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Geographic Information for Analysis of Highway Runoff-Quality Data on a National or Regional Scale in the Conterminous United States

Spatial data are important for interpretation of water-quality information on a regional or national scale. Geographic information systems (GIS) facilitate interpretation and integration of spatial data. The geographic information and data compiled for the conterminous United States during the National Highway Runoff Water-Quality Data and Methodology Synthesis project is described in this document, which also includes information on the structure, file types, and the geographic information in the data files. This 'geodata' directory contains two subdirectories, labeled 'gisdata' and 'gisimage.' The 'gisdata' directory contains ArcInfo coverages, ArcInfo export files, shapefiles (used in ArcView), Spatial Data Transfer Standard Topological Vector Profile format files, and meta files in subdirectories organized by file type. The 'gisimage' directory contains the GIS data in common image-file formats. The spatial geodata includes two rain-zone region maps and a map of national ecosystems originally published by the U.S. Environmental Protection Agency; regional estimates of mean annual streamflow, and water hardness published by the Federal Highway Administration; and mean monthly temperature, mean annual precipitation, and mean monthly snowfall modified from data published by the National Climatic Data Center and made available to the public by the Oregon Climate Service at Oregon State University. These GIS files were compiled for qualitative spatial analysis of available data on a national and(or) regional scale and therefore should be considered as qualitative representations, not precise geographic location information.

Open-File Report

Documentation and analysis of a geographic information system application for combining data layers, using nonpoint-source pollution as an example

A geographical information system application has been developed that allows scientists to combine multiple data layers into a single data layer. This application provides an effective tool for identifying areas where the potential effect of the combination of data layers may be greater than any single data layer. Such a tool is useful in studying an activity that cannot be measured directly. Scientists wanting to identify areas where an activity may have the greatest effect can identify factors that directly or indirectly reflect the effect of the activity being studied. When combined, these factors would identify areas where the potential for the activity to have an effect are greatest. The data layers used to develop the single data layer determine the activity addressed by the application?the application was developed to identify areas where the potential for nonpoint-source pollution to affect areas of Indiana is greater relative to other areas in Indiana. To evaluate the potential in other states or areas, data layers for those states or areas would be used. To address a different activity, even activities not related to water resources, data layers that directly or indirectly reflect the effects of the activity being studied would be used in the application. The application was developed using Environmental System Research Institute's ArcView geographical information system and the ArcView extension, Spatial Analyst. To use the application, the user selects data layers related to the activity being studied, describes the variability of a data element between geographic areas on each data layer, assigns a relative importance factor to each data layer, and focuses the output by identifying a watershed of interest. The application then assigns a rank value to the features within each data layer on the basis of the spatial variation of the data layer. The data layers are converted to grids. The values of the grid cells are the product of the rank values and the importance factors. The cells for each data layer are combined to form a single grid. The combination is summarized to describe the spatial variation for the watershed of interest. The combined data layer does not show the actual potential effect of the selected factors but rather the relative difference in the potential effect among areas when all data layers are considered. An analysis of the application indicates that the selected data layers to be combined should be at the greatest spatial resolution possible; however, all data layers do not have to be at the same spatial resolution. The spatial variation of the data layers should be adequately defined. The size of each grid cell should be small enough to maintain the spatial definition of smaller features within the data layers. The most accurate results are shown to occur when the values for the grid cells representing the individual data layers are summed and the mean of the summed grid-cell values is used to describe the watershed of interest.

Indiana

Extracting topographic structure from digital elevation data for geographic information-system analysis

Software tools have been developed at the U.S. Geological Survey's EROS Data Center to extract topographic structure and to delineate watersheds and overland flow paths from digital elevation models. The tools are specialpurpose FORTRAN programs interfaced with general-purpose raster and vector spatial analysis and relational data base management packages. The first phase of analysis is a conditioning phase that generates three data sets: the original OEM with depressions filled, a data set indicating the flow direction for each cell, and a flow accumulation data set in which each cell receives a value equal to the total number of cells that drain to it. The original OEM and these three derivative data sets can then be processed in a variety of ways to optionally delineate drainage networks, overland paths, watersheds for userspecified locations, sub-watersheds for the major tributaries of a drainage network, or pour point linkages between watersheds. The computer-generated drainage lines and watershed polygons and the pour point linkage information can be transferred to vector-based geographic information systems for futher analysis. Comparisons between these computergenerated features and their manually delineated counterparts generally show close agreement, indicating that these software tools will save analyst time spent in manual interpretation and digitizing.

