Soil and Land-Use Change Sustainability in the Northern Great Plains of the USA

Joshi, Deepak R.; Clay, David E.; Smart, Alexander J.; Clay, Sharon A.; Kharel, Tulsi P.; Mishra, Umakant

doi:10.5772/intechopen.84781

Cited by 4 publications

(8 citation statements)

References 31 publications

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“…This paper builds on the data reported by Joshi et al (2019), wherein the cultivation suitability of croplands is discussed. Nebraska and South Dakota were selected as a model system because they have a large number of diversified (i.e., containing both crops and livestock) cropping systems (NASS, 2019;USDA, 2015).…”

Section: Methodsmentioning

confidence: 99%

“…The same 27,200 points were used each of the 3 yr (2006, 2012, and 2014), resulting in a 3-yr total of 81,600 points. Additional information on the land uses and associated LCC values for each NASS region are available in Joshi et al (2019).…”

Section: Assessing Land Use Changementioning

confidence: 99%

“…One hundred percent of these points were correctly identified. We also compared the 16,000 points assessed by two studies (Joshi et al, 2019;Reitsma et al, 2015). These two studies had identical classification 97.6% of the time.…”

Section: Assessing Land Use Changementioning

confidence: 99%

“…),Clay et al (2014),Melillo et al (2014);Reitsma et al (2015),Joshi et al (2019), USDA (2015),Elder (1969);and McKnight (1969). Temporal changes in land enrolled in the Conservation Reserve Program are available in Decision Innovation Solutions (2013).…”

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confidence: 99%

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Grassland Retention in the North America Midwest after Periods of High Commodity Prices and Climate Variability

Joshi

Ulrich‐Schad

Wang

et al. 2019

Soil Science Soc of Amer J

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The conversion of grassland, wetlands, and forest to croplands may contribute to environmental degradation and diminished sustainability. This study determined the impact of land use change from 2006 to 2012 and from 2012 to 2014 on the cultivation suitability of grasslands that were not converted to cropland. The model system, which includes nebraska and South Dakota, was selected because it contains climatic conditions ranging from humid continental to semiarid and a large number of farms that produced both crops and livestock. During the study, commodity prices reached historically high values, and a severe drought occurred in 2012. Land use benchmarks were obtained by visually identifying land use at 81,600 sample sites in high-resolution remote sensing images obtained from the national Agricultural Imaging Program. Sampling sites with Land Capability Class values £4 were identified as suitable for cultivation if appropriate practices were followed. In 2006, 2012, and 2014, grasslands accounted for 11.0, 10.76, and 10.78 million ha in nebraska, respectively, whereas in South Dakota, grasslands accounted for 12.12, 11.65, and 11.69 million ha, respectively. In nebraska, the percentage of grasslands relative to working lands (grassland + croplands) decreased from 60.6% in 2006 to 58.9% in 2014, whereas in South Dakota the percentage of grassland decreased from 69.1% in 2006 to 66.0% in 2014. In eastern nebraska and South Dakota, 74.1% of the nonconverted grasslands in 2012 were suitable for crop production. Lower-than-expected conversion rates were attributed to a growing interest in land stewardship and a desire to maintain income diversification.

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Section: Methodsmentioning

confidence: 99%

Section: Assessing Land Use Changementioning

confidence: 99%

Section: Assessing Land Use Changementioning

confidence: 99%

mentioning

confidence: 99%

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Grassland Retention in the North America Midwest after Periods of High Commodity Prices and Climate Variability

Joshi

Ulrich‐Schad

Wang

et al. 2019

Soil Science Soc of Amer J

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“…These database uncertainties are the reason Joshi et al. (2019a, 2019b) used a more laborious manual approach, wherein handpicked points of high‐resolution imagery from the National Agricultural Imaging Program were visually assessed over time to better estimate grassland conversion rates in South Dakota and Nebraska. Similarly, Kharel et al.…”

Section: Introductionmentioning

confidence: 99%

Spatially and temporally disparate data in systems agriculture: Issues and prospective solutions

et al. 2020

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Big Data in agriculture is growing rapidly through advancements in metagenomics, precision agriculture, and on-farm sensor technologies, as well as through increased capacity to collect, process, and store these data. Concurrent with 60% increases in food production demands by 2050 and the need for sustainable intensification, is the increased need for data synthesis across temporal and spatial scales. Therefore, in our data-rich world, what is lacking is a data management system across spatial and temporal resolutions including workflows, interpretation methodology, and a delivery structure for identifying optimal systems for sustainable intensification or diversification. Consequently, the objective of this paper is to explore the current state of handling spatially and temporally disparate data and offer solutions for developing a platform for bridging component parts (encompassing multiple scales and disciplines) to analyze system functionality for greater resiliency, which may help manage risk. Two datasets were generated using bibliometrics (research articles from systematic literature reviews) evaluated trends and historical Big Data applications in agronomy. Results indicate research and industry progress is advancing towards web-based real-time output delivery systems using several well-established Big Data handling platforms (e.g., Amazon Web Service, Google Cloud, Microsoft Azure), which are not yet widely used by or designed for agronomic researchers. Cloud-based computing may provide opportunities to extrapolate agricultural research results across larger scales. Authors suggest training and educating agricultural practitioners on Big Data principles, database management, improved data visualization, as well as incentives for data sharing for optimizing Big Data in systems agriculture as these research innovations emerge.

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Unmanned Aerial Vehicles in Hydrology and Water Management: Applications, Challenges, and Perspectives

Acharya

Bhandari

Bandini

et al. 2021

Water Resources Research

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Global water withdrawal and usage have risen nearly sixfold since 1900. Approximately 69% of water withdrawals are used in agriculture, 19% in industries, and 12% for municipal purposes (Food and Agriculture Organization of the United Nations, 2020). Anthropogenic disturbances and climate change affect the water cycle, water supply and demand, and impose stress on the global water systems (Haddeland et al., 2014). As such, hydrologists, geologists, agronomists, soil scientists, and engineers need reliable tools to monitor and manage surface and groundwater resources, particularly in locations where traditional monitoring is inadequate.Traditional water monitoring and measurement techniques are time-consuming, costly, and typify an inadequate and disproportionate spatial and temporal range. Over the past few decades, airplanes and satellites have been the chief source of remotely sensed water resource data. However, the usefulness of these platforms is mainly restricted to the largest spatial scales. The low frequency of temporal sampling is dictated by logistical costs (aerial imagery) or tasking schedules (satellites; Becker et al., 2009;Xue & Su, 2017). The dearth of finer resolution data and temporal inflexibility of these platforms precludes the possibility of on-demand data acquisition that is often necessary to capture the highly transient processes operating at fine spatial scales necessary for the planning and management of water resources (e.g., freshwater abstraction) and the assessment of hazards (e.g., flood extents). However, with recent advances in sensors, cameras,

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Soil and Land-Use Change Sustainability in the Northern Great Plains of the USA

Cited by 4 publications

References 31 publications

Grassland Retention in the North America Midwest after Periods of High Commodity Prices and Climate Variability

Grassland Retention in the North America Midwest after Periods of High Commodity Prices and Climate Variability

Spatially and temporally disparate data in systems agriculture: Issues and prospective solutions

Unmanned Aerial Vehicles in Hydrology and Water Management: Applications, Challenges, and Perspectives

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