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At least 199 records · Page 11Linked to original sources

Automated Cropland Classification Algorithm (ACCA) for California using multi-sensor remote sensing

Increasing pressure to feed the growing population with scarce water resources requires accurate and routine cropland mapping. This paper develops and implements a rule-based automated cropland classification algorithm (ACCA) using multi-sensor remote sensing data. Pixel-by-pixel accuracy assessments showed that ACCA produced an overall accuracy of 96 percent (K hat = 0.8) when tested using independent data layers. Furthermore, ACCA-generated county cropland areas showed high agreement (R-square values 0.94) when compared with three independent data sources: (a) US Department of Agriculture (USDA) cropland data layer derived cropland areas, (b) county specific crop acreage data from the Farm Service Agency, and (c) the Census of Agriculture data for the 58 counties in California. Our results demonstrate the ability of ACCA to generate cropland extent and areas over space and time, in an automated fashion with high degree of accuracies year after year, greatly contributing to food and water security analysis and decision making.

California↗

The role of fish in a globally changing food system

Applied research and adaptive management techniques can assist with the necessary evolution of sustainable food systems to include a stronger emphasis on fish and other aquatic organisms. Fish provide key macro‐ and micronutrients and protein, are low in saturated fat, and have been linked to a wide array of health benefits for the developing fetus, infants, and adults. Diet quality is not only important for reducing nutrient deficiency, but is now regarded as essential for preventing chronic diseases such as obesity, type 2 diabetes, hypertension, coronary artery disease, and cancers. Small‐scale aquaculture also contributes to poverty alleviation and promotes food and nutrition security in less developed parts of the world. Climate change and climate variability influence aquatic ecosystems and fish populations. Ocean acidification is most commonly cited as being detrimental to marine invertebrates and algae that build carbonate structures.

Book chapter↗

Enhancing the application of Earth observations for improved environmental decision-making using the Early Warning eXplorer (EWX)

The mitigation of losses due to extreme climate events and long-term climate adaptation requires climate informed decision-making. In the past few decades, several remote sensing and modeled-based Earth observations (EOs) have been developed to provide an unprecedented global overview and routine monitoring of climate and its impacts on vegetation and hydrologic conditions, with the goal of supporting informed decision-making. However, their usage in decision-making is particularly limited in climate-risk vulnerable and in situ data-scarce regions such as sub-Saharan Africa, due to lack of access to EOs. Here, we describe the Early Warning eXplorer (EWX), which was developed to address this crucial limitation and facilitate the application of EOs in decision-making, particularly in the food and water-insecure regions of the world. First, the EWX's core framework, which includes (i) the Viewer, (ii) GeoEngine, and (iii) Support Applications, is described. Then, a comprehensive overview of the Viewer, which is a web-based interface used to access EOs, is provided. This includes a description of (i) the maps and associated features to access gridded EO data and anomalies for different temporal averaging periods, (ii) time series graphs and associated features to access EOs aggregated over polygons such as administrative boundaries, and (iii) commonly used EOs served by the EWX that provide assessments of climate and vegetation conditions. Next, examples are provided to demonstrate how EWX can be used to monitor development, progression, spatial extent, and severity of climate-driven extreme events to support timely decisions related to mitigation of food insecurity and flooding impacts. Finally, the value of a regional implementation of EWX at the Regional Centre for Mapping of Resources for Development (RCMRD) in Nairobi, Kenya, is highlighted. Regional implementation of the EWX facilitates access to regionally focused EOs and their availability at polygon boundaries most relevant to the local decision-makers. Similar instances of EWX implemented in other regions, especially those susceptible to food and water security, will likely further enhance the application of EOs for informed decision-making.

