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At least 19 recordsLinked to original sources
USGS2025

GIScience in the era of Artificial Intelligence: A research agenda towards Autonomous GIS

The advent of generative AI exemplified by large language models (LLMs) opens new ways to represent and compute geographic information and transcends the process of geographic knowledge production, driving geographic information systems (GIS) towards autonomous GIS. Leveraging LLMs as the decision core, autonomous GIS can independently generate and execute geoprocessing workflows to perform spatial analysis. In this vision paper, we further elaborate on the concept of autonomous GIS and present a conceptual framework that defines its five autonomous goals, five levels of autonomy, five core functions, and three operational scales. We demonstrate how autonomous GIS could perform geospatial data retrieval, spatial analysis, and map making with four proof-of-concept GIS agents. We conclude by identifying critical challenges and future research directions, including fine-tuning and self-growing decision-cores, autonomous modelling, and examining the societal and practical implications of autonomous GIS. By establishing the groundwork for a paradigm shift in GIScience, this paper envisions a future where GIS moves beyond traditional workflows to autonomously reason, derive, innovate, and advance geospatial solutions to pressing global challenges. Meanwhile, we emphasize that as we design and deploy increasingly intelligent geospatial systems, we carry a responsibility to ensure they are developed in socially responsible ways, serve the public good, and support the continued value of human geographic insight in an AI-augmented future.

Annals of GIS↗
USGS2004

The National Map: Benefits at what cost?

The U.S. Geological Survey has conducted a cost-benefit analysis of The National Map, and determined that, during its 30-year projected lifespan, the project will likely bring a net present value of benefits to society of $2.05 billion. Such a survey enhances the United States' ability to access, integrate, and apply geospatial data at global, national, and local scales. This paper gives an overview on the underlying economic model for evaluating program benefits and presents the primary findings as well as a sensitivity analysis assessing the robustness of the results.

GeoSpatial Solutions↗
USGS2004

Titanic exploration with GIS

To help teachers and students investigate one of the world's most famous historical events using the geographic perspective and GIS tools and methods, the U.S. Geological Survey (USGS) created a set of educational lessons based on the RMS Titanic's April 1912 sailing. With these lessons, student researchers can learn about latitude and longitude, map projections, ocean currents, databases, maps, and images through the analysis of the route, warnings, sinking, rescue, and eventual discovery of the submerged ocean liner in 1985. They can also consider the human and physical aspects of the maiden voyage in the North Atlantic Ocean at a variety of scales, from global to regional to local. Likewise, their investigations can reveal how the sinking of the Titanic affected future shipping routes.

GeoSpatial Solutions↗
USGS2010

The National Map: New viewer, services, and data download

Managed by the U.S. Geological Survey's (USGS) National Geospatial Program, The National Map has transitioned data assets and viewer applications to a new visualization and product and service delivery environment, which includes an improved viewing platform, base map data and overlay services, and an integrated data download service. This new viewing solution expands upon the National Geospatial Intelligence Agency (NGA) Palanterra X3 viewer, providing a solid technology foundation for navigation and basic Web mapping functionality. Building upon the NGA viewer allows The National Map to focus on improving data services, functions, and data download capabilities. Initially released to the public at the 125th anniversary of mapping in the USGS on December 3, 2009, the viewer and services are now the primary distribution point for The National Map data. The National Map Viewer: http://viewer.nationalmap.gov

