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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Remote sensing applications in agriculture and forestry. Applications of aerial photography and ERTS data to agricultural, forest and water resources management

Remote sensing techniques are being used in Minnesota to study: (1) forest disease detection and control; (2) water quality indicators; (3) forest vegetation classification and management; (4) detection of saline soils in the Red River Valley; (5) corn defoliation; and (6) alfalfa crop productivity. Results of progress, and plans for future work in these areas, are discussed.

Source record↗
DOE OSTI2023

Apparatus and method for agricultural data collection and agricultural operations

Aspects of the subject disclosure may include, for example, obtaining video data from a single monocular camera, wherein the video data comprises a plurality of frames, wherein the camera is attached to a mobile robot that is travelling along a lane defined by a row of crops, wherein the row of crops comprises a first plant stem, and wherein the plurality of frames include a depiction of the first plant stem; obtaining robot velocity data from encoder(s), wherein the encoder(s) are attached to the robot; performing foreground extraction on each of the plurality of frames of the video data, wherein the foreground extraction results in a plurality of foreground images; and determining, based upon the plurality of foreground images and based upon the robot velocity data, an estimated width of the first plant stem. Additional embodiments are disclosed.

Chowdhary, Girish↗
NASA NTRS2016

Brief History of Agricultural Systems Modeling

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the next generation models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. The lessons from history should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models.

agricultural systems↗
DOE OSTI2024

Pathways for Agricultural Decarbonization in the United States

In the United States, agricultural production is both a significant source of greenhouse gases (GHGs) (Environmental Protection Agency (EPA), 2022) and uniquely susceptible to climate change impacts (Vermeulen et al., 2012). Decarbonization solutions have been proposed for addressing agricultural GHGs; however, research has been limited in synthesizing qualitative and quantitative analysis of potential GHG mitigation solutions in the United States. In this report, we review U.S. agricultural GHG sources by activity and quantify potential mitigation solutions based on a comprehensive data and literature analysis. We also discuss agricultural carbon sequestration options to offset GHG emissions. In our analysis, we identified two significant and hard-to-abate GHG sources (N 2 O from soil management, and CH 4 from enteric fermentation from livestock) as well as high-impact GHG mitigation solutions (e.g. agroforestry, reforestation, and biochar application) and cross-cutting GHG mitigation solutions (renewable energy production, precision agriculture, no-till, integrated nutrient management, and biochar). This report is meant to provide initial analysis and establish a foundation for future agricultural decarbonization research - it is not an exhaustive analysis of all available studies. However, to our knowledge this report is the most comprehensive assessment of agricultural GHG emissions and associated mitigation opportunities in the United States to date. Future empirical research is recommended to close research gaps in different climates, soils, and agricultural systems. Meta-analyses for all mitigation solutions would increase confidence in the estimated GHG mitigation potentials. To conclude this report, we discuss short-term and long-term pathways for agricultural decarbonization in the United States, the importance of accounting for total GHG fluxes, potential co-benefits of agricultural decarbonization, analysis of study data confidence, and research gaps.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Can we have clean energy and grow our crops too? Solar siting on agricultural land in the United States

We report a record amount of large-scale solar development is proposed and under construction in the US Midwest, much of it on agricultural land. This article contributes to the social science literature on renewable energy and public acceptance by addressing stakeholder perspectives on developing utility-scale solar power on agricultural land and complex institutional dynamics that shape these siting decisions. How do stakeholders’ interactions coproduce solar siting decisions? How are the existing complex contexts of energy and agricultural systems affecting solar siting? Who are the stakeholders involved in agricultural solar siting, and how do their epistemic paradigms about using agricultural land, especially prime farmland, differ? To answer these questions, interviews were conducted and analyzed across energy, agriculture, government, and expert stakeholder groups, focusing on Michigan, with comparison to other states. The results provide a conceptual map of stakeholder interaction related to solar development on farmland and characterize the main epistemic paradigms shaping stakeholder conflict. Issues shaping agricultural community perceptions include identity and farmland, the decisions of local farmland renters and non-operating landlords, prime versus lower quality farmland, farm financial viability, and farmland as private property or a public good. Some scientists and engineers seek to alleviate conflicts and drawbacks of agricultural land conversion for solar use by combining farming and solar energy generation: a practice called agrivoltaics. We argue that agrivoltaics are currently treated as a technological fix by not accounting for stakeholder interaction in complex policy, community, and scientific institutions. We conclude by identifying interdisciplinary research priorities to develop socially robust designs.

