Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Food security”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

Climate Change Impacts on Rice Farming Systems in Northwestern Sri Lanka

Sri Lanka has achieved tremendous progress since 1950 in crop production and food availability. Yields grew at an impressive rate until leveling off in the mid-eighties. Sri Lanka's population is anticipated to grow in the coming decades, creating an ever-greater demand for food security on the household, sub-district, regional, and national scales.The agricultural sector in Sri Lanka is vulnerable to climate shocks. An unusual succession of droughts and floods from 2008 to 2014 has led to both booms and busts in agricultural production, which were reflected in food prices. In both instances, the majority of farmers and consumers were adversely affected.At present the rice-farming systems are under stress due to inadequate returns for the farmers and difficulty in coping with shocks due to climate, pests, and diseases, and prices for produce. There are government price-support mechanisms, fertilizer-subsidy schemes, and crop insurance schemes, but the levels of the supports are modest and often do not effectively reach the farmers.

agriculture↗

Two-thirds of Global Cropland Area Impacted by Climate Oscillations

The El Nino Southern Oscillation (ENSO) peaked strongly during the boreal winter 2015-2016, leading to food insecurity in many parts of Africa, Asia and Latin America. Besides ENSO, the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) are known to impact crop yields worldwide. Here we assess for the first time in a unified framework the relationship between ENSO, IOD and NAO and simulated crop productivity at the sub-country scale. Our findings reveal that during 1961-2010, crop productivity is significantly influenced by at least one large-scale climate oscillation in two-thirds of global cropland area. Besides observing new possible links, especially for NAO in Africa and the Middle East, our analyses confirm several known relationships between crop productivity and these oscillations. Our results improve the understanding of climatological crop productivity drivers, which is essential for enhancing food security in many of the most vulnerable places on the planet.

IOD↗

Restoring Soil Fertility on Degraded Lands to Meet Food, Fuel, and Climate Security Needs via Perennialization

A continuously growing pressure to increase food, fiber, and fuel production to meet worldwide demand and achieve zero hunger has put severe pressure on soil resources. Abandoned, degraded, and marginal lands with significant agricultural constraints—many still used for agricultural production—result from inappropriately intensive management, insufficient attention to soil conservation, and climate change. Continued use for agricultural production will often require ever more external inputs such as fertilizers and herbicides, further exacerbating soil degradation and impeding nutrient recycling and retention. Growing evidence suggests that degraded lands have a large potential for restoration, perhaps most effectively via perennial cropping systems that can simultaneously provide additional ecosystem services. Here we synthesize the advantages of and potentials for using perennial vegetation to restore soil fertility on degraded croplands, by summarizing the principal mechanisms underpinning soil carbon stabilization and nitrogen and phosphorus availability and retention. We illustrate restoration potentials with example systems that deliver climate mitigation (cellulosic bioenergy), animal production (intensive rotational grazing), and biodiversity conservation (natural ecological succession). Perennialization has substantial promise for restoring fertility to degraded croplands, helping to meet future food security needs.

54 ENVIRONMENTAL SCIENCES↗

A Simulated High CO 2 Spaceflight Environment Increases Plant Preference for Ammonium as a Nitrogen Source.