Photogrammetric Engineering and Remote Sensing

Calculation of coal resources using ARC/INFO and Earth Vision; methodology for the National Coal Resource Assessment

This report documents a comparison of two methods of resource calculation that are being used in the National Coal Resource Assessment project of the U.S. Geological Survey (USGS). Tewalt (1998) discusses the history of using computer software packages such as GARNET (Graphic Analysis of Resources using Numerical Evaluation Techniques), GRASS (Geographic Resource Analysis Support System), and the vector-based geographic information system (GIS) ARC/INFO (ESRI, 1998) to calculate coal resources within the USGS. The study discussed here, compares resource calculations using ARC/INFO* (ESRI, 1998) and EarthVision (EV)* (Dynamic Graphics, Inc. 1997) for the coal-bearing John Henry Member of the Straight Cliffs Formation of Late Cretaceous age in the Kaiparowits Plateau of southern Utah. Coal resource estimates in the Kaiparowits Plateau using ARC/INFO are reported in Hettinger, and others, 1996.

Open-File Report

Grassland live fractional cover map creation and Geographic Information System (GIS) analysis for rangeland management supporting Kenya Northern Rangelands Trust Conservancies

The handbooks and synchronized MP4 recordings provide hands-on instruction for creating and analyzing vegetation live fractional cover (LFC) maps. The methods and protocols used in the instruction materials follow those developed and recorded in Rangoonwala and Ramsey (2019). The LFC mapping and geographic information system (GIS) analyses highlight the consortium of rangeland conservancies covering the semiarid central region of Kenya (approximately 44,000 square kilometers). The instruction materials are separated into two parts: processing and map-product creation based on remote-sensing images and GIS analyses of the created maps for rangeland management. The image processing is conducted using the advanced and professional software package SeNtinels Application Platform (SNAP) that is supported and maintained by the European Space Agency. SNAP is a free image analyses software package available for download. It is largely icon driven but offers simple to advanced program inserts and batch processing. The GIS analyses are conducted using the software package Quantum Geographic Information System (QGIS), another free and downloadable software. QGIS is compatible with numerous software, including the Esri suite of ArcGIS software and database structure. The image data includes both high-spatial-resolution Sentinel-2 optical data and Sentinel-1 synthetic aperture radar (SAR). Both datasets are freely available via a public portal that is maintained by the European Space Agency. The image-processing instruction handbook covers all aspects of acquiring and processing satellite-image data and importing vector-data sources into SNAP. The GIS analysis handbook covers final creation of map products from the maps created in SNAP and creation of GIS procedures in QGIS that are needed to manage the rangeland resources for wildlife and pastoral grazing. Although focused on the Kenyan conservancies and their semiarid environment, the processing methods and procedures are applicable for similar environments and management, and to a large part, even for integrated mapping and GIS functionality of any managed landscape resource. The instruction handbooks are synchronized to MP4 training videos created with U.S. Geological Survey-licensed Camtasia 9 software. The workbook and MP4 video combinations are suitable for a single user or a workshop setting.

Open-File Report

US GeoData

US GeoData tapes are computer tapes which contain cartographic data in digital form. The 1:2,000,000-scale data are available in two forms. The graphic form can be used to generate computer-plotted maps. The content and scale of the maps can be varied to meet your needs. The topologically-structured form of US GeoData is suitable for input to geographic information systems for use in spatial analysis and geographic studies. Both forms must be used in conjunction with appropriate software. US GeoData tapes offer convenience, accuracy, flexibility, and cost effectiveness to many map users. Business, industry, and government users who are involved in network planning and analysis, transportation, demography, land use, or any activity where data can be related to, or plotted on a map will find US GeoData a valuable resource.

