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USGS2018

User’s guide for MapMark4GUI—A graphical user interface for the MapMark4 R package

MapMark4GUI is an R graphical user interface (GUI) developed by the U.S. Geological Survey to support user implementation of the MapMark4 R statistical software package. MapMark4 was developed by the U.S. Geological Survey to implement probability calculations for simulating undiscovered mineral resources in quantitative mineral resource assessments. The GUI provides an easy-to-use tool to input data, run simulations, and format output results for the MapMark4 package. The GUI is written and accessed in the R statistical programming language. This user’s guide includes instructions on installing and running MapMark4GUI and descriptions of the statistical output processes, output files, and test data files.

Techniques and Methods↗

USGS2025

Computing discharge using the entropy-based probability concept

This report describes the techniques and methods for computing the mean-channel velocity and discharge using the entropy-based probability concept (probability concept). The method is an alternative to or augments standard streamgaging methods adopted by the U.S. Geological Survey (USGS). Although sensor technology for measuring the mean velocity and discharge has advanced, standard streamgaging and computational methods have remained relatively unchanged since the USGS established its first streamgage at the Rio Grande at Embudo, New Mexico in 1889. Standard streamgaging methods rely on integrating velocities and depths measured at multiple verticals at a channel cross section (standard cross section) to compute a discharge. The probability concept computes discharge at a single vertical (y-axis) using the ratio of the mean-channel velocity (mean velocity) and maximum velocity, the measured maximum velocity, and the area as a function of stage at the standard cross section. Proper siting and operation and maintenance are required. If siting is conducted appropriately, the probability concept parameters and the y-axis stationing will be similar for different streamflow conditions. The timing of operation and maintenance visits should be based on hydrologic and meteorologic occurrences and seasonality and should capture low, medium, high, and opportunistic streamflow conditions. Advantages of the probability concept are the capacity to (1) compute discharge time series immediately after streamgage siting, (2) compute discharge for complex streamflow conditions that cannot be quantified by stage-discharge methods, (3) augment time-series data where gaps exist, and (4) integrate with surface velocity sensors such as Doppler velocity radars and cameras, which are not subject to damage caused by ice, debris, and flood flows. Potential sources of bias in discharge derived from the probability concept include (1) rain, (2) wind, and (3) geomorphologic and hydraulic instabilities. Recommendations to address these biases are provided. This report guides users through the steps to parameterize the probability concept, process field data, and compute the mean velocity and discharge using the probability concept.

Techniques and Methods↗

USGS2010

User's guide for MAGIC-Meteorologic and hydrologic genscn (generate scenarios) input converter

Meteorologic and hydrologic data used in watershed modeling studies are collected by various agencies and organizations, and stored in various formats. Data may be in a raw, un-processed format with little or no quality control, or may be checked for validity before being made available. Flood-simulation systems require data in near real-time so that adequate flood warnings can be made. Additionally, forecasted data are needed to operate flood-control structures to potentially mitigate flood damages. Because real-time data are of a provisional nature, missing data may need to be estimated for use in floodsimulation systems. The Meteorologic and Hydrologic GenScn (Generate Scenarios) Input Converter (MAGIC) can be used to convert data from selected formats into the Hydrologic Simulation System-Fortran hourly-observations format for input to a Watershed Data Management database, for use in hydrologic modeling studies. MAGIC also can reformat the data to the Full Equations model time-series format, for use in hydraulic modeling studies. Examples of the application of MAGIC for use in the flood-simulation system for Salt Creek in northeastern Illinois are presented in this report.

Open-File Report↗

USGS2014

Geospatial considerations for a multiorganizational, landscape-scale program

Geospatial data play an increasingly important role in natural resources management, conservation, and science-based projects. The management and effective use of spatial data becomes significantly more complex when the efforts involve a myriad of landscape-scale projects combined with a multiorganizational collaboration. There is sparse literature to guide users on this daunting subject; therefore, we present a framework of considerations for working with geospatial data that will provide direction to data stewards, scientists, collaborators, and managers for developing geospatial management plans. The concepts we present apply to a variety of geospatial programs or projects, which we describe as a “scalable framework” of processes for integrating geospatial efforts with management, science, and conservation initiatives. Our framework includes five tenets of geospatial data management: (1) the importance of investing in data management and standardization, (2) the scalability of content/efforts addressed in geospatial management plans, (3) the lifecycle of a geospatial effort, (4) a framework for the integration of geographic information systems (GIS) in a landscape-scale conservation or management program, and (5) the major geospatial considerations prior to data acquisition. We conclude with a discussion of future considerations and challenges.

