This layer features special areas of interest (AOIs) that have been contributed to Esri Community Maps using the new Community Maps Editor app. The data that is accepted by Esri will be included in selected Esri basemaps, including our suite of Esri Vector Basemaps, and made available through this layer to export and use offline. Export DataThe contributed data is also available for contributors and other users to export (or extract) and re-use for their own purposes. Users can export the full layer from the ArcGIS Online item details page by clicking the Export Data button and selecting one of the supported formats (e.g. shapefile, or file geodatabase (FGDB)). User can extract selected layers for an area of interest by opening in Map Viewer, clicking the Analysis button, viewing the Manage Data tools, and using the Extract Data tool. To display this data with proper symbology and metadata in ArcGIS Pro, you can download and use this layer file.Data UsageThe data contributed through the Community Maps Editor app is primarily intended for use in the Esri Basemaps. Esri staff will periodically (e.g. weekly) review the contents of the contributed data and either accept or reject the data for use in the basemaps. Accepted features will be added to the Esri basemaps in a subsequent update and will remain in the app for the contributor or others to edit over time. Rejected features will be removed from the app.Esri Community Maps Contributors and other ArcGIS Online users can download accepted features from this layer for their internal use or map publishing, subject to the terms of use below.

Become an ArcGIS Hub Specialist.ArcGIS Hub is a cloud-based engagement platform that helps organizations work more effectively with their communities. Learn how to use ArcGIS Hub capabilities and related technology to coordinate and engage with external agencies, community partners, volunteers, and citizens to tackle the projects that matter most in your community._Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...

Downloadable Layers: SPSD Office Locations 2024SPSD MLRA Soil Survey Office Area's 2024SPSD Region Polygons 2024Major Land Resource Areas (MLRA)

Geographic Information System (GIS) Analytics Market Outlook

The global Geographic Information System (GIS) Analytics market size is projected to grow remarkably from $9.1 billion in 2023 to $21.7 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 10.2% during the forecast period. This substantial growth can be attributed to several factors such as technological advancements in GIS, increasing adoption in various industry verticals, and the rising importance of spatial data for decision-making processes.

The primary growth driver for the GIS Analytics market is the increasing need for accurate and efficient spatial data analysis to support critical decision-making processes across various industries. Governments and private sectors are investing heavily in GIS technology to enhance urban planning, disaster management, and resource allocation. With the world becoming more data-driven, the reliance on GIS for geospatial data has surged, further propelling its market growth. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) with GIS is revolutionizing the analytics capabilities, offering deeper insights and predictive analytics.

Another significant growth factor is the expanding application of GIS analytics in disaster management and emergency response. Natural disasters such as hurricanes, earthquakes, and wildfires have highlighted the importance of GIS in disaster preparedness, response, and recovery. The ability to analyze spatial data in real-time allows for quicker and more efficient allocation of resources, thus minimizing the impact of disasters. Moreover, GIS analytics plays a pivotal role in climate change studies, helping scientists and policymakers understand and mitigate the adverse effects of climate change.

The transportation sector is also a major contributor to the growth of the GIS Analytics market. With the rapid urbanization and increasing traffic congestion in cities, there is a growing demand for effective transport management solutions. GIS analytics helps in route optimization, traffic management, and infrastructure development, thereby enhancing the overall efficiency of transportation systems. The integration of GIS with Internet of Things (IoT) devices and sensors is further enhancing the capabilities of traffic management systems, contributing to the market growth.

Regionally, North America is the largest market for GIS analytics, driven by the high adoption rate of advanced technologies and significant investment in geospatial infrastructure by both public and private sectors. The Asia Pacific region is expected to witness the highest growth rate during the forecast period due to the rapid urbanization, infrastructural developments, and increasing government initiatives for smart city projects. Europe and Latin America are also contributing significantly to the market growth owing to the increasing use of GIS in urban planning and environmental monitoring.

Component Analysis

The GIS Analytics market can be segmented by component into software, hardware, and services. The software segment holds the largest market share due to the continuous advancements in GIS software solutions that offer enhanced functionalities such as data visualization, spatial analysis, and predictive modeling. The increasing adoption of cloud-based GIS software solutions, which offer scalable and cost-effective options, is further driving the growth of this segment. Additionally, open-source GIS software is gaining popularity, providing more accessible and customizable options for users.

