent 6 decades under intensified agriculture. Generally, this newly developed dataset could facilitate spatial data development, with respect to delineating crop-specific management practices, and enable the quantification of cropland change impacts on the environment. Annual cropland density and crop type maps are available at https://doi.org/10.6084/m9.figshare.22822838.v2 (Ye et al., 2023).

Counterfactual scenarios reveal historical impact of cropland management on soil organic carbon stocks in the United States

Natural climate solutions provide opportunities to reduce greenhouse gas emissions and the United States is among a growing number of countries promoting storage of carbon in agricultural soils as part of the climate solution. Historical patterns of soil organic carbon (SOC) stock changes provide context about mitigation potential. Therefore, our objective was to quantify the influence of climate-smart soil practices on SOC stock changes in the top 30 cm of mineral soils for croplands in the United States using the DayCent Ecosystem Model. We estimated that SOC stocks increased annually in US croplands from 1995 to 2015, with the largest increase in 1996 of 16.6 Mt C (95% confidence interval ranging from 6.1 to 28.2 Mt CO2 eq.) and the lowest increase in 2015 of 10.6 Mt C (95% confidence interval ranging from − 1.8 to 22.2 Mt C). Most climate-smart soil practices contributed to increases in SOC stocks except for winter cover crops, which had a negligible impact due to a relatively small area with cover crop adoption. Our study suggests that there is potential for enhancing C sinks in cropland soils of the United States although some of the potential has been realized due to past adoption of climate-smart soil practices.

Irrigation benefits outweigh costs in more US croplands by mid-century

Irrigation can increase crop yields and could be a key climate adaptation strategy. However, future water availability is uncertain. Here we explore the economic costs and benefits of existing and expanded irrigation of maize and soybean throughout the United States. We examine both middle and end of the 21st-century conditions under future climates that span the range of projections. By mid-century we find an expansion in the area where the benefits of irrigation outweigh groundwater pumping and equipment ownership costs. Increased crop water demands limit the region where maize could be sustainably irrigated, but sustainably irrigated soybean is likely feasible throughout regions of the midwestern and southeastern United States. Shifting incentives for installing and maintaining irrigation equipment could place additional challenges on resource availability. It will be important for decision makers to understand and account for local water demand and availability when developing policies guiding irrigation installation and use.

Disentangling day–night contributions toward altering atmospheric desiccation strength for US croplands

AbstractVapor pressure deficit (VPD) is the difference between saturation and actual water vapor pressures and is driven by interactions between air temperature and humidity. Globally, VPD observations indicate drying of the atmosphere, while air temperature (T) and relative humidity (RH) have changed asymmetrically during daytime versus nighttime. However, whether daytime or nighttime T (Tday and Tnight, respectively) and RH (RHday and RHnight, respectively) have been more important to VPD change is unknown, and so is the seasonal variation of this importance. This research determines the relative contribution of Tday, Tnight, RHday, and RHnight to VPD change observed during 1981–2021 across the conterminous United States. Tday contributed 41% to driving a VPD increase of 2.1 standard deviations (SD), followed by contributions of 25%, 22%, and 12% from RHday, RHnight, and Tnight, respectively. Regions with significant VPD increase have seen increase in Tday (by 1 SD) and Tnight (by 0.9 SD) and a decrease in RHday (by 1 SD) and RHnight (by 3.4 SD). Diurnal asymmetry in warming and drying trends was true for most months, with greater rates of change during the nighttime than daytime. Tday was the dominant driver of the annual mean VPD rise for 70% of the counties, followed by RHday (18%), RHnight (11%), and Tnight (1%). We conclude that warming and drying during the days and nights together explain increased VPD across the US croplands and that climate stressors during days and nights should be viewed independently due to their crop‐specific impacts that vary spatially and seasonally.