Journal of Map & Geography Libraries↗

USGS2016

Aging and sexing guide to the forest birds of Hawai‘i Island

We banded birds in Hakalau Forest National Wildlife Refuge from 2012 to 2016, collecting photographs of birds and making detailed observations on coloration, morphology, and molting patterns. While we believe the criteria in this guide are applicable to forest birds across Hawai’i Island, as well as on other Hawaiian islands for ‘Apapane, ‘I‘iwi, and Hawai‘i ‘Amakihi, certain characteristics such as morphometrics may vary across populations, and users should verify the guide’s criteria with other available field data.

Technical Report↗

USGS2014

Summary and abstracts of the Planetary Data Workshop, June 2012

The recent boom in the volume of digital data returned by international planetary science missions continues to both delight and confound users of those data. In just the past decade, the Planetary Data System (PDS), NASA’s official archive of scientific results from U.S. planetary missions, has seen a nearly 50-fold increase in the amount of data and now serves nearly half a petabyte. In only a handful of years, this volume is expected to approach 1 petabyte (1,000 terabytes or 1 quadrillion bytes). Although data providers, archivists, users, and developers have done a creditable job of providing search functions, download capabilities, and analysis and visualization tools, the new wealth of data necessitates more frequent and extensive discussion among users and developers about their current capabilities and their needs for improved and new tools. A workshop to address these and other topics, “Planetary Data: A Workshop for Users and Planetary Software Developers,” was held June 25–29, 2012, at Northern Arizona University (NAU) in Flagstaff, Arizona. A goal of the workshop was to present a summary of currently available tools, along with hands-on training and how-to guides, for acquiring, processing and working with a variety of digital planetary data. The meeting emphasized presentations by data users and mission providers during days 1 and 2, and developers had the floor on days 4 and 5 using an “unconference” format for day 5. Day 3 featured keynote talks by Laurence Soderblom (U.S. Geological Survey, USGS) and Dan Crichton (Jet Propulsion Laboratory, JPL) followed by a panel discussion, and then research and technical discussions about tools and capabilities under recent or current development. Software and tool demonstrations were held in break-out sessions in parallel with the oral session. Nearly 150 data users and developers from across the globe attended, and 22 National Aeronautics and space Administration (NASA) and non-NASA data providers and missions were represented. Presentations (some in video format) and tutorials are posted on the meeting site ( http://astrogeology.usgs.gov/groups/Planetary-Data-Workshop ).

Open-File Report↗

USGS1977

GEOTHERM user guide

GEOTHERM is a computerized geothermal resources file developed by the U.S. Geological Survey. The file contains data on geothermal fields, wells, and chemical analyses from the United states and international sources. The General Information Processing System (GIPSY) in the IBM 370/155 computer is used to store and retrieve data. The GIPSY retrieval program contains simple commands which can be used to search the file, select a narrowly defined subset, sort the records, and output the data in a variety of forms. Eight commands are listed and explained so that the GEOTHERM file can be accessed directly by geologists. No programming experience is necessary to retrieve data from the file.

Open-File Report↗

USGS2004

NADM Conceptual Model 1.0 -- A Conceptual Model for Geologic Map Information

Executive Summary -- The NADM Data Model Design Team was established in 1999 by the North American Geologic Map Data Model Steering Committee (NADMSC) with the purpose of drafting a geologic map data model for consideration as a standard for developing interoperable geologic map-centered databases by state, provincial, and federal geological surveys. The model is designed to be a technology-neutral conceptual model that can form the basis for a web-based interchange format using evolving information technology (e.g., XML, RDF, OWL), and guide implementation of geoscience databases in a common conceptual framework. The intended purpose is to allow geologic information sharing between geologic map data providers and users, independent of local information system implementation. The model emphasizes geoscience concepts and relationships related to information presented on geologic maps. Design has been guided by an informal requirements analysis, documentation of existing databases, technology developments, and other standardization efforts in the geoscience and computer-science communities. A key aspect of the model is the notion that representation of the conceptual framework (ontology) that underlies geologic map data must be part of the model, because this framework changes with time and understanding, and varies between information providers. The top level of the model distinguishes geologic concepts, geologic representation concepts, and metadata. The geologic representation part of the model provides a framework for representing the ontology that underlies geologic map data through a controlled vocabulary, and for establishing the relationships between this vocabulary and a geologic map visualization or portrayal. Top-level geologic classes in the model are Earth material (substance), geologic unit (parts of the Earth), geologic age, geologic structure, fossil, geologic process, geologic relation, and geologic event.