The hardware segment includes GIS data collection devices such as GPS units, remote sensing instruments, and other data acquisition tools. This segment is witnessing steady growth due to the increasing demand for high-precision GIS data collection equipment. Technological advancements in hardware, such as the development of LiDAR and drones for spatial data collection, are significantly enhancing the capabilities of GIS analytics. Additionally, the integration of mobile GIS devices is facilitating real-time data collection, contributing to the growth of the hardware segment.

The services segment encompasses consulting, implementation, training, and maintenance services. This segment is expected to grow at a significant pace due to the increasing demand for professional services to manage and optimize GIS systems. Organizations are seeking expert consultants to help them leverage GIS analytics for strategic decision-making and operational efficiency. Additionally, the growing complexity o

GIS Mapping Software Market Outlook

The global GIS Mapping Software market size was valued at approximately USD 8.5 billion in 2023 and is projected to reach around USD 17.5 billion by 2032, growing at a CAGR of 8.3% from 2024 to 2032. This robust growth is driven by the increasing adoption of geospatial technologies across various sectors, including urban planning, disaster management, and agriculture.

One of the primary growth factors for the GIS Mapping Software market is the rising need for spatial data analytics. Organizations are increasingly recognizing the value of geographical data in making informed decisions, driving the demand for sophisticated mapping solutions. Furthermore, advancements in satellite imaging technology and the increasing availability of high-resolution imagery are enhancing the capabilities of GIS software, making it a crucial tool for various applications.

Another significant driver is the integration of GIS with emerging technologies such as artificial intelligence (AI) and the Internet of Things (IoT). These integrations are facilitating real-time data processing and analysis, thereby improving the efficiency and accuracy of GIS applications. For instance, in urban planning and disaster management, real-time data can significantly enhance predictive modeling and response strategies. This synergy between GIS and cutting-edge technologies is expected to fuel market growth further.

The growing emphasis on sustainable development and smart city initiatives globally is also contributing to the market's expansion. Governments and private entities are investing heavily in GIS technologies to optimize resource management, enhance public services, and improve urban infrastructure. These investments are particularly evident in developing regions where urbanization rates are high, and there is a pressing need for efficient spatial planning and management.

In terms of regional outlook, North America holds a significant share of the GIS Mapping Software market, driven by robust technological infrastructure and high adoption rates across various industries. However, Asia Pacific is expected to witness the highest growth rate during the forecast period. This growth is attributed to rapid urbanization, increasing government initiatives for smart cities, and rising investments in infrastructure development.

The Geographic Information Systems Platform has become an integral part of modern spatial data management, offering a comprehensive framework for collecting, analyzing, and visualizing geographic data. This platform facilitates the integration of diverse data sources, enabling users to create detailed maps and spatial models that support decision-making across various sectors. With the increasing complexity of urban environments and the need for efficient resource management, the Geographic Information Systems Platform provides the tools necessary for real-time data processing and analysis. Its versatility and scalability make it an essential component for organizations looking to leverage geospatial data for strategic planning and operational efficiency.

Component Analysis

The GIS Mapping Software market is segmented by component into software and services. The software segment dominates the market, primarily due to the continuous advancements in GIS software capabilities. Modern GIS software offers a range of functionalities, from basic mapping to complex spatial analysis, making it indispensable for various sectors. These software solutions are increasingly user-friendly, allowing even non-experts to leverage geospatial data effectively.

Moreover, the software segment is witnessing significant innovation with the integration of AI and machine learning algorithms. These advancements are enabling more sophisticated data analysis and predictive modeling, which are crucial for applications such as disaster management and urban planning. The adoption of cloud-based GIS software is also on the rise, offering scalability and real-time data processing capabilities, which are essential for dynamic applications like transport management.