The Economics of Nutrient Pollution from Agriculture

Nutrient pollution from agricultural sources, coming primarily from fertilization of row crops and manure from livestock operations, affects ecological health in the United States through water and air pollution. We summarize data trends on commercial fertilizer use, manure, cropland, and concentrations of nitrogen and phosphorus in waterways. We present data indicating that fertilizer applications per acre of US cropland exhibit an upward trend, with a strong spatial correlation between agricultural intensification and nutrient contents in waterbodies. While biophysical science has advanced our understanding of how nutrient pollutants affect the functioning of physical ecosystems, economic research has quantified only some of the economic damages related to losses in ecosystem services due to nutrient pollution. Our summary of this work indicates that quantification is incomplete and does not yet provide full characterization of these damages across the country. We summarize key available damage estimates and the limited evidence on cost-effective policy design. We conclude by identifying important yet understudied areas, including a focus on contaminated drinking water sources, health damages from nutrient pollution, and the need for holistic estimates of the costs of the externalities from pollution, where new research efforts will greatly benefit society.

A framework to estimate climate mitigation potential for US cropland using publicly available data

The US agricultural sector is proposed as one opportunity to contribute to greenhouse gas (GHG) emissions reductions—reductions that are needed to limit atmospheric warming to be more in line with the US Nationally Determined Contribution to the Paris Agreement. Improved management of agricultural soils can both mitigate GHG emissions and increase carbon (C) sequestration, but disagreement exists regarding what levels of adoption are possible and to what extent they may mitigate net GHG emissions. In this paper, we provide a framework for setting reasonable, short-term conservation practice adoption targets and quantifying the associated net emissions reductions. Our framework was constructed using USDA-based publicly available inventory data and mitigation potentials from the COMET-Planner tool scaled to nine farm resource regions. The framework includes 2017 levels of conservation practice adoption and two 10-year growth scenarios: business-as-usual (BAU) and accelerated adoption rates. We evaluated six cropland management practices and practices associated with Conservation Reserve Program (CRP) establishment. Based on existing (2017) census data, we estimated that 134.2 million tonnes (Mt) carbon dioxide equivalents (CO₂e) per year have been or continue to be reduced through the adoption of conservation management practices on a cumulative total of 133.5 million hectares (Mha) of cropland. Under the BAU scenario, we estimated an additional 6.2 Mha y⁻¹ of adoption could result in a reduction potential of 48.7 Mt CO₂e y⁻¹. Under the accelerated scenario, we estimated an additional 13.1 Mha y⁻¹ of adoption could result in a reduction potential of 118.5 Mt of CO₂e y⁻¹ over the next 10 years. This framework highlights three key outcomes: (1) agriculture has had a substantial impact on GHG mitigation through existing/historical adoption of six cropland management practices and conversion of lands to the CRP; (2) these shifts in adoption provide an important baseline to make future projections of changes in practice adoption given regional trends and the resulting GHG mitigation potentials; and (3) disaggregating national estimates to the farm resource region level can help to inform and prioritize programs and policies consistent with existing climate goals. Estimates reported here reflect the current state of national modeling efforts and agricultural inventory sources. As new data such as the pending 2022 Ag Census report and model enhancements are made, the framework we outline here can be used to revise and update the estimates to improve accuracy and applicability.

Crop-climate feedbacks boost US maize and soy yields

US maize and soy production have increased rapidly since the mid-20th century. While global warming has raised temperatures in most regions over this time period, trends in extreme heat have been smaller over US croplands, reducing crop-damaging high temperatures and benefiting maize and soy yields. Here we show that agricultural intensification has created a crop-climate feedback in which increased crop production cools local climate, further raising crop yields. We find that maize and soy production trends have driven cooling effects approximately as large as greenhouse gas induced warming trends in extreme heat over the central US and substantially reduced them over the southern US, benefiting crops in all regions. This reduced warming has boosted maize and soy yields by 3.3 (2.7–3.9; 13.7%–20.0%) and 0.6 (0.4–0.7; 7.5%–13.7%) bu/ac/decade, respectively, between 1981 and 2019. Our results suggest that if maize and soy production growth were to stagnate, the ability of the crop-climate feedback to mask warming would fade, exposing US crops to more harmful heat extremes.