Frontiers in Climate↗

Dynamics of green and blue water supply stress index across major global cropland basins

Global food and water insecurity could be serious problems in the upcoming decades with growing demands from the increasing global population and more frequent effect of climatic extremes. As the available water resources are diminishing and facing continuous stress, it is crucial to monitor water demand and water availability to understand the associated water stresses. This study assessed the water stress by applying the water supply stress index (WaSSI) in relation to green (WaSSI G ) and blue (WaSSI B ) water resources across six major cropland basins including the Mississippi (North America), San Francisco (South America), Nile (Africa), Danube (Europe), Ganges-Brahmaputra (Asia), and Murray-Darling (Australia) for the past 17-years (2003–2019). The WaSSI G and WaSSI B results indicated that the Murray-Darling Basin experienced the most severe (maximum WaSSI G and WaSSI B anomalies) green and blue water stresses and the Mississippi Basin had the least. All basins had both green and blue water stresses for at least 35% (6 out of 17 years) of the study period. The interannual variations in green water stress were driven by both crop water demand and green water supply, whereas the blue water stress variations were primarily driven by blue water supply. The WaSSI G and WaSSI B provided a better understanding of water stress (blue or green) and their drivers (demand or supply driven) across cropland basins. This information can be useful for basin-specific resource mobilization and interventions to ensure food and water security.

Frontiers in Climate↗

Implications of zoonoses from hunting and use of wildlife in North American arctic and boreal biomes: Pandemic potential, monitoring, and mitigation

The COVID-19 pandemic has re-focused attention on mechanisms that lead to zoonotic disease spillover and spread. Commercial wildlife trade, and associated markets, are recognized mechanisms for zoonotic disease emergence, resulting in a growing global conversation around reducing human disease risks from spillover associated with hunting, trade, and consumption of wild animals. These discussions are especially relevant to people who rely on harvesting wildlife to meet nutritional, and cultural needs, including those in Arctic and boreal regions. Global policies around wildlife use and trade can impact food sovereignty and security, especially of Indigenous Peoples. We reviewed known zoonotic pathogens and current risks of transmission from wildlife (including fish) to humans in North American Arctic and boreal biomes, and evaluated the epidemic and pandemic potential of these zoonoses. We discuss future concerns, and consider monitoring and mitigation measures in these changing socio-ecological systems. While multiple zoonotic pathogens circulate in these systems, risks to humans are mostly limited to individual illness or local community outbreaks. These regions are relatively remote, subject to very cold temperatures, have relatively low wildlife, domestic animal, and pathogen diversity, and in many cases low density, including of humans. Hence, favorable conditions for emergence of novel diseases or major amplification of a spillover event are currently not present. The greatest risk to northern communities from pathogens of pandemic potential is via introduction with humans visiting from other areas. However, Arctic and boreal ecosystems are undergoing rapid changes through climate warming, habitat encroachment, and development; all of which can change host and pathogen relationships, thereby affecting the probability of the emergence of new (and re-emergence of old) zoonoses. Indigenous leadership and engagement in disease monitoring, prevention and response, is vital from the outset, and would increase the success of such efforts, as well as ensure the protection of Indigenous rights as outlined in the United Nations Declaration on the Rights of Indigenous Peoples. Partnering with northern communities and including Indigenous Knowledge Systems would improve the timeliness, and likelihood, of detecting emerging zoonotic risks, and contextualize risk assessments to the unique human-wildlife relationships present in northern biomes.

Frontiers in Public Health↗

Classifying crop types using two generations of hyperspectral sensors (Hyperion and DESIS) with machine learning on the cloud

