The Digital Geologic-GIS Map of Great Sand Dunes National Park, Colorado is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (grsa_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 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. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (grsa_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (grsa_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (grsa_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (grsa_geology_metadata_faq.pdf). Please read the grsa_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. 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). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). 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 (grsa_geology_metadata.txt or grsa_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 1:35,000 and United States National Map Accuracy Standards features are within (horizontally) 17.8 meters or 58.3 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 Pro, QGIS 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).
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In this course, you will explore a variety of open-source technologies for working with geosptial data, performing spatial analysis, and undertaking general data science. The first component of the class focuses on the use of QGIS and associated technologies (GDAL, PROJ, GRASS, SAGA, and Orfeo Toolbox). The second component of the class introduces Python and associated open-source libraries and modules (NumPy, Pandas, Matplotlib, Seaborn, GeoPandas, Rasterio, WhiteboxTools, and Scikit-Learn) used by geospatial scientists and data scientists. We also provide an introduction to Structured Query Language (SQL) for performing table and spatial queries. This course is designed for individuals that have a background in GIS, such as working in the ArcGIS environment, but no prior experience using open-source software and/or coding. You will be asked to work through a series of lecture modules and videos broken into several topic areas, as outlined below. Fourteen assignments and the required data have been provided as hands-on opportunites to work with data and the discussed technologies and methods. If you have any questions or suggestions, feel free to contact us. We hope to continue to update and improve this course. This course was produced by West Virginia View (http://www.wvview.org/) with support from AmericaView (https://americaview.org/). This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G18AP00077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey. After completing this course you will be able to: apply QGIS to visualize, query, and analyze vector and raster spatial data. use available resources to further expand your knowledge of open-source technologies. describe and use a variety of open data formats. code in Python at an intermediate-level. read, summarize, visualize, and analyze data using open Python libraries. create spatial predictive models using Python and associated libraries. use SQL to perform table and spatial queries at an intermediate-level.
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Learn state-of-the-art skills to build compelling, useful, and fun Web GIS apps easily, with no programming experience required.Building on the foundation of the previous three editions, Getting to Know Web GIS, fourth edition,features the latest advances in Esri’s entire Web GIS platform, from the cloud server side to the client side.Discover and apply what’s new in ArcGIS Online, ArcGIS Enterprise, Map Viewer, Esri StoryMaps, Web AppBuilder, ArcGIS Survey123, and more.Learn about recent Web GIS products such as ArcGIS Experience Builder, ArcGIS Indoors, and ArcGIS QuickCapture. Understand updates in mobile GIS such as ArcGIS Collector and AuGeo, and then build your own web apps.Further your knowledge and skills with detailed sections and chapters on ArcGIS Dashboards, ArcGIS Analytics for the Internet of Things, online spatial analysis, image services, 3D web scenes, ArcGIS API for JavaScript, and best practices in Web GIS.Each chapter is written for immediate productivity with a good balance of principles and hands-on exercises and includes:A conceptual discussion section to give you the big picture and principles,A detailed tutorial section with step-by-step instructions,A Q/A section to answer common questions,An assignment section to reinforce your comprehension, andA list of resources with more information.Ideal for classroom lab work and on-the-job training for GIS students, instructors, GIS analysts, managers, web developers, and other professionals, Getting to Know Web GIS, fourth edition, uses a holistic approach to systematically teach the breadth of the Esri Geospatial Cloud.AUDIENCEProfessional and scholarly. College/higher education. General/trade.AUTHOR BIOPinde Fu leads the ArcGIS Platform Engineering team at Esri Professional Services and teaches at universities including Harvard University Extension School. His specialties include web and mobile GIS technologies and applications in various industries. Several of his projects have won specialachievement awards. Fu is the lead author of Web GIS: Principles and Applications (Esri Press, 2010).Pub Date: Print: 7/21/2020 Digital: 6/16/2020 Format: Trade paperISBN: Print: 9781589485921 Digital: 9781589485938 Trim: 7.5 x 9 in.Price: Print: $94.99 USD Digital: $94.99 USD Pages: 490TABLE OF CONTENTSPrefaceForeword1 Get started with Web GIS2 Hosted feature layers and storytelling with GIS3 Web AppBuilder for ArcGIS and ArcGIS Experience Builder4 Mobile GIS5 Tile layers and on-premises Web GIS6 Spatial temporal data and real-time GIS7 3D web scenes8 Spatial analysis and geoprocessing9 Image service and online raster analysis10 Web GIS programming with ArcGIS API for JavaScriptPinde Fu | Interview with Esri Press | 2020-07-10 | 15:56 | Link.