The services segment, although smaller than the software segment, is also experiencing growth. This includes consulting, implementation, and maintenance services that are critical for the successful deployment and operation of GIS systems. The increasing complexity of GIS applications nec

This vector tile layer is designed to support exporting small volumes of basemap tiles for offline use. The content of this layer is equivalent to World Terrain Reference map. This layer provides a detailed basemap for the world symbolized with populated places, and admin area boundary lines. The minimal features and styling is designed to draw attention to your thematic content. It is designed for use with World Terrain Base and shaded relief for added content. See World Terrain Reference for more details.Use this MapThis vector tile service supporting this layer will enable you to export a small number of tiles in a single request. This layer is not intended to be used to display live map tiles for use in a web map or web mapping application. To display map tiles, please use World Terrain Reference.Service Information for DevelopersTo export tiles for World Terrain Reference (for Export), you must use the instance of the World_Basemap_Export_v2 service hosted on basemaps.arcgis.com referenced by this layer (see URL in Contents below), which has the Export Tiles operation enabled. This layer is optimized to minimize the size of the download for offline use. Due to this optimization, there are small differences between this layer and the display optimized World_Basemap_v2 service. This layer is intended to support export of basemap tiles for offline use in ArcGIS applications and other applications built with an ArcGIS Runtime SDK.

This feature layer contains the locations of Natural Gas Import/Export Pipeline Facilities along the borders between the Continental United States, Canada, and Mexico for the Homeland Infrastructure Foundation-Level (HIFLD) Database (https://hifld-dhs-gii.gov/HIFLD) as well as the Energy modeling and simulation community. A Natural Gas Import/Export Pipeline Facility delivers natural gas in and out of the Continental United States between foreign countries.

Files are comma delimited. Washington State Law, Ch. 42.56 RCW, prohibits state and local agencies from providing access to lists of individuals intended for use for commercial purposes. No commercial use may be made of any Data comprising lists of individuals contained herein.

The Automated Geospatial Watershed Assessment (AGWA) tool is a GIS-based hydrologic modeling tool that uses commonly available GIS data layers to fully parameterize, execute, and spatially visualize results for the RHEM, KINEROS2, KINEROS-OPUS, SWAT2000, and SWAT2005 watershed runoff and erosion models. Accommodating novice to expert GIS users, it is designed to be used by watershed, water resource, land use, and resource managers and scientists investigating the hydrologic impacts of land-cover/land-use change in small watershed to basin-scale studies. AGWA is currently available as AGWA 1.5 for ArcView 3.x, AGWA 2.x for ArcGIS 9.x, and AGWA 3.X for ArcGIS 10.x. Planning and assessment in land and water resource management are evolving from simple, local-scale problems toward complex, spatially explicit regional ones. Such problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extensive data requirements and the difficult task of building input parameter files, however, have long represented an obstacle to the timely and cost-effective use of such complex models by resource managers. The USDA- ARS Southwest Watershed Research Center, in cooperation with the U.S. EPA Office of Research and Development Landscape Ecology Branch, the University of Arizona, and the University of Wyoming, has developed a GIS tool to facilitate this process. A geographic information system (GIS) provides the framework within which spatially-distributed data are collected and used to prepare model input files and evaluate model results. AGWA uses widely available standardized spatial datasets that can be obtained via the internet. The data are used to develop input parameter files for two watershed runoff and erosion models: KINEROS2 and SWAT.

This dataset is a compilation of address point data for the City of Tempe. The dataset contains a point location, the official address (as defined by The Building Safety Division of Community Development) for all occupiable units and any other official addresses in the City. There are several additional attributes that may be populated for an address, but they may not be populated for every address. Contact: Lynn Flaaen-Hanna, Development Services Specialist Contact E-mail Link: Map that Lets You Explore and Export Address Data Data Source: The initial dataset was created by combining several datasets and then reviewing the information to remove duplicates and identify errors. This published dataset is the system of record for Tempe addresses going forward, with the address information being created and maintained by The Building Safety Division of Community Development. Data Source Type: ESRI ArcGIS Enterprise Geodatabase Preparation Method: N/A Publish Frequency: Weekly Publish Method: Automatic Data Dictionary

Environmental Forensics Expert Witness Service Market Outlook

The Environmental Forensics Expert Witness Service market is poised for substantial growth over the next decade, with global market valuation expected to reach USD 1.5 billion by 2032, driven by increasing environmental regulations and litigations. One primary growth factor is the rising awareness and stricter enforcement of environmental laws worldwide, which necessitate specialized expertise to resolve disputes and determine liability.

Another significant growth driver is the burgeoning number of environmental contamination cases. As industrial activities expand, the incidence of environmental contamination has surged, leading to a rise in legal disputes. Environmental forensics experts play a crucial role in these cases by providing scientifically-backed assessments and testimony, thereby influencing the market growth. Moreover, the increasing recognition of environmental forensics as a vital tool in understanding and rectifying environmental damages has made expert witness services indispensable in legal proceedings.