Advances in spaceborne hyperspectral (HS) remote sensing, cloud-computing, and machine learning can help measure, model, map and monitor agricultural crops to address global food and water security issues, such as by providing accurate estimates of crop area and yield to model agricultural productivity. Leveraging these advances, we used the Earth Observing-1 (EO-1) Hyperion historical archive and the new generation DLR Earth Sensing Imaging Spectrometer (DESIS) data to evaluate the performance of hyperspectral narrowbands in classifying major agricultural crops of the U.S. with machine learning (ML) on Google Earth Engine (GEE). EO-1 Hyperion images from the 2010–2013 growing seasons and DESIS images from the 2019 growing season were used to classify three world crops (corn, soybean, and winter wheat) along with other crops and non-crops near Ponca City, Oklahoma, USA. The supervised classification algorithms: Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes (NB), and the unsupervised clustering algorithm WekaXMeans (WXM) were run using selected optimal Hyperion and DESIS HS narrowbands (HNBs). RF and SVM returned the highest overall producer’s, and user’s accuracies, with the performances of NB and WXM being substantially lower. The best accuracies were achieved with two or three images throughout the growing season, especially a combination of an earlier month (June or July) and a later month (August or September). The narrow 2.55 nm bandwidth of DESIS provided numerous spectral features along the 400–1000 nm spectral range relative to smoother Hyperion spectral signatures with 10 nm bandwidth in the 400–2500 nm spectral range. Out of 235 DESIS HNBs, 29 were deemed optimal for agricultural study. Advances in ML and cloud-computing can greatly facilitate HS data analysis, especially as more HS datasets, tools, and algorithms become available on the Cloud.

Remote Sensing↗

Crop water productivity from cloud-Based landsat helps assess California’s water savings

Demand for food and water are increasing while the extent of arable land and accessible fresh water are decreasing. This poses global challenges as economies continue to develop and the population grows. With agriculture as the leading consumer of water, better understanding how water is used to produce food may help support the increase of Crop Water Productivity (CWP; kg/m 3 ), the ratio of crop output per unit of water input (or crop per drop). Previous large-scale CWP studies have been useful for broad water use modeling at coarser resolutions. However, obtaining more precise CWP, especially for specific crop types in a particular area and growing season as outlined here are important for informing farm-scale water management decision making. Therefore, this study focused on California’s Central Valley utilizing high-spatial resolution satellite imagery of 30 m (0.09 hectares per pixel) to generate more precise CWP for commonly grown and water-intensive irrigated crops. First, two products were modeled and mapped. 1. Landsat based Actual Evapotranspiration (ET a ; mm/d) to determine Crop Water Use (CWU; m 3 /m 2 ), and 2. Crop Productivity (CP; kg/m 2 ) to estimate crop yield per growing season. Then, CWP was calculated by dividing CP by CWU and mapped. The amount of water that can be saved by increasing CWP of each crop was further calculated. For example, in the 434 million m 2 study area, a 10% increase in CWP across the 9 crops analyzed had a potential water savings of 31.5 million m 3 of water. An increase in CWP is widely considered the best approach for saving maximum quantities of water. This paper proposed, developed, and implemented a workflow of combined methods utilizing cloud computing based remote sensing data. The environmental implications of this work in assessing water savings for food and water security in the 21st century are expected to be significant.

California↗

Comparing DESIS hyperspectral and Landsat 10 simulated superspectral data for crop type classification in California's Central Valley

To advance crop type mapping in support of global food and water security, this study compared three spectral configurations: (A) the full 60-band DLR Earth Sensing Imaging Spectrometer (DESIS) hyperspectral narrowband (HNB) dataset, (B) a 14-band subset of DESIS-derived HNBs aligned with the planned Landsat 10 (formerly Landsat Next) spectral configuration (400–1000 nm), and (C) DESIS-based simulations of Landsat 10 superspectral broadbands. The analysis was conducted in California’s Central Valley, hereafter referred to as “the Central Valley”, during the peak growing month of August. DESIS imagery from August 2021, 2022, and 2023 was used sequentially for model development, testing, and independent validation. Over these three years, DESIS provided extensive hyperspectral coverage of much of the 4 million hectares in the Central Valley’s. Analyses were performed on Google Earth Engine using two pixel-based supervised classifiers, Random Forest (RF) and Support Vector Machine (SVM), to differentiate three major crop classes: row crops, grapes and tree crops, and winter wheat/fallow/other. The highest overall accuracy (86%) was achieved using SVM in combination with either the full DESIS hyperspectral dataset or the 14 DESIS narrowbands corresponding to Landsat 10. This finding aligns with earlier studies showing a small number of strategically positioned narrowbands can be optimal for crop type classification. Use of the narrowband datasets resulted in substantially higher accuracy (overall accuracy of 86%) compared to the simulated Landsat 10 broadbands (overall accuracy of 75%), supporting previous studies highlighting the utility of narrowbands. Despite the high accuracy using August imagery, the study indicates more granular crop type classification will require multi-temporal observations spanning the full phenological cycle (June–October), especially for a large number of crop classes. Acquiring task-based hyperspectral imagery over such large areas throughout the growing season remains operationally challenging. In contrast, Landsat 10 superspectral imagery could provide routine coverage across seasons and years that is practical and scalable for future large area crop type mapping and agricultural monitoring.