Small-scale integrated farming systems can abate continental-scale nutrient leakage.

Beef is the most resource intensive of all commonly used food items. Disproportionate synthetic fertilizer use during beef production propels a vigorous one-way factory-to-ocean nutrient flux, which alternative agriculture models strive to rectify by enhancing in-farm biogeochemical cycling. Livestock, especially cattle, are central to these models, which advocates describe as the context most likely to overcome beef's environmental liabilities. Yet the dietary potential of such models is currently poorly known. Here, I thus ask whether nitrogen-sparing agriculture (NSA) can offer a viable alternative to the current US food system. Focusing on the most common eutrophication-causing element, N, I devise a specific model of mixed-use NSA comprising numerous small farms producing human plant-based food and forage, the latter feeding a core intensive beef operation that forgoes synthetic fertilizer and relies only on locally produced manure and N fixers. Assuming the model is deployed throughout the high-quality, precipitation-rich US cropland (delimiting approximately 100 million ha, less than half of today's agricultural land use) and neglecting potential macroeconomic obstacles to wide deployment, I find that NSA could produce a diverse, high-quality nationwide diet distinctly better than today's mean US diet. The model also permits 70%-80% of today's beef consumption, raises today's protein delivery by 5%-40%, and averts approximately 60% of today's fertilizer use and approximately 10% of today's total greenhouse gas emissions. As defined here, NSA is thus potentially a viable, scalable environmentally superior alternative to the current US food system, but only when combined with the commitment to substantially enhance our reliance on plant food.

Midwest US Croplands Determine Model Divergence in North American Carbon Fluxes

AbstractLarge uncertainties in North American terrestrial carbon fluxes hinder regional climate projections. Terrestrial biosphere models (TBMs), the essential tools for understanding continental‐scale carbon cycle, diverge on whether temperate forests or croplands dominate carbon uptake in North America. Evidence from novel photosynthetic proxies, such as those based on chlorophyll fluorescence, has cast doubt on the “weak cropland, strong forest” carbon uptake patterns simulated by most TBMs. However, no systematic evaluation of TBMs has yet been attempted to pin down space‐time patterns that are most consistent with regional CO2 observational constraints. Here, we leverage atmospheric CO2 observations and satellite‐observed photosynthetic proxies to understand emergent space‐time patterns in North American carbon fluxes from a large suite of TBMs and data‐driven models. To do so, we evaluate how well the atmospheric signals resulting from carbon flux estimates reproduce the space‐time variability in atmospheric CO2, as is observed by a network of continuous‐monitoring towers over North America. Models with gross or net carbon fluxes that are consistent with the observed CO2 variability share a salient feature of growing‐season carbon uptake in Midwest US croplands. Conversely, the remaining models place most growing‐season uptake in boreal or temperate forests. Differences in model explanatory power depend mainly on the simulated annual cycles of cropland uptake—especially, the timing of peak uptake—rather than the distribution of annual mean fluxes across biomes. Our results suggest that improved model representation of cropland phenology is crucial to robust, policy‐relevant estimation of North American carbon exchange.

Evaluating Drought Responses of Surface Ozone Precursor Proxies: Variations With Land Cover Type, Precipitation, and Temperature.

