USGS Science⌕ Search

SEARCH · USGS Science

Results for “GeoSpatial Solutions”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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

28 records · Page 2Linked to original sources
USGS2011

Developing an institutional framework to incorporate ecosystem services into decision making-Proceedings of a workshop

The routine and effective incorporation of ecosystem services information into resource management decisions requires a careful consideration of the value of goods and services provided by natural systems. A multidisciplinary workshop was held in October 2008 on "Developing an Institutional Framework to Incorporate Ecosystem Services into Decision Making." This report summarizes that workshop, which focused on examining the relationship between an institutional framework and consideration of ecosystem services in resource management decision making. This workshop was the third in a series of three preconference workshops associated with ACES 2008 (A Conference on Ecosystem Services): Using Science for Decision Making in Dynamic Systems. These workshops were designed to explore the ACES 2008 theme on decision making and how the concept of ecosystem services can more effectively be incorporated into conservation, restoration, resource management, and development decisions. Preconference workshop 1, "Developing a Vision: Incorporating Ecosystem Services into Decision Making," was held April 15, 2008, in Cambridge, MA. In this workshop, participants addressed what would have to happen to make ecosystem services more routinely and effectively used in conservation, restoration, resource management, and development decisions, and identified some key challenges to developing the analytical framework (Hogan and others, 2009). Preconference workshop 2, "Developing an Analytical Framework: Incorporating Ecosystem Services into Decision Making," was held July 28, 2008, in Naples, FL, and focused on the analytical process and identification of research priorities for ecosystem services, their production and use, their spatial and temporal characteristics, their relationship with natural systems, and their interdependencies (Hogan and others, 2010). The summary presented here synthesizes the discussion at workshop 3 and considers how institutional structures and policy instruments can be used to achieve the vision developed in workshop 1, while recognizing the analytical capabilities and limitations identified in workshop 2. Our purpose was to identify how to use ecosystem service information more effectively and broadly in resource management and development decisions. We recognized the need to facilitate an integrated understanding of (1) the natural capital that produces ecosystem services; (2) the geospatial and temporal aspects of ecosystem service production, values, and use; (3) the value of ecosystem services (monetary and nonmonetary); and (4) institutional instruments, processes, and structures (property rights, laws, governance structures, and courts, for example). Interdisciplinary collaboration and understanding is beneficial and needs to engage stakeholders. The appropriate use of institutional structures, including markets, to integrate ecosystem services into decision making depends on the players and characteristics of the specific situation (such as stakeholders, the ecosystem, resources, and the political environment). Incorporating ecosystem service values into decisions requires consideration of place-based social, cultural, economic, and landscape characteristics and institutions. Thus, a single, prescribed solution will not work-various institutional strategies must be used in different situations. Market-based approaches require appropriate regulations, monitoring, and enforcement, depending on the situation and place. Further, market approaches will need to be coupled with nonmarket approaches into an integrated institutional framework.

Open-File Report↗
USGS2012

A program for handling map projections of small-scale geospatial raster data

Scientists routinely accomplish small-scale geospatial modeling using raster datasets of global extent. Such use often requires the projection of global raster datasets onto a map or the reprojection from a given map projection associated with a dataset. The distortion characteristics of these projection transformations can have significant effects on modeling results. Distortions associated with the reprojection of global data are generally greater than distortions associated with reprojections of larger-scale, localized areas. The accuracy of areas in projected raster datasets of global extent is dependent on spatial resolution. To address these problems of projection and the associated resampling that accompanies it, methods for framing the transformation space, direct point-to-point transformations rather than gridded transformation spaces, a solution to the wrap-around problem, and an approach to alternative resampling methods are presented. The implementations of these methods are provided in an open-source software package called MapImage (or mapIMG , for short), which is designed to function on a variety of computer architectures.