General Information Product

Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2002-07

Geographic information system (GIS) technology has become an important tool for scientific investigation, resource management, and environmental planning. A GIS is a computer-aided system capable of collecting, storing, analyzing, and displaying spatially referenced digital data. GIS technology is particularly useful when analyzing a wide variety of spatial data such as with remote sensing and spatial analysis. Remote sensing involves collecting remotely sensed data, such as satellite imagery, aerial photography, or radar images, and analyzing the data to gather information or investigate trends about the environment or the Earth's surface. Spatial analysis combines remotely sensed, thematic, statistical, quantitative, and geographical data through overlay, modeling, and other analytical techniques to investigate specific research questions. It is the combination of data formats and analysis techniques that has made GIS an essential tool in scientific investigations. This document presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup from 2002 through 2007.

Fact Sheet

New England salt marsh pools: A quantitative analysis of geomorphic and geographic features

New England salt marsh pools provide important wildlife habitat and are the object of on-going salt marsh restoration projects; however, they have not been quantified in terms of their basic geomorphic and geographic traits. An examination of 32 ditched and unditched salt marshes from the Connecticut shore of Long Island Sound to southern Maine, USA, revealed that pools from ditched and unditched marshes had similar average sizes of about 200 m 2 , averaged 29 cm in depth, and were located about 11 m from the nearest tidal flow. Unditched marshes had 3 times the density (13 pools/ha), 2.5 times the pool coverage (83 m pool/km transect), and 4 times the total pool surface area per hectare (913 m 2 pool/ha salt marsh) of ditched sites. Linear regression analysis demonstrated that an increasing density of ditches (m ditch/ha salt marsh) was negatively correlated with pool density and total pool surface area per hectare. Creek density was positively correlated with these variables. Thus, it was not the mere presence of drainage channels that were associated with low numbers of pools, but their type (ditch versus creek) and abundance. Tidal range was not correlated with pool density or total pool surface area, while marsh latitude had only a weak relationship to total pool surface area per hectare. Pools should be incorporated into salt marsh restoration planning, and the parameters quantified here may be used as initial design targets.

Connecticut, Maine, Massachusetts, New Hampshire,

Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2008-09

Geographic information system (GIS) technology has become an important tool for scientific investigation, resource management, and environmental planning. A GIS is a computer-aided system capable of collecting, storing, analyzing, and displaying spatially referenced digital data. GIS technology is useful for analyzing a wide variety of spatial data. Remote sensing involves collecting remotely sensed data, such as satellite imagery, aerial photography, or radar images, and analyzing the data to gather information or investigate trends about the environment or the Earth's surface. Spatial analysis combines remotely sensed, thematic, statistical, quantitative, and geographical data through overlay, modeling, and other analytical techniques to investigate specific research questions. It is the combination of data formats and analysis techniques that has made GIS an essential tool in scientific investigations. This fact sheet presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup during 2008 and 2009. After a summary of GIS Workgroup capabilities, brief descriptions of activities by project at the local and national levels are presented. Projects are grouped by the fiscal year (October-September 2008 or 2009) the project ends and include overviews, project images, and Internet links to additional project information and related publications or articles.

Fact Sheet

The noise is the signal: Spatio-temporal variability of production and productivity in high elevation meadows in the Sierra Nevada mountain range of North America