Prior work suggests drought exacerbates US air quality by increasing surface ozone concentrations. We analyze 2005–2015 tropospheric column concentrations of two trace gases that serve as proxies for surface ozone precursors retrieved from the OMI/Aura satellite: Nitrogen dioxide (ΩNO2; NOx proxy) and formaldehyde (ΩHCHO; VOC proxy). We find 3.5% and 7.7% summer drought enhancements (classified by SPEI) for ΩNO2 and ΩHCHO, respectively, corroborating signals previously extracted from ground‐level observations. When we subset by land cover type, the strongest ΩHCHO drought enhancement (10%) occurs in the woody savannas of the Southeast US. By isolating the influences of precipitation and temperature, we infer that enhanced biogenic VOC emissions in this region increase ΩHCHO independently with both high temperature and low precipitation during drought. The strongest ΩNO2 drought enhancement (6.0%) occurs over Midwest US croplands and grasslands, which we infer to reflect the sensitivity of soil NOx emissions to temperature.

Understanding the market for cover crop seeds in the United States: Background and potential policy directions

Previous literature has shown that cover crops have the potential to provide large-scale environmental benefits by reducing soil erosion, preventing nutrient leaching, sequestering carbon (C), and providing habitat for beneficial insects and pollinators (Snapp et al. 2005; Laloy and Bielders 2010; Castellano et al. 2012; Poeplau and Don 2015). In addition, cover crops can potentially generate private benefits to the farm operation by helping boost soil productivity (and subsequent cash crop yields), suppressing weeds, reducing fertilizer needs, and improving nutrient cycling (Bergtold et al. 2019; Myers and Watts 2015; Wittwer et al. 2017). Given the potential economic and environmental benefits of cover crop adoption, cover crop acreage in the US grew from about 10.3 million ac (4.2 Mha) in 2012 to about 15.4 million ac (6.23 Mha) in 2017 (i.e., a 50% increase), based on data from the US Census of Agriculture (LaRose and Myers 2019). Nonetheless, even in light of these adoption increases, acres planted to cover crops only equal 3.9% of all US cropland in 2017 (Zulauf and Brown 2019) (figure 1). Although there are several possible reasons that overall cover crop adoption rates in the US remain relatively low, one of the main factors that influences the cost of adopting cover crops is cover crop …

Environmental Drivers of Agricultural Productivity Growth: Co2 Fertilization of Us Field Crops

We assess the CO 2 fertilization effect on US agriculture using spatially-varying CO 2 data from NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite covering the majority of US cropland under actual growing conditions. This study complements the many CO 2 enrichment experiments that have found important interactions between CO 2 and local environmental conditions in controlled settings. We use three empirical strategies: (i) a panel of CO 2 anomalies and county yields, (ii) a panel of spatial first-differences between neighboring counties, and (iii) a cross-sectional spatial first-difference. We find consistently high fertilization effects: a 1 ppm increase in CO 2 equates to a 0.5%, 0.6%, and 0.8% yield increase for corn, soybeans, and wheat, respectively. Viewed retrospectively, 10%, 30%, and 40% of each crop's yield improvements since 1940 are attributable to rising CO 2 .

How to transition to reduced-meat diets that benefit people and the planet

Overwhelming evidence shows that overconsumption of meat is bad for human and environmental health and that moving towards a more plant-based diet is more sustainable. For instance, replacing beef with beans in the US could free up 42% of US cropland and reduce greenhouse gas emissions by 334 mmt, accomplishing 75% of the 2020 carbon reduction target. We summarise the evidence on how overconsumption of meat affects social, environmental and economic sustainability. We highlight the social, environmental and economic effectiveness of a range of dietary interventions that have been tested to date. Because meat eating is embedded within complex cultural, economic, and political systems, dietary shifts to reduce overconsumption are unlikely to happen quickly and a suite of sustained, context-specific interventions is likely to work better than brief, one-dimensional approaches. We conclude with key actions needed by global leaders in politics, industry and the health sector that could help aide this dietary transformation to benefit people and the planet.