Open-File Report↗

USGS2024

Think regionally, act locally: Perspectives on co-design of spatial conservation prioritization tools and why end-user engagement altered our approach

Coproduction represents an inclusive approach for developing decision-support resources because it seeks to integrate scientific knowledge and end-user needs. Unfortunately, spatial decision support systems (SDSS) coproduction has sometimes resulted in limited utility for end-users, partially due to scarce SDSS coproduction guidance. To initiate coproduction, we held a series of workshops to co-design a spatial conservation prioritization tool for sagebrush ecosystems in the western United States. We share four themes derived from participant feedback and our reflections to guide future SDSS codesign efforts. We found end-user confidence in data inputs and transparency regarding SDSS assumptions generated trust. Workshop participants noted our virtual format, with smaller break-out groups, effectively facilitated discussions. Ultimately, end-users appreciated the conservation context provided by regional-scale SDSS but preferred local-scale prioritization efforts for site-level planning. Therefore, we are shifting ongoing co-design efforts to consider local-scale tool development, which can scale up to larger geographic extents.

Conservation Science and Practice↗

USGS2022

Working toward a National Coordinated Soil Moisture Monitoring Network: Vision, progress, and future directions

Soil moisture is a critical land surface variable, impacting the water, energy, and carbon cycles. While in situ soil moisture monitoring networks are still developing, there is no cohesive strategy or framework to coordinate, integrate, or disseminate these diverse data sources in a synergistic way that can improve our ability to understand climate variability at the national, state, and local levels. Thus, a national strategy is needed to guide network deployment, sustainable network operation, data integration and dissemination, and user-focused product development. The National Coordinated Soil Moisture Monitoring Network (NCSMMN) is a federally led, multi-institution effort that aims to address these needs by capitalizing on existing wide-ranging soil moisture monitoring activities, increasing the utility of observational data, and supporting their strategic application to the full range of decision-making needs. The goals of the NCSMMN are to 1) establish a national “network of networks” that effectively demonstrates data integration and operational coordination of diverse in situ networks; 2) build a community of practice around soil moisture measurement, interpretation, and application—a “network of people” that links data providers, researchers, and the public; and 3) support research and development (R&D) on techniques to merge in situ soil moisture data with remotely sensed and modeled hydrologic data to create user-friendly soil moisture maps and associated tools. The overarching mission of the NCSMMN is to provide coordinated high-quality, nationwide soil moisture information for the public good by supporting applications like drought and flood monitoring, water resource management, agricultural and forestry planning, and fire danger ratings.

Bulletin of the American Meteorological Society↗

USGS2009

US Topo: Topographic Maps for the Nation

Fact Sheet↗

USGS2013

US Topo: topographic maps for the nation

US Topo is the next generation of topographic maps from the U.S. Geological Survey (USGS). Arranged in the familiar 7.5-minute quadrangle format, digital US Topo maps are designed to look and feel (and perform) like the traditional paper topographic maps for which the USGS is so well known. In contrast to paper-based maps, US Topo maps provide modern technical advantages that support faster, wider public distribution and enable basic, on-screen geographic analysis for all users. The US Topo quadrangle map has been redesigned so that map elements are visually distinguishable with the imagery turned on and off, while keeping the file size as small as possible. The US Topo map redesign includes improvements to various display factors, including symbol definitions (color, line thickness, line symbology, area fills), layer order, and annotation fonts. New features for 2013 include the following: a raster shaded relief layer, military boundaries, cemeteries and post offices, and a US Topo cartographic symbols legend as an attachment. US Topo quadrangle maps are available free on the Web. Each map quadrangle is constructed in GeoPDF® format using key layers of geographic data (orthoimagery, roads, geographic names, topographic contours, and hydrographic features) from The National Map databases. US Topo quadrangle maps can be printed from personal computers or plotters as complete, full-sized, maps or in customized sections, in a user-desired specific format. Paper copies of the maps can also be purchased from the USGS Store. Download links and a users guide are featured on the US Topo Web site. US Topo users can turn geographic data layers on and off as needed; they can zoom in and out to highlight specific features or see a broader area. File size for each digital 7.5-minute quadrangle, about 30 megabytes. Associated electronic tools for geographic analysis are available free for download. The US Topo provides the Nation with a topographic product that users can quickly incorporate into decisionmaking, operational or recreational activities.