Cartographic Perspectives↗
USGS2023

A guide to creating an effective big data management framework

Many agencies and organizations, such as the U.S. Geological Survey, handle massive geospatial datasets and their auxiliary data and are thus faced with challenges in storing data and ingesting it, transferring it between internal programs, and egressing it to external entities. As a result, these agencies and organizations may inadvertently devote unnecessary time and money to convey data without existing or outdated standards. This research aims to evaluate the components of data conveyance systems, such as transfer methods, tracking, and automation, to guide their improved performance. Specifically, organizations face the challenges of slow dispatch time and manual intervention when conveying data into, within, and from their systems. Conveyance often requires skilled workers when the system depends on physical media such as hard drives, particularly when terabyte transfers are required. In addition, incomplete or inconsistent metadata may necessitate manual intervention, process changes, or both. A proposed solution is organization-wide guidance for efficient data conveyance. That guidance involves systems analysis to outline a data management framework, which may include understanding the minimum requirements of data manifests, specification of transport mechanisms, and improving automation capabilities.

Journal of Big Data↗
USGS2018

A comparison of synthetic flowpaths derived from light detection and ranging topobathymetric data and National Hydrography Dataset High Resolution Flowlines

Bathymetric and topobathymetric light detection and ranging (lidar) digital elevation models created for the Delaware River were provided to the National Geospatial Program and used to evaluate synthetic flowpath extraction from bathymetric/topobathymetric lidar survey data as a data source for improving the density, distribution, and connectivity of the National Hydrography Dataset High Resolution Flowline Network. As the surface-water component of The National Map, the National Hydrography Dataset maintains the Nation’s drainage network flow information and geometries for surface-water features used in hydrologic, hydraulic, and other science and engineering disciplines. The regional lidar survey for the Delaware River between Hancock, New York, and Trenton, New Jersey, was collected for the U.S. Geological Survey using the Experimental Advanced Airborne Research Lidar sensor system and processed by the Coastal National Elevation Database Applications Program. Using 1 percent of the maximum flow accumulation value for the surveyed Delaware River corridor as the flow accumulation threshold for grid cells at 1-, 5-, and 10-meter resolution created 223 to 283 kilometers of synthetic flowpaths potentially representing the river channel thalweg, which is the deepest point in a riverbed cross-section. There was potential for improving the High Resolution National Hydrography Dataset (HR NHD) Flowline network in places where the Delaware River channel, depicted as an Artificial Path in the HR NHD, is offset from the extracted synthetic river flowpath which sometimes appeared better positioned than the Artificial Path to represent the river thalweg. For the same area, using 0.05 percent of the maximum flow accumulation at the 1-, 5-, and 10-meter resolutions extracted 744 to 1,317 kilometers of synthetic flowpaths, with extracted synthetic flowpaths representing the main river channel and additional synthetic flowpaths representing tributaries or streams adjacent to the main channel. Overlaying these results with the HR NHDFlowline Network indicates that some of the additional synthetic flowpaths are connected to or extend HR NHD stream/river feature types. Some disconnected or isolated synthetic flowpaths not included in stream/river feature types were validated in orthoimagery and U.S. Topo Maps and provide examples of how extracted synthetic flowpaths could be used to delineate new stream/river features. Other additional extracted synthetic flowpaths depict linear features such as canals, tree lines, roads, or linear topographic depressions. For some river reaches where obstructions to flow or where low-relief topographic or bathymetric surfaces alter the flow direction, the software tool used to develop the flow direction grid did not calculate a primary flowpath for the river channel. Based on the results of this analysis, site conditions for the Delaware River corridor did not affect the quality of lidar bathymetric survey data. However, depending on the resolution of the lidar bathymetric digital elevation models (BDEMs), site conditions do have different effects on results for extracted synthetic flowpaths. We found that synthetic flowpaths extracted from 1-meter resolution lidar DEMs had more varied flow directions around in-channel landforms that obstructed flow than synthetic flowpaths extracted from 5- or 10-meter resolution lidar DEMs. As a result the 1-meter resolution DEM created some isolated or discontinuous synthetic flowpath segments where the 5- and 10-meter DEMs developed more continuous flowpaths. In this case the river bed upstream from the in-channel obstruction is shallower than the river bed downstream. Under these conditions the 1-meter resolution DEM provided synthetic flowpaths delineating a potential river thalweg. In this same area, the software solution modified (virtually raised) the river bed in the 5- and 10-meter resolution DEMs and flattened the bathymetric surface to create a continuous downstream flow direction, which caused trellis-patterned synthetic flowpaths to form. Under different site conditions and converse to the above development of synthetic flowpaths at different resolutions, at an abandoned river flood plain (terrace) with low relief that is adjacent to the river channel, the flow direction grid for the 1-meter resolution DEM developed continuous synthetic flowpath corresponding to a HR NHD Flowline network stream/river feature that connected to the main river channel but the larger resolution DEMs created isolated or disconnected synthetic flowpaths. A project to continue an evaluation of benefits of or issues caused by extracting synthetic flowpaths to enhance the HR NHD could include a study to assess the potential for merging surface-water flowpaths extracted from lidar topobathymetry and 3D Elevation Program digital elevation models. The merged DEM approach to synthetic flowpath extraction could extend the HR NHDFlowline network and enhance flow accumulations that might develop better flow direction grids in low-relief areas. Because of the confined lateral extent of the Delaware River, the lidar DEMs were not used to create catchments or watersheds; however, the merged DEM approach could also be tested as a resource for enhancing HR NHD catchments and watersheds. This lidar DEM synthetic flowpath extraction project supports the National Geospatial Program efforts to collect and produce high-quality lidar data to provide 3-dimensional representations of natural feature and aligns with the National Spatial Data Infrastructure to improve utilization of geospatial data. The results also can be useful for understanding strategies that can help maintain quality data in the HR NHD programs. KEYWORDS: bathymetric, digital elevation model, extracted synthetic flowpath, lidar, High Resolution National Hydrography Dataset, topobathymetric