There are expectations that increasing temperatures will lead to significant changes in structure and function of montane meadows, including greater water stress on vegetation and lowered vegetation production and productivity. We evaluated spatio-temporal dynamics in production and productivity in meadows within the Sierra Nevada mountain range of North America by: (1) compiling Landsat satellite data for the Normalized Difference Vegetation Index (NDVI) across a 37-year period (1985–2021) for 8,095 meadows >2,500 m elevation; then, (2) used state-space models, changepoint analysis, geographically-weighted regression (GWR), and distance-decay analysis (DDA) to: (a) identify meadows with decreasing, increasing or no trends for NDVI; (b) detect meadows with abrupt changes (changepoints) in NDVI; and (c) evaluate variation along gradients of latitude, longitude, and elevation for eight indices of temporal dynamics in annual production (mean growing season NDVI; MGS) and productivity (rate of spring greenup; RSP). Meadows with no long-term change or evidence of increasing NDVI were 2.6x more frequent as those with decreasing NDVI (72% vs. 28%). Abrupt changes in NDVI were detected in 48% of the meadows; they occurred in every year of the study and with no indication that their frequency had changed over time. The intermixing of meadows with different temporal dynamics was a consistent pattern for monthly NDVI and, especially, the eight annual indices of MGS and RSP. The DDA showed temporal dynamics in pairs of meadow within a few 100 m of each other were often as different as those hundreds of kilometers apart. Our findings point strongly toward a great diversity of temporal dynamics in meadow production and productivity in the SNV. The heterogeneity in spatial patterns indicated that production and productivity of meadow vegetation is being driven by interplay among climatic, physiographic and biotic factors at basin and meadow scales. Thus, when evaluating spatio-temporal dynamics in condition for many high elevation meadow systems, what might often be considered “noise” may provide greater insight than a “signal” embedded within a large amount of variability.

California

Tracking acid mine-drainage in Southeast Arizona using GIS and sediment delivery models

This study investigates the application of models traditionally used to estimate erosion and sediment deposition to assess the potential risk of water quality impairment resulting from metal-bearing materials related to mining and mineralization. An integrated watershed analysis using Geographic Information Systems (GIS) based tools was undertaken to examine erosion and sediment transport characteristics within the watersheds. Estimates of stream deposits of sediment from mine tailings were related to the chemistry of surface water to assess the effectiveness of the methodology to assess the risk of acid mine-drainage being dispersed downstream of abandoned tailings and waste rock piles. A watershed analysis was preformed in the Patagonia Mountains in southeastern Arizona which has seen substantial mining and where recent water quality samples have reported acidic surface waters. This research demonstrates an improvement of the ability to predict streams that are likely to have severely degraded water quality as a result of past mining activities. ?? Springer Science+Business Media B.V. 2007.

Environmental Monitoring and Assessment

Shapes on a plane: Evaluating the impact of projection distortion on spatial binning

One method for working with large, dense sets of spatial point data is to aggregate the measure of the data into polygonal containers, such as political boundaries, or into regular spatial bins such as triangles, squares, or hexagons. When mapping these aggregations, the map projection must inevitably distort relationships. This distortion can impact the reader’s ability to compare count and density measures across the map. Spatial binning, particularly via hexagons, is becoming a popular technique for displaying aggregate measures of point data sets. Increasingly, we see questionable use of the technique without attendant discussion of its hazards. In this work, we discuss when and why spatial binning works and how mapmakers can better understand the limitations caused by distortion from projecting to the plane. We introduce equations for evaluating distortion’s impact on one common projection (Web Mercator) and discuss how the methods used generalize to other projections. While we focus on hexagonal binning, these same considerations affect spatial bins of any shape, and more generally, any analysis of geographic data performed in planar space.

Cartography and Geographic Information Science

Climate has contrasting direct and indirect effects on armed conflicts

There is an active debate regarding the influence that climate has on the risk of armed conflict, which stems from challenges in assembling unbiased datasets, competing hypotheses on the mechanisms of climate influence, and the difficulty of disentangling direct and indirect climate effects. We use gridded historical non-state conflict records, satellite data, and land surface models in a structural equation modeling approach to uncover the direct and indirect effects of climate on violent conflicts in Africa and the Middle East (ME). We show that climate–conflict linkages in these regions are more complex than previously suggested, with multiple mechanisms at work. Warm temperatures and low rainfall direct effects on conflict risk were stronger than indirect effects through food and water supplies. Warming increases the risk of violence in Africa but unexpectedly decreases this risk in the ME. Furthermore, at the country level, warming decreases the risk of violence in most West African countries. Overall, we find a non-linear response of conflict to warming across countries that depends on the local temperature conditions. We further show that magnitude and sign of the effects largely depend on the scale of analysis and geographical context. These results imply that extreme caution should be exerted when attempting to explain or project local climate–conflict relationships based on a single, generalized theory.