Fact Sheet↗

USGS2017

Program MAMO: Models for avian management optimization-user guide

The following chapters describe the structure and code of MAMO, and walk the reader through running the different components of the program with sample data. This manual should be used alongside a computer running R, so that the reader can copy and paste code into R, observe the output, and follow along interactively. Taken together, chapters 2–4 will allow the user to replicate a simulation study investigating the consequences of climate change and two potential management actions on the population dynamics of a vulnerable and iconic Hawaiian forest bird, the ‘I‘iwi (Drepanis coccinea; hereafter IIWI).

Technical Report↗

USGS2022

Guiding principles for using satellite-derived maps in rangeland management

On the Ground Rangeland management has entered a new era with the accessibility and advancement of satellite-derived maps. Maps provide a comprehensive view of rangelands in space and time, and challenge us to think critically about natural variability. Here, we advance the practice of using satellite-derived maps with four guiding principles designed to increase end user confidence and thereby accessibility of these data for decision-making.

Idaho↗

USGS2021

Validation of the U.S. Geological Survey’s Land Change Monitoring, Assessment and Projection (LCMAP) collection 1.0 annual land cover products 1985–2017

The U.S. Geological Survey Land Change Monitoring, Assessment and Projection (USGS LCMAP) has released a suite of annual land cover and land cover change products for the conterminous United States (CONUS). The accuracy of these products was assessed using an independently collected land cover reference sample dataset produced by analysts interpreting Landsat data, high-resolution aerial photographs, and other ancillary data. The reference sample of nearly 25,000 pixels and the accompanying 33-year time series of annual land cover reference labels allowed for a comprehensive assessment of accuracy of the LCMAP land cover and land cover change products. Overall accuracy (± standard error) for the per-pixel assessment across all years for the eight land cover classes was 82.5% (±0.2%). Overall accuracy was consistent year-to-year within a range of 1.5% but varied regionally with lower accuracy in the eastern United States. User’s accuracy (UA) and producer’s accuracy (PA) for CONUS ranged from the higher accuracies of Water (UA=96%, PA=93%) and Tree Cover (UA=90%, PA=83%) to the lower accuracies of Wetland (UA=69%, PA=74%) and Barren (UA=43%, PA=57%). For a binary change / no change classification, UA of change was 13% (±0.5%) and PA was 16% (±0.6%) for CONUS when agreement was defined as a match by the exact year of change. UA and PA improved to 28% and 34% when agreement was defined as the change being detected by the map and reference data within a ±2-year window. Change accuracy was higher in the eastern United States compared to the western US. UA was 49% (±0.3) and PA was 54% (±0.3) for the footprint of change (defined as the area experiencing at least one land cover change from 1985–2017). For class-specific loss and gain when agreement was defined as an exact year match, UA and PA were generally below 30%, with Tree Cover loss being the most accurately mapped change (UA=25%, PA=31%). These accuracy results provide users with information to assess the suitability of LCMAP data and information to guide future research for improving LCMAP products, particularly focusing on the challenges of accurately mapping annual land cover change.

Remote Sensing of Environment↗

USGS2025

User’s guide for the National Hydrography Dataset Plus High Resolution (NHDPlus HR)

The National Hydrography Dataset Plus High Resolution (NHDPlus HR) is a scalable hydrologic geospatial fabric or framework, built from (1) the High Resolution (1:24,000-scale or better) National Hydrography Dataset (NHD), (2) nationally complete Watershed Boundary Dataset (WBD), and (3) 1/3-arc-second 3D Elevation Program (3DEP) digital elevation model (DEM) data (at a 10-meter ground spacing; or 5-meter 3DEP DEM in Alaska only). The NHDPlus HR provides a modeling and assessment framework at a local 1:24,000 scale, while nesting seamlessly into the national context. NHDPlus HR is modeled after the highly successful NHDPlus version 2 (NHDPlusV2). Like NHDPlusV2, the NHDPlus HR includes data for a nationally seamless network of stream reaches, elevation-based catchment areas, flow surfaces, and value-added attributes that enhance stream-network navigation, analysis, and data display. However, NHDPlus HR provides much greater spatial detail than NHDPlusV2, while NHDPlusV2 is, at present, more complete in its attribution of additions, removals, and diversions, as well as stream connectivity. This user’s guide is intended to provide necessary information and guidance in the use of NHDPlus HR data.