Future long-duration missions will require a sustainable supply of food to support human crews. The spaceflight cabin environment often contains very high concentrations of CO 2 due to release of CO 2 by astronauts that is not completely scrubbed from the cabin, and it is therefore crucial to understand plant responses to elevated CO 2 (eCO 2 ) environments. Much focus has been given to changes in plant photosynthetic and performance parameters in response to eCO 2 , but the effects of eCO 2 on nitrogen (N) uptake are poorly understood. Shoot nitrate reduction may be reduced at eCO 2 , likely due to less reductant available for nitrate reduction because of reduced photorespiration and increased carbon fixation 1. Relative growth rate can be reduced at eCO 2 when N is provided only as nitrate and can be unaffected when N is supplied as ammonium 1. However, N uptake in response to eCO 2 has, to our knowledge, not yet been studied. An increased ‘preference’ for plants to take up N as ammonium at eCO 2 could have important implications for growth in the space environment, where N is currently only supplied as nitrate. In this study, novel stable isotope approaches were used in conjunction with hydroponics and isotope ratio mass spectrometry to determine the effect of eCO 2 on N preference for ammonium or nitrate in spring barley and lettuce when both N forms are provided equally. Several varieties of spring barley displayed increased ammonium preference at eCO 2 (720 ppm) compared to ambient CO 2 (410 ppm), though this was not true for all varieties 2. In most cases, increases in ammonium preference were driven by increases in ammonium uptake at eCO 2 and not decreases in nitrate uptake. Current research is assessing whether similar responses are observed in the candidate space crop lettuce, at levels of CO 2 like those observed on ISS (3000 ppm), and these results will also be presented. This work will enable the development of optimized nutrient regimes for candidate crops in space environments and the selection of crop varieties adapted to eCO 2 environments. Plants adapted to ammonium nutrition may play a role in future plant-based bioregenerative life support systems with higher ammonium concentrations due to waste recycling 3. Moreover, this research will further our understanding of plant responses to the eCO 2 environment brought about by climate change, allowing the development of future-proof crops that will help to maintain food security. References: 1. Bloom (2015). The increasing importance of distinguishing among plant nitrogen sources. Current Opinion in Plant Biology 25, 10-16. 2. Fountain (2023). Understanding interactions of barley (Hordeum vulgare) with soil nitrogen cycling activity and links to plant nitrogen preference. Ph.D. Thesis, The University of Sheffield. 3. Schiefloe et al. (2023). From urine to food and oxygen: effects of high and low NH4+:NO3- ratio on lettuce cultivated in a gas-tight hydroponic facility. Frontiers in Plant Science 14:1229476.

nitrogen↗

Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach

Context: The world is experiencing frequent extreme weather events like droughts, snowstorms, and shifting of seasons due to climate change. Increased frequency and severity of these extreme weather events threaten food security because agriculture depends on climate conditions. Impacts of climate change on the agricultural system not only occur at the grower’s level, but also cascade to other levels along the supply chain. Objective: In this study, we aim to quantify a wide range of economic impacts of different extreme climate events on different stages of a food supply chain. Methods: We chose the potato supply chain in Idaho as a case study. We developed a multi-echelon supply chain simulation model using an agent-based modeling (ABM) approach with five types of agents—farmers, shippers, processors, retailers, and logistics companies. In addition to the business-as-usual (BAU) scenario, we designed two climate-related disruption events—drought and snowstorm. We quantified the heterogeneous impacts at different stages of the supply chain for both fresh and processed potatoes using key performance indicators (KPIs) including revenues, prices, lead times, traded quantities, and food waste quantity. Results and Conclusion: The impacts of the disruption events are different on different agents in the supply chain for different product categories. The price hike of fresh potatoes is far higher than processed potatoes during disruption events. This price hike makes consumers switch to processed potatoes, which require more fresh potatoes as an input that further reinforces the price hike. However, because processed potatoes have an elastic demand, once their prices go up due to higher input cost, their demand drops. Non-contracted farmers gain additional revenues from the disruption events, whereas contracted farmers incur a loss due to lock-in price and lower than usual harvest. Significance: The methodology developed in this study could be applied to other food and agricultural supply chains for understanding the vulnerabilities at agent levels due to climate change disruption events. Furthermore, the findings would help develop mitigation strategies or policies to improve the well-being of the overall supply chain.