Technological advancements in data analysis and site assessment techniques have also spurred market growth. Modern technologies such as Geographic Information Systems (GIS), remote sensing, and advanced analytical chemistry have enhanced the accuracy and efficiency of environmental forensic investigations. These advancements have not only improved the quality of expert testimony but also broadened the scope of services offered by experts, thus contributing to market expansion.

Furthermore, the growing need for litigation support in complex environmental cases is expected to sustain market growth. With the rising complexity of environmental regulations and the intricate nature of contamination cases, the demand for expert witnesses who can provide comprehensive litigation support has intensified. This support includes detailed data analysis, preparation of expert reports, and testimony in court, all of which are critical in influencing legal outcomes.

Regionally, North America holds the largest market share owing to stringent environmental regulations and a high number of environmental litigations. The presence of numerous industrial activities and a robust legal framework further augment the demand for environmental forensics experts in this region. Europe follows closely, driven by strict environmental policies and the proactive stance of government agencies in addressing environmental issues. Meanwhile, the Asia Pacific region is expected to witness the highest CAGR due to rapid industrialization and increasing environmental awareness.

Service Type Analysis

Within the Environmental Forensics Expert Witness Service market, the Service Type segment includes Site Assessment, Data Analysis, Expert Testimony, Litigation Support, and Others. Each service type addresses specific aspects of environmental forensic investigations, offering tailored solutions to meet diverse client needs. Site Assessment services encompass the initial evaluation of suspected contamination sites to gather crucial data, which forms the basis of forensic investigations. This service is particularly essential in identifying the extent and sources of contamination, making it a fundamental component of environmental forensics.

Data Analysis services involve the meticulous examination of collected environmental data to uncover patterns, sources, and extents of contamination. These services leverage advanced analytical techniques and technologies to provide accurate, reliable, and actionable insights. The growing reliance on data-driven decision-making in environmental cases has significantly bolstered the demand for data analysis services, positioning them as a vital segment in the market.

Expert Testimony is another critical service, as it entails presenting scientific findings and interpretations in legal settings. Environmental forensics experts provide compelling, evidence-based testimonies that can significantly influence the outcomes of environmental litigations. The increasing complexity of environmental cases necessitates expert testimony that is not only scientifically sound but also easily comprehensible to legal professionals and juries.

Litigation Support services encompass a broad range of activities aimed at assisting legal teams in building strong cases. This includes preparing detailed expert reports, offering consultation during legal proceedings, and providing strategic insights based on forensic findings. The comprehe

This vector tile layer is designed to support exporting small volumes of basemap tiles for offline use. The content of this layer is equivalent to World Street Map (with Relief). This layer includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, building footprints, and administrative boundaries, designed for use with shaded relief for added context. See World Street Map (with Relief) for more details.Use this MapThis vector tile service supporting this layer will enable you to export a small number of tiles in a single request. This layer is not intended to be used to display live map tiles for use in a web map or web mapping application. To display map tiles, please use World Street Map (with Relief).Service Information for DevelopersTo export tiles for World Street Map (with Relief- for Export), you must use the instance of the World_Basemap_Export_v2 service hosted on basemaps.arcgis.com referenced by this layer (see URL in Contents below), which has the Export Tiles operation enabled. This layer is optimized to minimize the size of the download for offline use. Due to this optimization, there are small differences between this layer and the display optimized World_Basemap_v2 service. This layer is intended to support export of basemap tiles for offline use in ArcGIS applications and other applications built with an ArcGIS Runtime SDK.

Web-based GIS mapping application.Contains all available GIS and mapping resources for Cuyahoga County.Use the application to explore data using the available search, identify, and query tools; markup the map with the drawing tools; export the map to a geo-referenced image file; print the map to PDF with a custom title and include a legend and scale.View the 'Help Guide' for FAQs, tool tips, and additional information about the application and the data.