14 SOLAR ENERGY↗
NASA NTRS2016

Safety and Certification Considerations for Expanding the Use of UAS in Precision Agriculture

The agricultural community is actively engaged in adopting new technologies such as unmanned aircraft systems (UAS) to help assess the condition of crops and develop appropriate treatment plans. In the United States, agricultural use of UAS has largely been limited to small UAS, generally weighing less than 55 lb and operating within the line of sight of a remote pilot. A variety of small UAS are being used to monitor and map crops, while only a few are being used to apply agricultural inputs based on the results of remote sensing. Larger UAS with substantial payload capacity could provide an option for site-specific application of agricultural inputs in a timely fashion, without substantive damage to the crops or soil. A recent study by the National Aeronautics and Space Administration (NASA) investigated certification requirements needed to enable the use of larger UAS to support the precision agriculture industry. This paper provides a brief introduction to aircraft certification relevant to agricultural UAS, an overview of and results from the NASA study, and a discussion of how those results might affect the precision agriculture community. Specific topics of interest include business model considerations for unmanned aerial applicators and a comparison with current means of variable rate application. The intent of the paper is to inform the precision agriculture community of evolving technologies that will enable broader use of unmanned vehicles to reduce costs, reduce environmental impacts, and enhance yield, especially for specialty crops that are grown on small to medium size farms.

Hayhurst, Kelly J.↗
NASA NTRS2018

Climate Shifts Within Major Agricultural Seasons for +1.5 and +2.0 °C Worlds: HAPPI Projections and AgMIP Modeling Scenarios

This study compares climate changes in major agricultural regions and current agricultural seasons associated with global warming of +1.5 or +2.0 °C above pre-industrial conditions. It describes the generation of climate scenarios for agricultural modeling applications conducted as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments. Climate scenarios from the Half a degree Additional warming, Projections, Prognosis and Impacts project (HAPPI) are largely consistent with transient scenarios extracted from RCP4.5 simulations of the Coupled Model Intercomparison Project phase 5 (CMIP5). Focusing on food and agricultural systems and top-producing breadbaskets in particular, we distinguish maize, rice, wheat, and soy season changes from global annual mean climate changes. Many agricultural regions warm at a rate that is faster than the global mean surface temperature (including oceans) but slower than the mean land surface temperature, leading to regional warming that exceeds 0.5 °C between the +1.5 and +2.0 °C Worlds. Agricultural growing seasons warm at a pace slightly behind the annual temperature trends in most regions, while precipitation increases slightly ahead of the annual rate. Rice cultivation regions show reduced warming as they are concentrated where monsoon rainfall is projected to intensify, although projections are influenced by Asian aerosol loading in climate mitigation scenarios. Compared to CMIP5, HAPPI slightly underestimates the CO2 concentration that corresponds to the +1.5 °C World but overestimates the CO2 concentration for the +2.0 °C World, which means that HAPPI scenarios may also lead to an overestimate in the beneficial effects of CO2 on crops in the +2.0 °C World. HAPPI enables detailed analysis of the shifting distribution of extreme growing season temperatures and precipitation, highlighting widespread increases in extreme heat seasons and heightened skewness toward hot seasons in the tropics. Shifts in the probability of extreme drought seasons generally tracked median precipitation changes; however, some regions skewed toward drought conditions even where median precipitation changes were small. Together, these findings highlight unique seasonal and agricultural region changes in the +1.5 °C and +2.0 °C worlds for adaptation planning in these climate stabilization targets.

Alexander C. Ruane↗
NASA NTRS2019

2018 NISAR Applications Workshop: Agriculture and Soil Moisture

Agricultural lands cover the globe and play an essential role in not only sustaining a growing global population, but can have significant implications on the Earth system through land use change (e.g., deforestation, grazing, etc.). As such, countries around the world have dedicated programs for managing these lands. Accurate and timely information concerning the status of agricultural crops (soil moisture, crop health, crop type, etc.) is essential to those nations’ anthropogenic and ecological health as well as economy. The joint NASA/US Department of Agriculture Agricultural Research Service (USDA-ARS) workshop focused on advancing agriculture and soil moisture applications by using remote sensing data from the NASA-ISRO Synthetic Aperture Radar (NISAR) mission (expected launch 2022). Participants included representatives from the international agriculture community that are key players in facilitating integration of Earth Observations into decision support workflows including US Federal Agencies, nonprofits, and private sector. They included scientists, technicians, and program managers with a responsibility for data acquisition and exploitation such as product development, delivery, and use, as well as capacity building. Discussions were held over two and a half days to convey the broader agriculture and soil moisture community information needs, the mission and procedures for various representative participants and programs involved in the delivery of geospatial products, and the capabilities and status of the NISAR mission. Case studies were presented to demonstrate the current state of practice in the use of SAR remote sensing for applications of direct importance for the agriculture and soil moisture communities. Eleven organizations presented their information requirements in response to a set of questions provided by the NASA team, then the NASA team responded by describing the degree to which NISAR could meet these requirements. Discussion ensued about needed data product specifications to increase utility (e.g., projection, latency, etc.), tools and capacity building.

Stavros, Natasha↗