Fact Sheet↗
USGS1997

Geospatial Technology Strategic Plan 1997-2000

Executive Summary -- Geospatial technology applications have been identified in many U.S. Geological Survey Biological Resources Division (BRD) proposals for grants awarded through internal and partnership programs. Because geospatial data and tools have become more sophisticated, accessible, and easy to use, BRD scientists frequently are using these tools and capabilities to enhance a broad spectrum of research activities. Bruce Babbitt, Secretary of the Interior, has acknowledged--and lauded--the important role of geospatial technology in natural resources management. In his keynote address to more than 5,500 people representing 87 countries at the Environmental Systems Research Institute Annual Conference (May 21, 1996), Secretary Babbitt stated, '. . .GIS [geographic information systems], if properly used, can provide a lot more than sets of data. Used effectively, it can help stakeholders to bring consensus out of conflict. And it can, by providing information, empower the participants to find new solutions to their problems.' This Geospatial Technology Strategic Plan addresses the use and application of geographic information systems, remote sensing, satellite positioning systems, image processing, and telemetry; describes methods of meeting national plans relating to geospatial data development, management, and serving; and provides guidance for sharing expertise and information. Goals are identified along with guidelines that focus on data sharing, training, and technology transfer. To measure success, critical performance indicators are included. The ability of the BRD to use and apply geospatial technology across all disciplines will greatly depend upon its success in transferring the technology to field biologists and researchers. The Geospatial Technology Strategic Planning Development Team coordinated and produced this document in the spirit of this premise. Individual Center and Program managers have the responsibility to implement the Strategic Plan by working within the policy and guidelines stated herein.

Information and Technology Report↗
USGS2022

Global groundwater solute composition and concentrations

Informed analysis of policies related to food security, global climate change, wetland ecology, environmental nutrient flux, element cycling, groundwater weathering, continental denudation, human health, etc. depends to a large extent on quantitative estimates of solute mass fluxes into and out of all global element pools including the enigmatic global aquifer systems. Herein for the first time, we proffer the mean global solute concentration of all major and selected minor and trace solutes in the active groundwater that represents 99% of liquid fresh water on Earth. Concentrations in this significant element pool have yielded to a geospatial machine learning kNN-nearest neighbors’ algorithm with numerous geospatial predictors utilizing a large new lithology/climate/aquifer age/elevation based solute database. The predicted concentrations are consistent with traditional solute ratios, concentrations, and thermodynamic saturation indices.

Groundwater↗
USGS2017

International Watershed Technology: Improving Water Quality and Quantity at the Local, Basin, and Regional Scales

This article introduces the five papers in the “International Watershed Technology” collection. These papers were selected from 60 technical presentations at the fifth biennial ASABE 21st Century Watershed Technology Conference and Workshop: Improving the Quality of Water Resources at Local, Basin, and Regional Scales, held in Quito, Ecuador, on 3-9 December 2016. The conference focused on solving spatial and temporal water quality and quantity problems and addressed topics such as watershed management in developing countries, aquatic ecology and ecohydrology, ecosystem services, climate change mitigation strategies, flood forecasting, remote sensing, and water resource policy and management. While diverse, the presentation topics reflected the continuing evolution of the “data mining” and “big data” themes of past conferences related to geospatial data applications, with increasing emphasis on practical solutions. The papers selected for this collection represent applications of spatial data analyses toward practical ends with a theme of “tools and techniques for sustainability.” The papers address a range of topics, including the matching of crops with water availability, and assessing the environmental impacts of agricultural production. The papers identify some of the latest tools and techniques for improving sustainability in watershed resource management that are relevant to both developing and developed countries.

Transactions of the ASABE↗
USGS2016

TopoLens: Building a cyberGIS community data service for enhancing the usability of high-resolution National Topographic datasets

Geospatial data, often embedded with geographic references, are important to many application and science domains, and represent a major type of big data. The increased volume and diversity of geospatial data have caused serious usability issues for researchers in various scientific domains, which call for innovative cyberGIS solutions. To address these issues, this paper describes a cyberGIS community data service framework to facilitate geospatial big data access, processing, and sharing based on a hybrid supercomputer architecture. Through the collaboration between the CyberGIS Center at the University of Illinois at Urbana-Champaign (UIUC) and the U.S. Geological Survey (USGS), a community data service for accessing, customizing, and sharing digital elevation model (DEM) and its derived datasets from the 10-meter national elevation dataset, namely TopoLens, is created to demonstrate the workflow integration of geospatial big data sources, computation, analysis needed for customizing the original dataset for end user needs, and a friendly online user environment. TopoLens provides online access to precomputed and on-demand computed high-resolution elevation data by exploiting the ROGER supercomputer. The usability of this prototype service has been acknowledged in community evaluation.