New Jersey↗
USGS2009

NBII-SAIN Data Management Toolkit

The Strategic Plan for the U.S. Geological Survey Biological Informatics Program (2005-2009) recognizes the need for effective data management: Though the Federal government invests more than $600 million per year in biological data collection, it is difficult to address these issues because of limited accessibility and lack of standards for data and information...variable quality, sources, methods, and formats (for example observations in the field, museum specimens, and satellite images) present additional challenges. This is further complicated by the fast-moving target of emerging and changing technologies such as GPS and GIS. Even though these technologies offer new solutions, they also create new informatics challenges (Ruggiero and others, 2005). The USGS National Biological Information Infrastructure program, hereafter referred to as NBII, is charged with the mission to improve the way data and information are gathered, documented, stored, and accessed. The central objective of this project is a direct reflection of the purpose of NBII as described by John Mosesso, Program Manager of the U.S. Geological Survey-Biological Informatics Program-GAP Analysis: At the outset, the reason for bringing about NBII was that there were significant amounts of data and information scattered all over the U.S., not accessible, in incompatible formats, and that NBII was tasked with addressing this problem...NBII's focus is to pull data together that truly matters to someone or communities. Essentially, the core questions are: 1) what are the issues, 2) where is the data, and 3) how can we make it usable and accessible (John Mosesso, U.S. Geological Survey, oral commun., 2006). Redundancy in data collection can be a major issue when multiple stakeholders are involved with a common effort. In 2001 the U.S. General Accounting Office (USGAO) estimated that about 50 percent of the Federal government's geospatial data at the time was redundant. In addition, approximately 80 percent of the cost of a spatial information system is associated with spatial data collection and management (U.S. General Accounting Office, 2003). These figures indicate that the resources (time, personnel, money) of many agencies and organizations could be used more efficiently and effectively. Dedicated and conscientious data management coordination and documentation is critical for reducing such redundancy. Substantial cost savings and increased efficiency are direct results of a pro-active data management approach. In addition, details of projects as well as data and information are frequently lost as a result of real-world occurrences such as the passing of time, job turnover, and equipment changes and failure. A standardized, well documented database allows resource managers to identify issues, analyze options, and ultimately make better decisions in the context of adaptive management (National Land and Water Resources Audit and the Australia New Zealand Land Information Council on behalf of the Australian National Government, 2003). Many environmentally focused, scientific, or natural resource management organizations collect and create both spatial and non-spatial data in some form. Data management appropriate for those data will be contingent upon the project goal(s) and objectives and thus will vary on a case-by-case basis. This project and the resulting Data Management Toolkit, hereafter referred to as the Toolkit, is therefore not intended to be comprehensive in terms of addressing all of the data management needs of all projects that contain biological, geospatial, and other types of data. The Toolkit emphasizes the idea of connecting a project's data and the related management needs to the defined project goals and objectives from the outset. In that context, the Toolkit presents and describes the fundamental components of sound data and information management that are common to projects involving biological, geospatial, and other related data