54 ENVIRONMENTAL SCIENCES↗

The Agricultural Model Intercomparison and Improvement Project: Phase I Activities by a Global Community of Science

The Agricultural Model Intercomparison and Improvement Project (AgMIP) was founded in 2010. Its mission is to improve substantially the characterization of world food security as affected by climate variability and change, and to enhance adaptation capacity in both developing and developed countries. The objectives of AgMIP are to: Incorporate state-of-the-art climate, crop/livestock, and agricultural economic model improvements into coordinated multi-model regional and global assessments of future climate impacts and adaptation and other key aspects of the food system. Utilize multiple models, scenarios, locations, crops/livestock, and participants to explore uncertainty and the impact of data and methodological choices. Collaborate with regional experts in agronomy, animal sciences, economics, and climate to build a strong basis for model applications, addressing key climate related questions and sustainable intensification farming systems. Improve scientific and adaptive capacity in modeling for major agricultural regions in the developing and developed world, with a focus on vulnerable regions. Improve agricultural data and enhance data-sharing based on their intercomparison and evaluation using best scientific practices. Develop modeling frameworks to identify and evaluate promising adaptation technologies and policies and to prioritize strategies.

farm crops↗

Editorial: Achieving Water-Energy-Food Nexus Sustainability: A Science and Data Need or a Need for Integrated Public Policy?

The benefits of addressing the water, energy, and food sectors in an integrated manner is gaining significant recognition. An integrated approach can provide improved resource use efficiencies, more coherent environmental policies, and an overall strategy for achieving sustainability in the three sectors, as outlined in the United Nations Sustainable Development Goals (SDG) 2 (Food), 6 (Water), and 7 (Energy). Societies are concerned with ensuring food security, avoiding wars over water, and creating opportunity by ensuring access to energy. To be effective, however, this approach needs to be adopted at all levels of societies including government, private and civil society and reinforced by management and planning methods. This special issue identifies different approaches that are either being conceptualized or tested to support the Water-Energy-Food (WEF) Nexus approach. The articles contribute to answering the question, “Is achieving Water-Energy-Food (WEF) Nexus Sustainability a science and data need or an integrated public policy need?” In either case, both natural and social sciences will need to combine to support science issues or integrated policy issues. The papers explore the ways in which science, data, and policy development could help to define integrative principles and policies for the three sectors. This approach could expand beyond the water, energy, and food sectors to include health, environment, trade, commerce, and international assistance thereby providing broad support to the SDGs. Moreover, this issue demonstrates that data combined with new technologies (tools and models) can support better decision-making when adopted by governments and the sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Marine wild-capture fisheries after nuclear war

Nuclear war, beyond its devastating direct impacts, is expected to cause global climatic perturbations through injections of soot into the upper atmosphere. Reduced temperature and sunlight could drive unprecedented reductions in agricultural production, endangering global food security. However, the effects of nuclear war on marine wild-capture fisheries, which significantly contribute to the global animal protein and micronutrient supply, remain unexplored. We simulate the climatic effects of six war scenarios on fish biomass and catch globally, using a state-of-the-art Earth system model and global process-based fisheries model. We also simulate how either rapidly increased fish demand (driven by food shortages) or decreased ability to fish (due to infrastructure disruptions), would affect global catches, and test the benefits of strong pre-war fisheries management. We find a decade-long negative climatic impact that intensifies with soot emissions, with global biomass and catch falling by up to 18 ± 3% and 29 ± 7% after a US-Russia war under business-as-usual fishing – similar in magnitude to the end-of-century declines under unmitigated global warming. When war occurs in an overfished state, increasing demand increases short-term (1-2 year) catch by at most ~30% followed by precipitous declines of up to ~70%, thus offsetting only a minor fraction of agricultural losses. However, effective pre-war management that rebuilds fish biomass could ensure a short-term catch buffer large enough to replace ~43 ± 35% of today’s global animal protein production. This buffering function in the event of a global food emergency adds to the many previously-known economic and ecological benefits of effective and precautionary fisheries management.

food from the ocean↗

Grain export restrictions during COVID-19 risk food insecurity in many low and middle income countries

Global food security is threatened by the effects of COVID-19 on international agricultural supply chains and locusts destroying crops and livelihoods in the Horn of Africa and South Asia. We quantify the possible impacts on global supplies and prices of wheat, rice and maize. We show that local production declines have moderate impacts on global prices and supply – but trade restrictions and precautionary purchases by a few key actors could create global food price spikes and severe local food shortages.