Conference Paper↗
USGS2009

Providing public standardized data access function: Lessons learned from accessing USGS Landsat archive

The geospatial community is experiencing a shift from having data locally to sharing them over the Web. However, not all the data accessing systems are built in compliance with open geospatial standards and thus are weak in terms of interoperability. The USGS Landsat data are now available through free electronic access though not yet through standard Web service interfaces. This paper intends to discuss the experience and lessons learned from integrating a public data access function to the USGS Landsat data archive into a geospatial workflow environment. Currently available systems and their problems, proposed solutions and application scenarios are discussed.

Conference Paper↗
USGS2025

Evaluating Three-Dimensional Elevation Program lidar consistency and accuracy at scale using cloud-native, open-source methods

The U.S. Geological Survey three-dimensional elevation program (3DEP) has significantly expanded national lidar coverage, necessitating scalable, reproducible methods for assessing data quality across diverse terrains and acquisition conditions. This study introduces a cloud-native, open-source workflow designed to evaluate the geometric accuracy and consistency of 3DEP lidar data sets at a national scale. Leveraging tools such as the Point Data Abstraction Library, Open3D, and Amazon Web Services infrastructure, the workflow integrates global navigation satellite system‐surveyed ground control points and terrestrial laser scanning data to validate airborne lidar collections. Two case studies demonstrate the application of this process. In Puerto Rico, the process identified vertical biases and inconsistencies in vegetated areas, while in Iowa and Arizona, the process confirmed high vertical accuracy with minimal bias. The results underscore the effectiveness of combining cloud computing with open-source tools to perform large-scale lidar data quality assessments. This process offers a reproducible, efficient solution for nationwide validation of 3DEP data sets, supporting enhanced decision-making in geospatial applications.

Photogrammetric Engineering and Remote Sensing↗
USGS2021

The 4th paradigm in multiscale data representation: Modernizing the National Geospatial Data Infrastructure

The need of citizens in any nation to access geospatial data in readily usable form is critical to societal well-being, and in the United States (US), demands for information by scientists, students, professionals and citizens continue to grow. Areas such as public health, urbanization, resource management, economic development and environmental management require a variety of data collected from many sources to identify problems, monitor trends and propose solutions. Such information needs and demands have driven the coordination of federal and regional government agencies with respective private sector participation to develop national geospatial data infrastructures in many countries.

Book chapter↗
USGS2004

Distributed Processing of Projections of Large Datasets: A Preliminary Study

Modern information needs have resulted in very large amounts of data being used in geographic information systems. Problems arise when trying to project these data in a reasonable amount of time and accuracy, however. Current single-threaded methods can suffer from two problems: fast projection with poor accuracy, or accurate projection with long processing time. A possible solution may be to combine accurate interpolation methods and distributed processing algorithms to quickly and accurately convert digital geospatial data between coordinate systems. Modern technology has made it possible to construct systems, such as Beowulf clusters, for a low cost and provide access to supercomputer-class technology. Combining these techniques may result in the ability to use large amounts of geographic data in time-critical situations.

Open-File Report↗
USGS1997

A Graphical-User Interface for the U. S. Geological Survey's SUTRA Code using Argus ONE (for simulation of variable-density saturated-unsaturated ground-water flow with solute or energy transport)