Open-File Report↗
USGS2024

NASA Champions 2024: Data strategies for when to use cloud, coding strategies for parallelization, & first examples of big science in the Cloud

From April-May 2024, the NASA Mentors who span eleven Distributed Active Archive Centers (DAACs) co-led the third Champions Cohort with the NASA Openscapes project team, this year focusing on, teaching lessons they adapted for geospatial and cloud analysis. The Cohort included nine international research teams from academia and government that were curious about working with NASA Earthdata in the Cloud. Many teams were interested in using data from multiple DAACs. User cloud adaption takes time, given the new conceptual mindsets and technical skillsets it requires. During the ten weeks we worked together, NASA Mentors refined and extended previous lessons to focus on thinking through and planning the transition to using the Cloud for science research and applications, and initial experiments using the Cloud through our 2i2c JupyterHub. Below are these updates and YouTube clips! There were also recurring themes/questions that we have heard before, some of which remain as open questions and continue to remain a challenge. Importantly, Amazon Web Services (AWS) Cloud onboarding, when to use what resources, how to set them up, and how to discuss needs with organizational leadership and IT staff, which often falls outside the scope of NASA DAACs, yet it’s a key element of helping users adopt the Cloud and use NASA data in the Cloud. It is encouraging to hear some of the champions starting to have conversations with their institutions, IT departments, and making their needs known, which is likely a big part of the solution, too. We are thankful to NASA Openscapes Champions for informing and nudging these conversations! All of this work is underpinned by Openscapes and NASA’s commitment to open science practices and a kinder collaborative culture. This cohort is funded by NASA and is part of our NASA Openscapes Framework project.

Report↗
USGS2020

Statewide assessment of karst aquifers in New York with an inventory of closed-depression and focused-recharge features