Grain export restrictions↗

Development of Laboratory Testbeds Simulating Real-World Greenhouse Gas Emissions

Climate change leads to drastic variations in the environment that can threaten food security. To protect the security and prosperity of the environment, new agricultural practices that mitigate greenhouse gas emissions need to be developed. Agriculture plays a large role in the emissions of greenhouse gases, thus a need for new practices. At present, testing landscape management practices for carbon sequestration and reduction of greenhouse gas emissions are expensive because such tests often require intricate field experiments. Laboratory tests on landscape management practices often fail to simulate and accurately represent the natural systems researchers intend to study. There are methods that can be used to make these laboratory tests more closely replicate natural systems for the improvement of agricultural lands used in biofuel and food production. The goal of this project is to develop a laboratory testbed replicating field conditions that will mimic field greenhouse gas emissions. To achieve this goal, we used soil cores taken from agricultural and marginal lands, then attached fiberglass wicks to improve the drainage system in the soil core to simulate a more natural hydraulic system. The soil cores with the wicks were used to compared to greenhouse gas emissions observed in the field. Our preliminary results suggest that the soil carbon dioxide and nitrous oxide flux from the agricultural land site were comparable to the soil cores equipped with the drainage wicks. The data suggests that laboratory testbeds can be used to mimic field greenhouse gas emissions if parameters, such as soil water content were in a set range. The laboratory testbed produces similar greenhouse gas emissions to the agricultural site when the soil water content was between 15-25%.

54 ENVIRONMENTAL SCIENCES↗

Global Patterns of Crop Yield Stability Under Additional Nutrient and Water Inputs

Agricultural production must increase to feed a growing and wealthier population, as well as to satisfy increasing demands for biomaterials and biomass-based energy. At the same time, deforestation and land-use change need to be minimized in order to preserve biodiversity and maintain carbon stores in vegetation and soils. Consequently, agricultural land use needs to be intensified in order to increase food production per unit area of land. Here we use simulations of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 to assess implications of input-driven intensification (water, nutrients) on crop yield and yield stability, which is an important aspect in food security. We find region- and crop-specific responses for the simulated period 1980+/-2009 with broadly increasing yield variability under additional nitrogen inputs and stabilizing yields under additional water inputs (irrigation), reflecting current patterns of water and nutrient limitation. The different models of the GGCMI ensemble show similar response patterns, but model differences warrant further research on management assumptions, such as variety selection and soil management, and inputs as well as on model implementation of different soil and plant processes, such as on heat stress, and parameters. Higher variability in crop productivity under higher fertilizer input will require adequate buffer mechanisms in trade and distribution/storage networks to avoid food price volatility.

Maize↗

Multi-Level Impacts of Extreme Climate-Related Events on Food Supply Chain: Idaho Potato's Case Study