Crowther_Nature_Files.zip This description pertains to the original download. Details on revised (newer) versions of the datasets are listed below. When more than one version of a file exists in Figshare, the original DOI will take users to the latest version, though each version technically has its own DOI. -- Two global maps (raster files) of tree density. These maps highlight how the number of trees varies across the world. One map was generated using biome-level models of tree density, and applied at the biome scale. The other map was generated using ecoregion-level models of tree density, and applied at the ecoregion scale. For this reason, transitions between biomes or between ecoregions may be unrealistically harsh, but large-scale estimates are robust (see Crowther et al 2015 and Glick et al 2016). At the outset, this study was intended to generate reliable estimates at broad spatial scales, which inherently comes at the cost of fine-scale precision. For this reason, country-scale (or larger) estimates are generally more robust than individual pixel-level estimates. Additionally, due to data limitations, estimates for Mangroves and Tropical coniferous forest (as identified by WWF and TNC) were generated using models constructed from Topical moist broadleaf forest data and Temperate coniferous forest data, respectively. Because we used ecological analogy, the estimates for these two biomes should be considered less reliable than those of other biomes . These two maps initially appeared in Crowther et al (2015), with the biome map being featured more prominently. Explicit publication of the data is associated with Glick et al (2016). As they are produced, updated versions of these datasets, as well as alternative formats, will be made available under Additional Versions (see below).

Methods: We collected over 420,000 ground-sources estimates of tree density from around the world. We then constructed linear regression models using vegetative, climatic, topographic, and anthropogenic variables to produce forest tree density estimates for all locations globally. All modeling was done in R. Mapping was done using R and ArcGIS 10.1.

Viewing Instructions: Load the files into an appropriate geographic information system (GIS). For the original download (ArcGIS geodatabase files), load the files into ArcGIS to view or export the data to other formats. Because these datasets are large and have a unique coordinate system that is not read by many GIS, we suggest loading them into an ArcGIS dataframe whose coordinate system matches that of the data (see File Format). For GeoTiff files (see Additional Versions), load them into any compatible GIS or image management program.

Comments: The original download provides a zipped folder that contains (1) an ArcGIS File Geodatabase (.gdb) containing one raster file for each of the two global models of tree density – one based on biomes and one based on ecoregions; (2) a layer file (.lyr) for each of the global models with the symbology used for each respective model in Crowther et al (2015); and an ArcGIS Map Document (.mxd) that contains the layers and symbology for each map in the paper. The data is delivered in the Goode homolosine interrupted projected coordinate system that was used to compute biome, ecoregion, and global estimates of the number and density of trees presented in Crowther et al (2015). To obtain maps like those presented in the official publication, raster files will need to be reprojected to the Eckert III projected coordinate system. Details on subsequent revisions and alternative file formats are list below under Additional Versions.----------

Additional Versions: Crowther_Nature_Files_Revision_01.zip contains tree density predictions for small islands that are not included in the data available in the original dataset. These predictions were not taken into consideration in production of maps and figures presented in Crowther et al (2015), with the exception of the values presented in Supplemental Table 2. The file structure follows that of the original data and includes both biome- and ecoregion-level models.

Crowther_Nature_Files_Revision_01_WGS84_GeoTiff.zip contains Revision_01 of the biome-level model, but stored in WGS84 and GeoTiff format. This file was produced by reprojecting the original Goode homolosine files to WGS84 using nearest neighbor resampling in ArcMap. All areal computations presented in the manuscript were computed using the Goode homolosine projection. This means that comparable computations made with projected versions of this WGS84 data are likely to differ (substantially at greater latitudes) as a product of the resampling. Included in this .zip file are the primary .tif and its visualization support files.

References:

Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., Smith, J. R., Hintler, G., Duguid, M. C., Amatulli, G., Tuanmu, M. N., Jetz, W., Salas, C., Stam, C., Piotto, D., Tavani, R., Green, S., Bruce, G., Williams, S. J., Wiser, S. K., Huber, M. O., Hengeveld, G. M., Nabuurs, G. J., Tikhonova, E., Borchardt, P., Li, C. F., Powrie, L. W., Fischer, M., Hemp, A., Homeier, J., Cho, P., Vibrans, A. C., Umunay, P. M., Piao, S. L., Rowe, C. W., Ashton, M. S., Crane, P. R., and Bradford, M. A. 2015. Mapping tree density at a global scale. Nature, 525(7568): 201-205. DOI: http://doi.org/10.1038/nature14967Glick, H. B., Bettigole, C. B., Maynard, D. S., Covey, K. R., Smith, J. R., and Crowther, T. W. 2016. Spatially explicit models of global tree density. Scientific Data, 3(160069), doi:10.1038/sdata.2016.69.

RPD's patrol procedures training bulletin on drug recognition expert protocol.