Karst is a landscape formed from the dissolution of soluble rock or rock containing minerals that are easily dissolved from within the rock. The landscape is characterized by sinkholes, caves, losing streams, springs, and underground drainage systems, which rapidly move water through the karst. The two forms of karst in New York State include carbonate karst, which forms in carbonate rock (limestone, marble, and dolostone), and evaporite karst, which forms in rock that contains the evaporite minerals gypsum and halite. Past and recent studies of karst across the State have shown that areas of focused recharge in karstic carbonate rock allow contaminants to enter aquifer systems with little attenuation. Focused areas of recharge need to be identified to help prevent such contamination from sources on or adjacent to the karst. The New York State Departments of Environmental Conservation and Health are collaborating with the agricultural community to make farmers and farm-planning advisors more aware of karst and how to manage daily farming activities to reduce their impact on surface water and groundwater resources, especially in karst areas. There is also a need to make regulators, planners, and the general public aware of New York’s karst resources and to properly protect and manage these resources to protect the quality of groundwater and surface water that can flow into, through, and from karst bedrock. Using publicly available geospatial data, karst bedrock and closed depressions over or near karst rock were identified across New York. Carbonate, evaporite, and marble geologic units were selected from a statewide 1:250,000-scale bedrock geology dataset. The selected geologic units were intersected with 7.5-minute quadrangle maps to define the study area. The U.S. Geological Survey has compiled an inventory of closed depressions from statewide digital contour data, scanned 7.5-minute topographic maps known as a digital raster graphics, and light detection and ranging (lidar) digital elevation models. Analysis of the data resulted in the identification of 5,023 closed depressions statewide. The inventory was conducted to eliminate duplication of results from analysis of the three data sources. A series of overlay analyses was conducted using the closed depressions and thematic data known to be key factors in determining the probability of a closed depression contributing to focused groundwater recharge; the thematic data include bedrock geology, soil type, soil infiltration rate, and land cover. Though the extent of karst development is important in understanding the interaction between surface water and groundwater in karst terrains, some of the worst cases of groundwater contamination in karst can occur where only minor karst features might be present. The presence of karst—be it a short section of a solutioned fracture or an extensive cave system—requires careful consideration, forward-looking environmental planning, and consistent water-quality protection to preserve New York State’s water resources.

New York↗
USGS2016

Post-disaster supply chain interdependent critical infrastructure system restoration: A review of data necessary and available for modeling

The majority of restoration strategies in the wake of large-scale disasters have focused on short-term emergency response solutions. Few consider medium- to long-term restoration strategies to reconnect urban areas to national supply chain interdependent critical infrastructure systems (SCICI). These SCICI promote the effective flow of goods, services, and information vital to the economic vitality of an urban environment. To re-establish the connectivity that has been broken during a disaster between the different SCICI, relationships between these systems must be identified, formulated, and added to a common framework to form a system-level restoration plan. To accomplish this goal, a considerable collection of SCICI data is necessary. The aim of this paper is to review what data are required for model construction, the accessibility of these data, and their integration with each other. While a review of publicly available data reveals a dearth of real-time data to assist modeling long-term recovery following an extreme event, a significant amount of static data does exist and these data can be used to model the complex interdependencies needed. For the sake of illustration, a particular SCICI (transportation) is used to highlight the challenges of determining the interdependencies and creating models capable of describing the complexity of an urban environment with the data publicly available. Integration of such data as is derived from public domain sources is readily achieved in a geospatial environment, after all geospatial infrastructure data are the most abundant data source and while significant quantities of data can be acquired through public sources, a significant effort is still required to gather, develop, and integrate these data from multiple sources to build a complete model. Therefore, while continued availability of high quality, public information is essential for modeling efforts in academic as well as government communities, a more streamlined approach to a real-time acquisition and integration of these data is essential.

Data Science Journal↗
USGS2022

Implementing landscape connectivity with topographic filtering model: A simulation of suspended sediment delivery in an agricultural watershed

The widespread availability of high-fidelity topography combined with advances in geospatial analysis offer the opportunity to reimagine approaches to the difficult problem of predicting sediment delivery from watersheds. Here we present a model that uses high-resolution topography to filter sediment sources to quantify sediment delivery to the watershed outlet. It is a reduced-complexity, top-down model that defines transfer functions—topographic filters—between spatially distributed sediment sources and spatially integrated sediment delivery. The goal of the model is to forecast changes in watershed suspended sediment delivery in response to spatially distributed changes in sediment source magnitude or delivery, whether a result of watershed drivers or intentional management actions. Such an application requires the context of a watershed model that accounts for all sediment sources, enforces sediment mass balance throughout the spatial domain, and accommodates sediment storage and delivery over time. The model is developed for a HUC-8 watershed with a flat upland dominated by corn-soybean agriculture and deeply incised valleys near the watershed outlet with large sediment contributions from near-channel sources. Topofilter computes delivery and storage of field-derived sediment according to its spatial and structural connectivity to the stream channel network; subsequently, delivery of both field- and near-channel-derived sediment along with floodplain storage are computed in the stream channel network to the watershed outlet. The model outputs provide a spatially rich representation of sediment delivery and storage on field and along the stream that is consistent with available independent information on sediment accumulations and fluxes. Rather than a single best-calibrated solution, Topofilter uses the Generalized Likelihood Uncertainty Estimate (GLUE) approach to develop many possible solutions with sediment delivery rates expressed as probability distributions across the watershed. The ensemble of simulation outputs provides a useful basis for estimating uncertainty in sediment delivery and the effectiveness of different landscape management allocation across a watershed.