Scientific Investigations Report↗

USGS2004

User's Guide for the MapImage Reprojection Software Package, Version 1.01

Scientists routinely accomplish small-scale geospatial modeling in the raster domain, using high-resolution datasets (such as 30-m data) for large parts of continents and low-resolution to high-resolution datasets for the entire globe. Recently, Usery and others (2003a) expanded on the previously limited empirical work with real geographic data by compiling and tabulating the accuracy of categorical areas in projected raster datasets of global extent. Geographers and applications programmers at the U.S. Geological Survey's (USGS) Mid-Continent Mapping Center (MCMC) undertook an effort to expand and evolve an internal USGS software package, MapImage, or mapimg, for raster map projection transformation (Usery and others, 2003a). Daniel R. Steinwand of Science Applications International Corporation, Earth Resources Observation Systems Data Center in Sioux Falls, S. Dak., originally developed mapimg for the USGS, basing it on the USGS's General Cartographic Transformation Package (GCTP). It operated as a command line program on the Unix operating system. Through efforts at MCMC, and in coordination with Mr. Steinwand, this program has been transformed from an application based on a command line into a software package based on a graphic user interface for Windows, Linux, and Unix machines. Usery and others (2003b) pointed out that many commercial software packages do not use exact projection equations and that even when exact projection equations are used, the software often results in error and sometimes does not complete the transformation for specific projections, at specific resampling resolutions, and for specific singularities. Direct implementation of point-to-point transformation with appropriate functions yields the variety of projections available in these software packages, but implementation with data other than points requires specific adaptation of the equations or prior preparation of the data to allow the transformation to succeed. Additional constraints apply to global raster data. It appears that some packages use the USGS's GCTP or similar point transformations without adaptation to the specific characteristics of raster data (Usery and others, 2003b). It is most common for programs to compute transformations of raster data in an inverse fashion. Such mapping can result in an erroneous position and replicate data or create pixels not in the original space. As Usery and others (2003a) indicated, mapimg performs a corresponding forward transformation to ensure the same location results from both methods. The primary benefit of this function is to mask cells outside the domain. MapImage 1.01 is now on the Web. You can download the User's Guide, source, and binaries from the following site: http://mcmcweb.er.usgs.gov/carto_research/projection/acc_proj_data.html

Open-File Report↗

USGS2022

Bridging the gap between spatial modeling and management of invasive annual grasses in the imperiled sagebrush biome

Invasions of native plant communities by non-native species present major challenges for ecosystem management and conservation. Invasive annual grasses such as cheatgrass, medusahead, and ventenata are pervasive and continue to expand their distributions across imperiled sagebrush-steppe communities of the western United States. These invasive grasses alter native plant communities, ecosystem function, and fire regimes, threatening sagebrush ecosystem persistence. Spatial data describing the distribution and abundance of invasive species are often used by resource managers to identify, target, and determine needed interventions. However, there are challenges associated with translating these datasets into management actions. We conducted a review of available spatial products to assess advances in, and barriers to, applying contemporary model-based maps to support rangeland management. We found dozens of regional data products describing cheatgrass or annual herbaceous cover and few maps describing ventenata or medusahead. Over the past decade, IAG spatial data increased in spatial and temporal resolution and increasingly used response variables that indicate the severity of infestation such as percent cover. Despite improvements, use of such data is limited by the time required to find, compare, understand, and translate model-based maps into management strategy. There is also a need for products with higher spatial resolution and accuracy. In collaboration with a multipartner stakeholder group, we identified key considerations that guide selection of IAG spatial data products for use by land managers and other users. On the basis of these considerations, we discuss issues that contribute to a research-implementation gap between users and product developers and suggest future directions for improved development of management-ready spatial products.

Rangeland Ecology & Management↗