A strategic plan for future USDA Agricultural Research Service erosion research and model development

Soil erosion is a natural process, and the erosion potential of a site is the result of complex interactions among soil, vegetation, topographic position, land use and management, and climate. Soil erosion occurs when aeolian and hydrologic processes exceed a soil’s inherent resistance to these forces (figures 1 and 2). Soil erosion was recognized as a significant problem at both local and national scales in the United States in the 1920s; by 1935 soil erosion was considered a national disaster, covering over one-half of the country (Sampson and Weyl 1918; Weaver 1935), and is still a concern with 21% of the western United States degraded and vulnerable to accelerated soil erosion (Herrick et al. 2010; Weltz et al. 2014a; Duniway et al. 2019). In 1995, it was estimated that 4 × 109 t (4.4 × 109 tn) of soil was lost from US cropland (Pimentel et al. 1995). The most vulnerable areas for soil movement and thus erosion occur where annual precipitation is 100 to 400 mm y–1 (4 to 16 in yr–1), which limits soil moisture available to sustain plant growth. Anthropogenic-driven dust emissions have dramatically increased across …

Climate Benefits of Increasing Plant Diversity in Perennial Bioenergy Crops

Bioenergy from perennial grasses mitigates climate change via displacing fossil fuels and storing atmospheric CO2 belowground as soil carbon. Here, we conduct a critical review to examine whether increasing plant diversity in bioenergy grassland systems can further increase their climate change mitigation potential. We find that compared with highly productive monocultures, diverse mixtures tend to produce as great or greater yields. In particular, there is strong evidence that legume addition improves yield, in some cases equivalent to mineral nitrogen fertilization at 33–150 kg per ha. Plant diversity can also promote soil carbon storage in the long term, reduce soil N2O emissions by 30%–40%, and suppress weed invasion, hence reducing herbicide use. These potential benefits of plant diversity translate to 50%–65% greater life-cycle greenhouse gas savings for biofuels from more diverse grassland biomass grown on degraded soils. In addition, there is growing evidence that plant diversity can accelerate land restoration.

Thinking Like a Grassland: Challenges and Opportunities for Biodiversity Conservation in the Great Plains of North America

Fauna of North America’s Great Plains evolved strategies to contend with the region’s extreme spatiotemporal variability in weather and low annual primary productivity. The capacity for large-scale movement (migration and/or nomadism) enables many species, from bison to lark buntings, to track pulses of productivity at broad spatial scales (> 1 000 km2). Furthermore, even sedentary species often rely on metapopulation dynamics over extensive landscapes for long-term population viability. The current complex pattern of land ownership and use of Great Plains grasslands challenges native species conservation. Approaches to managing both public and private grasslands, frequently focused at the scale of individual pastures or ranches, limit opportunities to conserve landscape-scale processes such as fire, animal movement, and metapopulation dynamics. Using the US National Land Cover Database and Cropland Data Layers for 2011−2017, we analyzed land cover patterns for 12 historical grassland and savanna communities (regions) within the US Great Plains. On the basis of the results of these analyses, we highlight the critical contribution of restored grasslands to the future conservation of Great Plains biodiversity, such as those enrolled in the Conservation Reserve Program. Managing disturbance regimes at larger spatial scales will require acknowledging that, where native large herbivores are absent, domestic livestock grazing can function as a central component of Great Plains disturbance regimes if they are able move at large spatial scales and coexist with a diverse array of native flora and fauna. Opportunities to increase the scale of grassland management include 1) spatial prioritization of grassland restoration and reintroduction of grazing and fire, 2) finding creative approaches to increase the spatial scale at which fire and grazing can be applied to address watershed to landscape-scale objectives, and 3) developing partnerships among government agencies, landowners, businesses, and conservation organizations that enhance cross-jurisdiction management and address biodiversity conservation in grassland landscapes, rather than pastures.