Background: The world is experiencing frequent extreme weather events like droughts, floods, snowstorms, and shifting of seasons due to climate change. Increasing frequencies and severity of these extreme weather events threaten food security because agriculture is extremely vulnerable to climate change. Higher temperature reduces overall yields of the desirable crops but proliferates weeds and harmful pests. Current data shows that every year U.S. farmers spend more than 11 billion USD to fight weeds and this number is expected to rise in the coming years due to climate change. Due to droughts, the water required for irrigation is becoming scarcer. Since many areas are becoming climatically unusable for crop production, the amount of farmland area is shrinking rapidly. In addition, changes in precipitation patterns are causing crop failures and negatively impacting expected yields. In this study, we investigated how different extreme climate events impact different stages of a food supply chain. Approach: As a case study, we chose Idaho’s potato supply chain (SC). Idaho is the top potato producing state in the U.S. and contributes around 30% of the nation’s potato production. Using the agent-based modeling (ABM) approach, we developed a multi-echelon potato supply chain computer simulation model with six types of agents – seed producers, farmers, shippers, processors, retailers, and logistics companies. In addition to the baseline scenario, we developed two additional climate-related disruption events – drought and snowstorm. We investigated how each of these disruption events impacts different stakeholders across the supply chain in terms of revenue and some other key performance metrics such as lead time, food waste, number of delayed orders, and order fulfillment rate. Results: Extreme climate events not only impact the growers but there is also cascading ripple effects downstream of the supply chain. The methodology developed in this study could be applied to other food and agricultural SC to understand the vulnerabilities of the different links. The findings would potentially help to adopt new policies for the well-being of the overall SC.

54 ENVIRONMENTAL SCIENCES↗

Famine Early Warning Systems and Remote Sensing Data

This book describes the interdisciplinary work of USAID's Famine Early Warning System Network (FEWS NET) and its influence on how food security crises are identified, documented and the kind of responses that result. The book describes FEWS NET's systems and methods for using satellite remote sensing to identify and describe how biophysical hazards impact the lives and livelihoods of the population where they occur. It presents several illustrative case studies that will demonstrate the integration of both physical and social science disciplines in its work. FEWS NET s operational needs have driven science in biophysical remote sensing applications through its collaboration with the US Geological Survey, the National Aeronautics and Space Administration, National Oceanographic and Atmospheric Administration, and US Department of Agriculture, as well as methodologies in the social science domain through its support of the US Agency for International Development, UNWorld Food Program and numerous international non-governmental organizations such as Save the Children, Oxfam and others. Because FEWS NET is an organization that must provide a global picture of food insecurity to decision makers, the information it relies on are by necessity observable and able to be documented. Thus many aspects of traditional livelihood analysis, for example, cannot be used by FEWS NET as they rely upon relationships, and ways of expressing power and knowledge at the local scale that cannot be easily scaled up to express variations in access to food at a community level. The book focuses on the ways that remote sensing information is transformed into an understanding of the actions that must be taken in order to ensure that lives and livelihoods are protected, including describing the remote sensing observations and models needed to identify hazards and the information gathering requirements and analytical frameworks needed to understand their impact. Its focus is primarily analysis conducted in Africa, but also touches upon FEWS NET s work in Central America, Haiti and Afghanistan. As an organization that seeks to integrate social and physical science methodologies and strategies into its work on a daily basis, it is a fascinating and rich example of interdisciplinary knowledge generation and innovation.

Brown, Molly E.↗

An Interoperable, Agricultural Information System Based on Satellite Remote Sensing Data

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of US. agricultural products and for global food security. The Goddard Space Flight Center Earth Sciences Data and Information Services Center Distributed Active Archive Center (GES DISC DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM Online Visualization and Analysis System (TOVAS), which will operationally provide satellite remote sensing data products (e.g., rainfall) and services. The data products will include crop condition and yield prediction maps, generated from a crop growth model with satellite data inputs, in collaboration with the USDA Agricultural Research Service. The AIS will enable the remote, interoperable access to distributed data, by using the GrADS-DODS Server (GDS) and by being compliant with Open GIS Consortium standards. Users will be able to download individual files, perform interactive online analysis, as well as receive operational data flows. AIS outputs will be integrated into existing operational decision support systems for global crop monitoring, such as those of the USDA Foreign Agricultural Service and the U.N. World Food Program.