This Feature Layer Collection contains publicly shared data from Envirostor, the Department of Toxic Substances Control's Project Management Solution. The data includes Cleanup Sites, Hazardous Waste Sites, and Inspection, Compliance and Enforcement sites. Cleanup Sites: DTSC conducts and supervises investigation and cleanup actions at sites where oil or hazardous chemicals have been or may be released into the environment. Cleanup activities take place at active and abandoned waste sites, federal and state facilities and properties, and where any storage tanks have leaked. DTSC, federal and other state agencies or municipalities, or the company or party responsible for the contamination may perform cleanups. Cleanup can also include site reuse and redevelopment. Hazardous Waste Sites: Hazardous waste management facilities receive hazardous wastes for treatment, storage or disposal. These facilities are often referred to as treatment, storage and disposal facilities, or TSDFs, and their activities are described in more detail below: Treatment - Using various processes, such as incineration or oxidation, to alter the character or composition of hazardous wastes. Some treatment processes enable waste to be recovered and reused in manufacturing settings, while other treatment processes dramatically reduce the amount of hazardous waste. Storage - Temporarily holding hazardous wastes until they are treated or disposed. Hazardous waste is commonly stored prior to treatment or disposal, and must be stored in containers, tanks, containment buildings, drip pads, waste piles, or surface impoundments that comply with the Resource Conservation and Recovery Act (RCRA) regulations. Disposal - Permanently containing hazardous wastes. The most common type of disposal facility is a landfill, where hazardous wastes are disposed of in carefully constructed units designed to protect groundwater and surface water resources. ICE Sites: The Department of Toxic Substances Control (DTSC) regulates the generation, transportation, treatment, storage, and disposal of hazardous wastes. DTSC monitors compliance with state and federal hazardous waste requirements by conducting inspections. DTSC works to ensure compliance with environmental requirements. When warranted, DTSC will take civil or criminal enforcement action against violators of environmental laws. DTSC provides compliance incentives and auditing to encourage facilities to find and disclose violations to the Agency. Violations may also be discovered from tips/complaints received by the Agency from the public. Violations discovered as a result of any of these activities may lead to civil or criminal enforcement. This data is a geospatial representation of data found at https://www.envirostor.dtsc.ca.gov/public/. This dataset is updated daily.

The Unpublished Digital Geologic-GIS Map of Virgin Islands National Park, Virgin Islands is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (viis_geology.gdb), a 10.1 ArcMap (.mxd) map document (viis_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (viis_geology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.txt) and FAQ (.pdf) formats, and a GIS readme file (viis_geology_gis_readme.pdf). Please read the viis_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@colostate.edu; see contact information below). The data is also available as a 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. Google Earth software is available for free at: http://www.google.com/earth/index.html. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (viis_geology_metadata.txt or viis_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm). The GIS data projection is NAD83, UTM Zone 20N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth. The data is within the area of interest of Virgin Islands National Park.

The regression analysis of predicting the degree of human impact by expert and non-expert groups, when the regression is split into 2 simultaneous models.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

This dataset contains 4 different scale GEODATA TOPO series, Geoscience Australia topographic datasets. 1M, 2.5M, 5M and 10M with age ranges from 2001 to 2004.

1:1 Million - Global Map Australia 1M 2001 is a digital dataset covering the Australian landmass and island territories, at a 1:1 million scale. Product Specifications -Themes: It consists of eight layers of information: Vector layers - administrative boundaries, drainage, transportation and population centres Raster layers - elevation, vegetation, land use and land cover -Coverage: Australia -Currency: Variable, based on GEODATA TOPO 250K Series 1 -Coordinates: Geographical -Datum: GDA94, AHD -Medium: Free online -Format: -Vector: ArcInfo Export, ESRI Shapefile, MapInfo mid/mif and Vector Product Format (VPF) -Raster: Band Interleaved by Line (BIL)