Carbon emissions from cropland expansion in the United States

After decades of decline, croplands are once again expanding across the United States. A recent spatially explicit analysis mapped nearly three million hectares of US cropland expansion that occurred between 2008 and 2012. Land use change (LUC) of this sort can be a major source of anthropogenic carbon (C) emissions, though the effects of this change have yet to be analyzed. We developed a data-driven model that combines these high-resolution maps of cropland expansion with published maps of biomass and soil organic carbon stocks (SOC) to map and quantify the resulting C emissions. Our model increases emphasis on non-forest—i.e. grassland, shrubland and wetland—above and belowground biomass C stocks and the response of SOC to LUC—emission sources that are frequently neglected in traditional C accounting. These sources represent major emission conduits in the US, where new croplands primarily replace grasslands. We find that expansion between 2008–12 caused, on average, a release of 55.0 MgC ha−1 (SDspatial = 39.9 MgC ha−1), which resulted in total emissions of 38.8 TgC yr−1 (95% CI = 21.6–55.8 TgC yr−1). We also find wide geographic variation in both the size and sensitivity of affected C stocks. Grassland conversion was the primary source of emissions, with more than 90% of these emissions originating from SOC stocks. Due to the long accumulation time of SOC, its dominance as a source suggests that emissions may be difficult to mitigate over human-relevant time scales. While methodological limitations regarding the effects of land use legacies and future management remain, our findings emphasize the importance of avoiding LUC emissions and suggest potential means by which natural C stocks can be conserved.

Where should we apply biochar?

The heating of biomass under low-oxygen conditions generates three co-products, bio-oil, biogas, and biochar. Bio-oil can be stabilized and used as fuel oil or be further refined for various applications and biogas can be used as an energy source during the low-oxygen heating process. Biochar can be used to sequester carbon in soil and has the potential to increase crop yields when it is used to improve yield-limiting soil properties. Complex bio-physical interactions have made it challenging to answer the question of where biochar should be applied for the maximum agronomic and economic benefits. We address this challenge by developing an extensive informatics workflow for processing and analyzing crop yield response data as well as a large spatial-scale modeling platform. We use a probabilistic graphical model to study the relationships between soil and biochar variables and predict the probability and magnitude of crop yield response to biochar application. Our results show an average increase in crop yields ranging from 4.7% to 6.4% depending on the biochar feedstock and application rate. Expected yield increases of at least 6.1% and 8.8% are necessary to cover 25% and 10% of US cropland with biochar. We find that biochar application to crop area with an expected yield increase of at least 5.3%–5.9% would result in carbon sequestration offsetting 0.57%–0.67% of US greenhouse gas emissions. Applying biochar to corn area is the most profitable from a revenue perspective when compared to soybeans and wheat because additional revenues accrued by farmers are not enough to cover the costs of biochar applications in many regions of the United States.

In-Season Major Crop-Type Identification for US Cropland from Landsat Images Using Crop-Rotation Pattern and Progressive Data Classification

Crop type information at the field level is vital for many types of research and applications. The United States Department of Agriculture (USDA) provides information on crop types for US cropland as a Cropland Data Layer (CDL). However, CDL is only available at the end of the year after the crop growing season. Therefore, CDL is unable to support in-season research and decision-making regarding crop loss estimation, yield estimation, and grain pricing. The USDA mostly relies on field survey and farmers’ reports for the ground truth to train image classification models, which is one of the major reasons for the delayed release of CDL. This research aims to use trusted pixels as ground truth to train classification models. Trusted pixels are pixels which follow a specific crop rotation pattern. These trusted pixels are used to train image classification models for the classification of in-season Landsat images to identify major crop types. Six different classification algorithms are investigated and tested to select the best algorithm for this study. The Random Forest algorithm stands out among selected algorithms. This study classified Landsat scenes between May and mid-August for Iowa. The overall agreements of classification results with CDL in 2017 are 84%, 94%, and 96% for May, June, and July, respectively. The classification accuracies have been assessed through 683 ground truth data points collected from the fields. The overall accuracies of single date multi-band image classification are 84%, 89% and 92% for May, June, and July, respectively. The result also shows higher accuracy (94–95%) can be achieved through multi-date image classification compared to single date image classification.