This report describes a Graphical-User Interface (GUI) for SUTRA, the U.S. Geological Survey (USGS) model for saturated-unsaturated variable-fluid-density ground-water flow with solute or energy transport,which combines a USGS-developed code that interfaces SUTRA with Argus ONE, a commercial software product developed by Argus Interware. This product, known as Argus Open Numerical Environments (Argus ONE TM ), is a programmable system with geographic-information-system-like (GIS-like) functionality that includes automated gridding and meshing capabilities for linking geospatial information with finite-difference and finite-element numerical model discretizations. The GUI for SUTRA is based on a public-domain Plug-In Extension (PIE) to Argus ONE that automates the use of ArgusONE to: automatically create the appropriate geospatial information coverages (information layers) for SUTRA, provide menus and dialogs for inputting geospatial information and simulation control parameters for SUTRA, and allow visualization of SUTRA simulation results. Following simulation control data and geospatial data input bythe user through the GUI, ArgusONE creates text files in a format required for normal input to SUTRA,and SUTRA can be executed within the Argus ONE environment. Then, hydraulic head, pressure, solute concentration, temperature, saturation and velocity results from the SUTRA simulation may be visualized. Although the GUI for SUTRA discussed in this report provides all of the graphical pre- and post-processor functions required for running SUTRA, it is also possible for advanced users to apply programmable features within Argus ONE to modify the GUI to meet the unique demands of particular ground-water modeling projects.

Open-File Report↗
USGS2016

POLARIS: A 30-meter probabilistic soil series map of the contiguous United States

A new complete map of soil series probabilities has been produced for the contiguous United States at a 30 m spatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~ 2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS' accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security.

Geoderma↗
USGS2018

Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor

Biologists and environmental scientists now routinely solve computational problems that were unimaginable a generation ago. Examples include processing geospatial data, analyzing -omics data, and running large-scale simulations. Conventional desktop computing cannot handle these tasks when they are large, and high-performance computing is not always available nor the most appropriate solution for all computationally intense problems. High-throughput computing (HTC) is one method for handling computationally intense research. In contrast to high-performance computing, which uses a single "supercomputer," HTC can distribute tasks over many computers (e.g., idle desktop computers, dedicated servers, or cloud-based resources). HTC facilities exist at many academic and government institutes and are relatively easy to create from commodity hardware. Additionally, consortia such as Open Science Grid facilitate HTC, and commercial entities sell cloud-based solutions for researchers who lack HTC at their institution. We provide an introduction to HTC for biologists and environmental scientists. Our examples from biology and the environmental sciences use HTCondor, an open source HTC system.

PLOS Computational Biology↗
USGS2022

U.S. Geological Survey Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)—Information Management Technology Plan

Introduction More than 840 publications, 575 data releases, and 330 project web pages from the U.S. Geological Survey (USGS) pertain to the Colorado River Basin. Limited interconnections between Colorado River Basin publications, data, and web pages restrict the ability to synthesize and interpret scientific resources. Currently, these pieces are spread across multiple isolated locations, internal systems, data repositories, and local offices. The increasing size, complexity, and diversity of Colorado River Basin data creates additional need for integration. These different data types—including discrete, continuous, aerial, remote sensing, geophysical, geospatial, and other types in varied formats—are collected over numerous time and space scales and require data-intensive science and technology to integrate. Information management technology (IMT) resources are enterprise capabilities that the USGS workforce can leverage at multiple scales with consistent interoperable solutions to better facilitate integrated science. The USGS 21st Century Science Strategy directs the USGS to establish enterprise IMT capabilities that support integrated work through interoperable software and database solutions at multiple scales. This Information Management Technology Plan identifies nine steps to leverage new and existing technologies, data, models, and scientific knowledge to support integrated science projects conducted across the Colorado River Basin. These steps are transferable to integrated-science studies in other locations.