California↗

Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, are starting points to develop higher-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as for assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015–2016.

Remote Sensing↗

The Global food‐energy‐water nexus

Water availability is a major factor constraining humanity's ability to meet the future food and energy needs of a growing and increasingly affluent human population. Water plays an important role in the production of energy, including renewable energy sources and the extraction of unconventional fossil fuels that are expected to become important players in future energy security. The emergent competition for water between the food and energy systems is increasingly recognized in the concept of the “food‐energy‐water nexus.” The nexus between food and water is made even more complex by the globalization of agriculture and rapid growth in food trade, which results in a massive virtual transfer of water among regions and plays an important role in the food and water security of some regions. This review explores multiple components of the food‐energy‐water nexus and highlights possible approaches that could be used to meet food and energy security with the limited renewable water resources of the planet. Despite clear tensions inherent in meeting the growing and changing demand for food and energy in the 21st century, the inherent linkages among food, water, and energy systems can offer an opportunity for synergistic strategies aimed at resilient food, water, and energy security, such as the circular economy.

Reviews of Geophysics↗

Warming-driven erosion and sediment transport in cold regions

Rapid atmospheric warming since the mid-twentieth century has increased temperature-dependent erosion and sediment-transport processes in cold environments, affecting food, energy and water security. In this Review, we summarize landscape changes in cold environments and provide a global inventory of increases in erosion and sediment yield driven by cryosphere degradation. Anthropogenic climate change, deglaciation, and thermokarst disturbances are causing increased sediment mobilization and transport processes in glacierized and periglacierized basins. With continuous cryosphere degradation, sediment transport will continue to increase until reaching a maximum (peak sediment). Thereafter, transport is likely to shift from a temperature-dependent regime toward a rainfall-dependent regime roughly between 2100–2200. The timing of the regime shift would be regulated by changes in meltwater, erosive rainfall and landscape erodibility, and complicated by geomorphic feedbacks and connectivity. Further progress in integrating multisource sediment observations, developing physics-based sediment-transport models, and enhancing interdisciplinary and international scientific collaboration is needed to predict sediment dynamics in a warming world.