Minnesota↗
USGS2019

Demonstrating the value of Earth observations—methods, practical applications, and solutions—group on Earth observations side event proceedings

Executive Summary The U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the European Association for Remote Sensing Companies, and the European Space Agency in coordination with the GEOValue Community hosted a side event to the Group on Earth Observations Plenary on October 23–24, 2017, in Washington, D.C. The workshop, entitled “Demonstrating the Value of Earth Observations: Methods, Practical Applications and Solutions,” brought together more than 60 international experts including economists, scientists, and engineers to consider the state of the science and applications of valuing Earth observations (EO). This 2-day workshop built upon previous activities developed under the GEOValue initiative. This workshop brought together expert analysts from multiple disciplines and backgrounds who are developing methods to identify and measure the value of information generated from the use of satellite and in-situ data. The mix of government agencies, international financial institutions, and independent consultants who participated in the workshop blended to develop a rich mix of views, approaches, and outcomes. During the first part of the workshop, the focus was on the latest science in valuing EO. A number of methodologies were described. Approaches generally assess the societal benefits of specific actions (for example, investments in EO). Some methods focus on broad measures of economic activity (for example, gross domestic product) or methods to assess total economic value such as contingent valuation surveys. Alternatively, use-case approaches (a use case is defined as an evaluation in which one or more decisions, applications, or other uses of data, information, and information products are specifically considered) start with the specific actions and how information is used to support decision making and affect outcomes. The second part of the meeting was focused on the use and development of value chains and decision trees. A value chain can be defined as the set of value-adding activities that one or more organizations perform in creating and distributing goods and services. In terms of EO, the value chain approach can be applied to consider societal benefits of the data and assess the value of data and data features. The EO value chain considers the geospatial data sources and the processing of the data into value added information to be incorporated into decision-support systems, leading to decision makers’ actions. To understand the value of EO, one would also need to recognize the demand side of the equation or how EO benefits users. Extending the value chain concept and incorporating tenets of Bayesian decision making, a decision tree would include one or more use cases. The value provided by the marginal increase in information could flow from one or several parts of the supply side of the value chain. The decision tree is based on the premise that information has no value if it is not used in at least one decision. By connecting the value chain and the decision tree, a framework is created that allows for conceptualizing the value of EO in its many uses. One can then apply economic techniques to monetize the marginal benefit of an outcome with information versus one without. A third part of the meeting applied the value chain and decision-tree frameworks to five specific thematic areas, each with the focus of using information for a decision point: Effect of increasing temperatures on human health; Flooding—Mitigating, managing, and avoiding impacts to safety and property damage; Harmful algal blooms—Effects on human health, recreation, and tourism; Energy and mineral supply—Mitigating, managing, and avoiding impacts of shortfalls on the economy; and Effects of natural hazards on transportation systems—Effects on mobility, safety, and the economy. During the working session, five separate groups worked to define and delineate the value chains and decision trees associated with each topic, discussing the related challenges and data needs. The outcomes were reported back to the full group. Because of the complexity of the topics, most groups first identified a network of value chains and then narrowed the scope to develop a single value chain to address their group’s topic. Although they worked separately and on different topics, the groups came to similar conclusions, concurring that the value chain and decision-tree frameworks are very effective for informing quantitative impact assessments and developing a relatable narrative to assist the public in understanding the link between EO and citizens.

Open-File Report↗