Teng, William↗

Land-use and atmospheric shifts jointly amplify U.S. drought-driven crop losses

Agricultural drought (AD) poses a major threat to food security, yet its future risk remains uncertain under co-evolving atmospheric conditions and land-use trajectories. Using an integrated, multi-sector modeling framework, we project AD risks for major crops across the contiguous United States (CONUS) through 2055 under a range of plausible futures that capture thermodynamic changes and land-use and land-cover change (LULCC) trajectories. Model projections reveal that drought-driven crop production losses increase sharply by nearly 60% for corn, 250% for wheat, and 135% for soybean relative to historical levels. The primary drivers of these increases, which include atmospheric shifts and LULCC, vary by region and crop type. LULCC acting as an important risk amplifier in regions experiencing cropland expansion into drought-prone regions, such as the Great Plains and northwestern U.S. Wheat exhibits the largest projected loss increases, a result that remains robust across scenarios. These findings highlight that interactions between atmospheric conditions and land-use trajectories shape future agricultural drought risk and should be jointly considered to support effective adaptation and food-system planning.

Yao, Lili↗

A Framework for the Cross-Sectoral Integration of Multi-Model Impact Projections: Land Use Decisions Under Climate Impacts Uncertainties

Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impactmodel setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making

farmlands↗

Trade can buffer climate-induced risks and volatilities in crop supply

Climate change is intensifying the frequency and severity of extreme events, posing challenges to food security. Corn, a staple crop for billions, is particularly vulnerable to heat stress, a primary driver of yield variability. While many studies have examined climate impact on average corn yields, little attention has been given to the climate impact on production volatility. This study investigates the future volatility and risks associated with global corn supply under climate change, evaluating the potential benefits of two key adaptation strategies: irrigation and market integration. A statistical model is employed to estimate corn yield response to heat stress and utilize NEX-GDDP-CMIP6 climate data to project future production volatility and risks of substantial yield losses. Three metrics are introduced to quantify these risks: Sigma (σ), the standard deviation of year-on-year yield change, which reflects overall yield volatility; Rho (ρ), the risk of substantial loss, defined as the probability of yield falling below a critical threshold; and Beta (β), a relative risk coefficient that captures the volatility of a region's corn production compared to the globally integrated market. The analysis reveals a concerning trend of increasing year-on-year yield volatility (σ) across most regions and climate models. This volatility increase is significant for key corn-producing regions like Brazil and the United States. While irrigated corn production exhibits a smaller rise in volatility, suggesting irrigation as a potential buffer against climate change impacts, it is not a sustainable option as it can cause groundwater depletion. On the other hand, global market integration reduces overall volatility and market risks significantly with less sustainability concerns. Furthermore, these findings highlight the importance of a multidimensional approach to adaptation in the food sector. While irrigation can benefit individual farmers, promoting global market integration offers a broader solution for fostering resilience and sustainability across the entire food system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Flood Monitoring and Crop Damage Assessment

In recent years, the occurrence and impact of inland and coastal flood events have become more frequent and damaging, especially within agricultural fields, due to the global climate change and consistent sea level rise. Monitoring and measuring the magnitude of flood events in a timely manner and assessing the subsequent crop damages accurately are precursors in minimizing detrimental consequences that could potentially lead to a global food security crisis. Traditional gauge-based measurements with sophisticated hydrological models are capable of monitoring flood events precisely but limited within the smaller spatial extent, time-consuming, and costly. In recent decades, advancement in airborne- and satellite-based remote sensing technologies offering products at a daily global spatial extent with various spectral resolution helps address the shortcomings of the traditional in situ approaches in flood monitoring. Furthermore, the methods such as classification and band ratioing using remote sensing products are simple and effective in assessing flood-induced agricultural damages. The combination of remote sensing products and geographic information systems along with the current development in web mapping, users now can get near real-time flood monitoring and crop damage assessments, albeit dependent upon the quality of available data. A case study to quantify the impact of the 2011 Missouri Mississippi River flooding on the surrounding cornfield was performed through a regression model. The model was trained using historical daily NDVI and corn yield across Nebraska and Missouri, and the overall accuracy in estimating corn yield was about 90%. The method implemented in this localized case study could be extended at a larger geographical scale.

Flood monitoring↗