Nature--Reviews of Earth and Environment↗

U.S. Geological Survey—Energy and wildlife research annual report for 2017

Introduction Terrestrial and aquatic ecosystems provide valuable services to humans and are a source of clean water, energy, raw materials, and productive soils. The Nation’s food supply is more secure because of wildlife. For example, native pollinators enhance agricultural crops, and insect-eating bats provide pest control services worth billions of dollars to farmers annually. Fish and wildlife are also vital to a vibrant outdoor recreation and tourism industry. Recreational activities, such as hunting, shooting, boating, and angling, generated \$1.1 billion in excise taxes paid to State wildlife agencies in 2017. National parks, wildlife refuges, and monuments accounted for $35 billion in economic output and 318,000 jobs nationwide in 2016. Additional economic benefits are generated from the use and enjoyment of wildlife in State-owned lands and waters. Although the United States is rich in natural resources, human activity continues to place new pressures on fish and wildlife and the habitats they rely on. The United States became the world’s top producer of petroleum and natural gas products in 2012, surpassing Russia’s natural gas production levels in 2009 and Saudi Arabia’s petroleum production in 2013. The U.S. Energy Information Administration projects that the demand for liquid fuel, natural gas, and renewable energy will show strong growth in the next 20 years. Wind energy has demonstrated consistent growth since 2007 with now more than 53,000 wind turbines contributing to power grids in 41 States, Guam, and Puerto Rico. Solar energy has seen rapid growth since 2013 and made up nearly one-third of the total electricity generation additions in 2016. Yet as our Nation works to advance energy security and sustain wildlife, some conflicts have surfaced. Impacts of an expanding energy infrastructure include fragmentation and loss of habitat as well as mortality of birds, bats, fish, and other animals from interactions with energy generation facilities. Because energy development can often occur in wildlife habitats, ecological science can help guide project siting and operational decisions to areas that present the lowest risk to wildlife and energy developers. To address these challenges and make the most of new opportunities, the U.S. Geological Survey is producing innovative science to develop workable solutions that can help sustain wildlife and the habitat they rely upon, while allowing informed development.

Circular↗

Spatial variation in density of American black bears in northern Yellowstone National Park

The quality and availability of resources are known to influence spatial patterns of animal density. In Yellowstone National Park, relationships between the availability of resources and the distribution of grizzly bears ( Ursus arctos ) have been explored but have yet to be examined in American black bears ( Ursus americanus ). We conducted non-invasive genetic sampling during 2017–2018 (mid-May to mid-July) and applied spatially explicit capture-recapture models to estimate density of black bears and examine associations with landscape features. In both years, density estimates were higher in forested vegetation communities, which provide food resources and thermal and security cover preferred by black bears, compared with non-forested areas. In 2017, density also varied by sex, with female densities being higher than males. Based on our estimates, the northern range of Yellowstone National Park supports one of the highest densities of black bears (20 black bears/100 km 2 ) in the northern Rocky Mountains (6–12 black bears/100 km 2 in other regions). Given these high densities, black bears could influence other wildlife populations more than previously thought, such as through displacement of sympatric predators from kills. Our study provides the first spatially explicit estimates of density for black bears within an ecosystem that contains the majority of North America's large mammal species. Our density estimates provide a baseline that can be used for future research and management decisions of black bears, including efforts to reduce human–bear conflicts.

Montana, Wyoming↗

Interannual to multidecadal climate forcings on groundwater resources of the U.S. West Coast

Study region The U.S. West Coast, including the Pacific Northwest and California Coastal Basins aquifer systems. Study focus Groundwater response to interannual to multidecadal climate variability has important implications for security within the water–energy–food nexus. Here we use Singular Spectrum Analysis to quantify the teleconnections between AMO, PDO, ENSO, and PNA and precipitation and groundwater level fluctuations. The computer program DAMP was used to provide insight on the influence of soil texture, depth to water, and mean and period of a surface infiltration flux on the damping of climate signals in the vadose zone. New hydrological insights for the region We find that PDO, ENSO, and PNA have significant influence on precipitation and groundwater fluctuations across a north-south gradient of the West Coast, but the lower frequency climate modes (PDO) have a greater influence on hydrologic patterns than higher frequency climate modes (ENSO and PNA). Low frequency signals tend to be preserved better in groundwater fluctuations than high frequency signals, which is a function of the degree of damping of surface variable fluxes related to soil texture, depth to water, mean and period of the infiltration flux. The teleconnection patterns that exist in surface hydrologic processes are not necessarily the same as those preserved in subsurface processes, which are affected by damping of some climate variability signals within infiltrating water.