Environmental Research Letters

A map overlay error model based on boundary geometry

An error model for quantifying the magnitudes and variability of errors generated in the areas of polygons during spatial overlay of vector geographic information system layers is presented. Numerical simulation of polygon boundary displacements was used to propagate coordinate errors to spatial overlays. The model departs from most previous error models in that it incorporates spatial dependence of coordinate errors at the scale of the boundary segment. It can be readily adapted to match the scale of error-boundary interactions responsible for error generation on a given overlay. The area of error generated by overlay depends on the sinuosity of polygon boundaries, as well as the magnitude of the coordinate errors on the input layers. Asymmetry in boundary shape has relatively little effect on error generation. Overlay errors are affected by real differences in boundary positions on the input layers, as well as errors in the boundary positions. Real differences between input layers tend to compensate for much of the error generated by coordinate errors. Thus, the area of change measured on an overlay layer produced by the XOR overlay operation will be more accurate if the area of real change depicted on the overlay is large. The model presented here considers these interactions, making it especially useful for estimating errors studies of landscape change over time. ?? 2005 The Ohio State University.

Geographical Analysis

A selected bibliography: Remote sensing applications in geography

The bibliography contains 82 citations of selected publications and technical reports. The references deal with the application of remote sensing techniques to the collection and analysis of geographic data. All of the citations were published between January 1968 and July 1977.

Report

Bedrock Geologic Map of New Hampshire, a Digital Representation of Lyons and Others 1997 Map and Ancillary Files

The New Hampshire Geological Survey collects data and performs research on the land, mineral, and water resources of the State, and disseminates the findings of such research to the public through maps, reports, and other publications. The Bedrock Geologic Map of New Hampshire, by John B. Lyons, Wallace A. Bothner, Robert H. Moench, and James B. Thompson, was published in paper format by the U.S. Geological Survey (USGS) in 1997. The online version of this CD contains digital datasets of the State map that are intended to assist the professional geologist, land-use planners, water resource professionals, and engineers and to inform the interested layperson. In addition to the bedrock geology, the datasets include geopolitical and hydrologic information, such as political boundaries, quadrangle boundaries, hydrologic units, and water-well data. A more thorough explanation for each of these datasets may be found in the accompanying metadata files. The data are spatially referenced and may be used in a geographic information system (GIS). ArcExplorer, the Environmental Systems Research Institute's (ESRI) free GIS data viewer, is available at http://www.esri.com/software/arcexplorer. ArcExplorer provides basic functions that are needed to harness the power and versatility of the spatial datasets. Additional information on the viewer and other ESRI products may be found on the ArcExplorer website. Although extensive review and revisions of the data have been performed by the USGS and the New Hampshire Geological Survey, these data represent interpretations made by professional geologists using the best available data, and are intended to provide general geologic information. Use of these data at scales larger than 1:250,000 will not provide greater accuracy. The data are not intended to replace site-specific or specific-use investigations. The U.S. Geological Survey, New Hampshire Geological Survey, and State of New Hampshire make no representation or warranty, expressed or implied, regarding the use, accuracy, or completeness of the data presented herein, or from a map printed from these data; nor shall the act of distribution constitute any such warranty. The New Hampshire Geological Survey disclaims any legal responsibility or liability for interpretations made from the map, or decisions based thereon. For more information on New Hampshire Geological Survey programs please visit the State's website at http://des.nh.gov/Geology/. New Hampshire Geographically Referenced Analysis and Information Transfer System (NH GRANIT) provides access to statewide GIS (http://www.granit.unh.edu/). Questions about this CD or about other datasets should be directed to the New Hampshire Department of Environmental Services.

Data Series