Arizona, Colorado, Nevada, New Mexico, Utah, Wyomi↗
USGS2013

LANDFIRE 2010 - updated data to support wildfire and ecological management

Wildfire is a global phenomenon that affects human populations and ecosystems. Wildfire effects occur at local to global scales impacting many people in different ways (Figure 1). Ecological concerns due to land use, fragmentation, and climate change impact natural resource use, allocation, and conservation. Access to consistent and current environmental data is a constant challenge, yet necessary for understanding the complexities of wildfire and ecological management. Data products and tools from the LANDFIRE Program help decision-makers to clarify problems and identify possible solutions when managing fires and natural resources. LANDFIRE supports the reduction of risk from wildfire to human lives and property, monitoring of fire danger, prediction of fire behavior on active incidents, and assessment of fire severity and impacts on natural systems [1] [2] [3]. LANDFIRE products are unique in that they are nationally consistent and provide the only complete geospatial dataset describing vegetation and wildland fuel information for the entire U.S. As such, LANDFIRE data are useful for many ecological applications [3]. For example, LANDFIRE data were recently integrated into a decision-support system for resource management and conservation decision-making along the Appalachian Trail. LANDFIRE is a joint effort between the U.S. Department of the Interior Office of Wildland Fire, U.S. Department of Agriculture Forest Service Fire & Aviation Management, and The Nature Conservancy. To date, seven versions of LANDFIRE data have been released, with each successive version improving the quality of the data, adding additional features, and/or updating the time period represented by the data. The latest version, LANDFIRE 2010 (LF 2010), released mid-2013, represents circa 2010 landscape conditions and succeeds LANDFIRE 2008 (LF 2008), which represented circa 2008 landscape conditions. LF 2010 used many of the same processes developed for the LF 2008 effort [3]. Ongoing refinement of the LANDFIRE vegetation and fuel data is necessary to improve the quality and usability of the data and to capture landscape disturbance. LANDFIRE relies on Landsat multi-spectral imagery to produce and update vegetation and fuel data. The deep Landsat archive provides data needed for vegetation classification, change analysis, and historical disturbance characterization, for which LANDFIRE has used more than 24,000 image scenes since the program’s inception. In addition, LF 2010 used airborne and spaceborne lidar, and spaceborne synthetic aperture radar (SAR) to map vegetation structure in areas where ground-based field information was lacking, including Alaska and U.S.-affiliated islands in the Caribbean and the Pacific. The mapping of insular areas is new for the 2010 data release; previous versions of LANDFIRE were limited to the conterminous U.S., Alaska, and Hawaii.

Earthzine↗
USGS1999

Upgrade to MODFLOW-GUI; addition of MODPATH, ZONEBDGT, and additional MODFLOW packages to the U.S. Geological Survey MODFLOW-96 Graphical-User Interface

This report describes enhancements to a Graphical-User Interface (GUI) for MODFLOW-96, the U.S. Geological Survey (USGS) modular, three-dimensional, finitedifference ground-water flow model, and MOC3D, the USGS three-dimensional, method-ofcharacteristics solute-transport model. The GUI is a plug-in extension (PIE) for the commercial program Argus ONEe. The GUI has been modified to support MODPATH (a particle tracking post-processing package for MODFLOW), ZONEBDGT (a computer program for calculating subregional water budgets), and the Stream, Horizontal-Flow Barrier, and Flow and Head Boundary packages in MODFLOW. Context-sensitive help has been added to make the GUI easier to use and to understand. In large part, the help consists of quotations from the relevant sections of this report and its predecessors. The revised interface includes automatic creation of geospatial information layers required for the added programs and packages, and menus and dialog boxes for input of parameters for simulation control. The GUI creates formatted ASCII files that can be read by MODFLOW-96, MOC3D, MODPATH, and ZONEBDGT. All four programs can be executed within the Argus ONEe application (Argus Interware, Inc., 1997). Spatial results of MODFLOW-96, MOC3D, and MODPATH can be visualized within Argus ONEe. Results from ZONEBDGT can be visualized in an independent program that can also be used to view budget data from MODFLOW, MOC3D, and SUTRA. Another independent program extracts hydrographs of head or drawdown at individual cells from formatted MODFLOW head and drawdown files. A web-based tutorial on the use of MODFLOW with Argus ONE has also been updated. The internal structure of the GUI has been modified to make it possible for advanced users to easily customize the GUI. Two additional, independent PIEs were developed to allow users to edit the positions of nodes and to facilitate exporting the grid geometry to external programs.

Open-File Report↗