California, Oregon, Washington↗

The 3D Elevation Program: summary of program direction

The 3D Elevation Program (3DEP) initiative responds to a growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation's natural and constructed features. The National Enhanced Elevation Assessment (NEEA), which was completed in 2011, clearly documented this need within government and industry sectors. The results of the NEEA indicated that enhanced elevation data have the potential to generate $13 billion in new benefits annually. The benefits apply to food risk management, agriculture, water supply, homeland security, renewable energy, aviation safety, and other areas. The 3DEP initiative was recommended by the National Digital Elevation Program and its 12 Federal member agencies and was endorsed by the National States Geographic Information Council (NSGIC) and the National Geospatial Advisory Committee (NGAC).

Fact Sheet↗

Expansion of urban area and wastewater irrigated rice area in Hyderabad, India

The goal of this study was to investigate land use changes in urban and peri-urban Hyderabad and their influence on wastewater irrigated rice using Landsat ETM + data and spectral matching techniques. The main source of irrigation water is the Musi River, which collects a large volume of wastewater and stormwater while running through the city. From 1989 to 2002, the wastewater irrigated area along the Musi River increased from 5,213 to 8,939 ha with concurrent expansion of the city boundaries from 22,690 to 42,813 ha and also decreased barren lands and range lands from 86,899 to 66,616 ha. Opportunistic shifts in land use, especially related to wastewater irrigated agriculture, were seen as a response to the demand for fresh vegetables and easy access to markets, exploited mainly by migrant populations. While wastewater irrigated agriculture contributes to income security of marginal groups, it also supplements the food basket of many city dwellers. Landsat ETM + data and advanced methods such as spectral matching techniques are ideal for quantifying urban expansion and associated land use changes, and are useful for urban planners and decision makers alike. ?? 2011 Springer Science+Business Media B.V.

Irrigation and Drainage Systems↗

Substrate discrimination in burying beetles, Nicrophorus orbicollis (Coleoptera: Silphidae)

Burying beetles Nicrophorus orbicollis (Coleoptera: Silphidae) secure and bury small vertebrate carcasses as a food resource for their offspring and themselves. Burial may take place at the point of carcass discovery or at some distance from that site. Burying beetles were tested to determine if they discriminate between different substrates when burying a carcass. Three substrates were presented simultaneously. Substrate one contained soil from typical beetle habitat; substrates two and three contained 2:1 and 5:1 ratios, respectively, of soil and a senescent prairie grass ( Panicum virgatum ), which added a bulk structural component to the soil. Beetles generally moved and buried the carcass within 24 hours. Results for both paired and individual trials suggest that burying beetles discriminate between substrates, preferring substrates with added bulk over those without.

Journal of the Kansas Entomological Society↗

Brackish groundwater and its potential as a resource in the southwestern United States

Secure, reliable, and sustainable water resources are fundamental to food production, energy independence, and the health of humans and ecosystems. But the large-scale development of fresh groundwater resources has stressed aquifers in some areas, causing declines in the amount of groundwater in storage and decreases in discharge to surface-water bodies like rivers and springs (Reilly and others, 2008). In some parts of the southwestern United States, the water supply is not adequate to meet demand without substantial effects on groundwater storage or surface discharge, and severe drought intensifies the stresses affecting water resources. In support of the national census of water resources, the U.S. Geological Survey (USGS) completed the national brackish groundwater assessment to provide information about brackish groundwater as a potential resource to augment or replace freshwater supplies (Stanton and others, 2017). The objectives of the brackish groundwater assessment were to consolidate available data into a comprehensive database of brackish groundwater resources in the United States and to produce a summary report about the distribution, physical and chemical characteristics, and use of brackish groundwater. This fact sheet summarizes the occurrence of brackish groundwater and factors affecting its usability in the southwestern United States (specifically the Southwest Basins region) reported for the national study. The map below (fig. 1) summarizes the brackish zones for the five largest principal aquifers within the southwestern United States, along with groundwater resources in the remaining part of the region (Reilly and others, 2008).

Fact Sheet↗