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This is a raster-based suitability map of landfill sites produced after the February 6, 2023, Türkiye earthquakes centred on Kahramanmaraş - Pazarcık and Kahramanmaraş - Elbistan. In this study, a site selection model was developed using open-source Geographic Information Systems (GIS) software and the Best-Worst Method (BWM), one of the Multi-Criteria Decision-Making Methods, to determine the most suitable landfill areas immediately after the earthquake.The suitability map of the landfill sites can be accessed through the Serverless Cloud-GIS based Disaster Management Portal at https://web.itu.edu.tr/metemu/nominal/deprem.htmlThe pairwise comparison matrix, weight calculation, and sensitivity analysis are also provided in the MS Excel file.
ArcGIS Location Tracking Privacy Best Practices (Esri Whitepaper).This document contains relevant information that helps guide IT managers, GIS administrators, andprivacy and security team members in deploying cloud and enterprise GIS in a manner that helps complywith privacy regulations, such as GDPR, for location tracking services._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...
This layer shows the Best Management Practices for water pollution control located on West Chester University's campus. | Publication Date: April 2018, Last Updated: April 2018 | West Chester University’s Geography and Planning department upholds its mission to provide spatial analysis expertise in order to solve many problems regarding spatial applications that facilitates research, sustainability goals, planning and communal integration.This dataset was curated by West Chester University’s Department of Geography and Planning and presented using West Chester University's Open GIS Data.
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This dataset holds all materials for the Inform E-learning GIS course
Two dashboards, one intelligent URL (ArcGIS Blog). Half of website traffic is generated by mobile devices and half by desktops. Does your dashboard look good on both?_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...
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The global Geographic Information System (GIS) Software market size was valued at approximately USD 7.8 billion in 2023 and is projected to reach USD 15.6 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.3% during the forecast period. This impressive growth can be attributed to the increasing demand for efficient data management tools across various industries, which rely on spatial data for decision-making and strategic planning. The rapid advancements in technology, such as the integration of AI and IoT with GIS software, have further propelled the market, enabling organizations to harness the full potential of geographic data in innovative ways.
One of the primary growth drivers of the GIS Software market is the burgeoning need for urban planning and smart city initiatives worldwide. As urbanization trends escalate, cities are increasingly relying on GIS technology to manage resources more effectively, optimize transportation networks, and enhance public safety. The ability of GIS software to provide real-time data and spatial analysis is vital for city planners and administrators faced with the challenges of modern urban environments. Furthermore, the trend towards digital transformation in governmental organizations is boosting the adoption of GIS solutions, as they seek to improve operational efficiency and service delivery.
The agricultural sector is also experiencing significant transformations due to the integration of GIS software, which is another pivotal growth factor for the market. Precision agriculture, which involves the use of GIS technologies to monitor and manage farming practices, is enabling farmers to increase crop yields while reducing resource consumption. By leveraging spatial data, farmers can make informed decisions about planting, irrigation, and harvesting, ultimately leading to more sustainable agricultural practices. This trend is particularly prominent in regions where agriculture forms a substantial portion of the economy, encouraging the adoption of advanced GIS tools to maintain competitive advantage.
Another influential factor contributing to the growth of the GIS Software market is the increasing importance of environmental management and disaster response. GIS technology plays a crucial role in assessing environmental changes, managing natural resources, and planning responses to natural disasters. The ability to overlay various data sets onto geographic maps allows for better analysis and understanding of environmental phenomena, making GIS indispensable in tackling issues such as climate change and resource depletion. Moreover, governments and organizations are investing heavily in GIS tools that aid in disaster preparedness and response, ensuring timely and effective action during emergencies.