1:2.5 Million - GEODATA TOPO 2.5M 2003 is a national seamless data product aimed at regional or national applications. It is a vector representation of the Australian landscape as represented on the Geoscience Australia 2.5 million general reference map and is suitable for GIS applications. The product consists of the following layers: built-up areas; contours; drainage; framework; localities; offshore; rail transport; road transport; sand ridges; Spot heights; and waterbodies. It is a vector representation of the Australian landscape as represented on the Geoscience Australia 1:2.5 million scale general reference maps. This data supersedes the TOPO 2.5M 1998 product through the following characteristics: developed according to GEODATA specifications derived from GEODATA TOPO 250K Series 2 data where available. Product Specifications Themes: GEODATA TOPO 2.5M 2003 consists of eleven layers: built-up areas; contours; drainage; framework; localities; offshore; rail transport; road transport; sand ridges; spot heights; and waterbodies Coverage: Australia Currency: 2003 Coordinates: Geographical Datum: GDA94, AHD Format: ArcInfo Export, ArcView Shapefile and MapInfo mid/mif Medium: Free online - Available in ArcInfo Export, ArcView Shapefile and MapInfo mid/mif

1:5 Million - GEODATA TOPO 5M 2004 is a national seamless data product aimed at regional or national applications. It is a vector representation of the Australian landscape as represented on the Geoscience Australia 5 million general reference map and is suitable for GIS applications. Offshore and sand ridge layers were sourced from scanning of the original 1:5 million map production material. The remaining nine layers were derived from the GEODATA TOPO 2.5M 2003 dataset. Free online. Available in ArcInfo Export, ArcView Shapefile and MapInfo mid/mif. Product Specifications: Themes: consists of eleven layers: built-up areas; contours; drainage; framework; localities; offshore; rail transport; road transport; sand ridges, spot heights and waterbodies Coverage: Australia Currency: 2004 Coordinates: Geographical Datum: GDA94, AHD Format: ArcInfo Export, ArcView Shapefile and MapInfo mid/mif Medium: Free online

1:10 Million - The GEODATA TOPO 10M 2002 version of this product has been completely revised, including the source information. The data is derived primarily from GEODATA TOPO 250K Series 1 data. In October 2003, the data was released in double precision coordinates. It provides a fundamental base layer of geographic information on which you can build a wide range of applications and is particularly suited to State-wide and national applications. The data consists of ten layers: built-up areas, contours, drainage, Spot heights, framework, localities, offshore, rail transport, road transport, and waterbodies. Coverage: Australia Currency: 2002 Coordinates: Geographical Datum: GDA94, AHD Format: ArcInfo Export, Arcview Shapefile and MapInfo mid/mif Medium: Free online

Dataset History

1:1Million - Vector data was produced by generalising Geoscience Australia's GEODATA TOPO 250K Series 1 data and updated using Series 2 data where available in January 2001. Raster data was sourced from USGS and updated using GEODATA 9 Second DEM Series 2, 1:5 million, Vegetation - Present (1988) and National Land and Water Resources data. However, updates have not been subjected to thorough vetting. A more detailed land use classification for Australia is available at www.nlwra.gov.au.

Full Metadata - http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_48006

1:2.5Million - Data for the Contours, Offshore, and Sand ridge layers was captured from 1:2.5 million scale mapping by scanning stable base photographic film positives of the original map production material. The key source material for Built-up areas, Drainage, Spot heights, Framework, Localities, Rail transport, Road transport and Waterbodies layers was GEODATA TOPO 2.5M 2003

Full Metadata - http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_60804

1:5Million - Offshore and Sand Ridge layers have been derived from 1:5M scale mapping by scanning stable base photographic film positives of the various layers of the original map production material. The remaining layers were sourced from the GEODATA TOPO 2.5M 2003 product.

Full Metadata - http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_61114

1:10Million - The key source for production of the Builtup Areas, Drainage, Framework, Localities, Rail Transport, Road Transport and Waterbodies layers was the GEODATA TOPO 250K Series 1 product. Some revision of the Builtup Areas, Road Transport, Rail Transport and Waterbodies layers was carried out using the latest available satelite imagery. The primary source for the Spot Heights, Contours and Offshore layers was the GEODATA TOPO 10M Version 1 product. A further element to the production of GEODATA TOPO 10M 2002 has been the datum shift from the Australian Geodetic Datum 1966 (AGD66) to the Geocentric Datum of Australia 1994 (GDA94).

Full Metadata - http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_60803

Dataset Citation

Geoscience Australia (2001) Geoscience Australia GEODATA TOPO series - 1:1 Million to 1:10 Million scale. Bioregional Assessment Source Dataset. Viewed 09 October 2018, http://data.bioregionalassessments.gov.au/dataset/310c5d07-5a56-4cf7-a5c8-63bdb001cd1a.