The evolution of GIS Mapping Software has been instrumental in transforming how spatial data is utilized across various sectors. These software solutions offer robust tools for visualizing, analyzing, and interpreting geographic data, enabling users to make informed decisions based on spatial insights. With the ability to integrate multiple data sources, GIS Mapping Software provides a comprehensive platform for conducting spatial analysis, which is crucial for applications ranging from urban planning to environmental management. As technology continues to advance, the capabilities of GIS Mapping Software are expanding, offering more sophisticated features such as 3D visualization and real-time data processing. These advancements are not only enhancing the utility of GIS tools but also making them more accessible to a wider range of users, thereby driving their adoption across different industries.
Regionally, North America and Europe have traditionally dominated the GIS Software market, thanks to their robust technological infrastructure and higher adoption rates of advanced technologies. However, Asia Pacific is expected to witness the highest growth rate during the forecast period, driven by rapid urbanization, increased government spending on infrastructure development, and the expanding telecommunications sector. The growing awareness and adoption of GIS solutions in countries like China and India are significant contributors to this regional growth. Furthermore, Latin America and the Middle East & Africa regions are slowly catching up, with ongoing investments in smart city projects and infrastructure development driving the demand for GIS software.
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The Geographic Information System (GIS) software market is experiencing a significant transformation, underpinned by rapid technological advancements and a growing demand for location-based analytics across diverse industries. As of now, the global GIS software market is valued at approximately $4 billion, reflectin
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This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups include: new/revised datasets (paleo-geothermal features, geochemistry, geophysics, heat flow, slip and dilation, potential structures, geothermal power plants, positive and negative test sites), machine learning model input grids, machine learning models (Artificial Neural Network (ANN), Extreme Learning Machine (ELM), Bayesian Neural Network (BNN), Principal Component Analysis (PCA/PCAk), Non-negative Matrix Factorization (NMF/NMFk) - supervised and unsupervised), original NV Play Fairway data and models, and NV cultural/reference data.
See layer descriptions for additional metadata. Smaller GIS resource packages (by category) can be found in the related datasets section of this submission. A submission linking the full codebase for generating machine learning output models is available through the "Related Datasets" link on this page, and contains results beyond the top picks present in this compilation.
The Digital Geologic-GIS Map of Great Basin National Park and Vicinity, Nevada is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (grba_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 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. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (grba_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (grba_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (grba_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (grba_geology_metadata_faq.pdf). Please read the grba_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. 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). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Stanford University and the Stanford 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 (grba_geology_metadata.txt or grba_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 Pro, QGIS 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).
Essential configurations for highly scalable ArcGIS Online web apps (ArcGIS Blog).Learn best practices for configuring web applications that receive a high amount of web traffic, use a quick checklist focus on critical settings._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...
Dataset containing all nine metrics for the Utility Management program Best Practice Scores, including data collected by Rural Utility Business Advisor (RUBA).These scores are collected in collaboration with the Department of Environmental Conservation twice a year. Data collection started in 2016 and is currently on-going. Best Practice scores help to determine funding for water utility projects.
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Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.
The Digital Geomorphic-GIS Map of the Great Swash to Quork Hammock Area (1:10,000 scale 2006 mapping), North Carolina is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (gsqh_geomorphology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (gsqh_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (gsqh_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (caha_fora_wrbr_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (caha_fora_wrbr_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (gsqh_geomorphology_metadata_faq.pdf). Please read the caha_fora_wrbr_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. 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). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: East Carolina University. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (gsqh_geomorphology_metadata.txt or gsqh_geomorphology_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 1:10,000 and United States National Map Accuracy Standards features are within (horizontally) 8.5 meters or 27.8 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 ArcGIS, QGIS 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 NG9-1-1 GIS Guidelines and Best Practices Manual is a cooperative effort between the Arizona 9-1-1 Program, the AGIC 9-1-1 Committee and the Arizona 9-1-1 Program for the 9-1-1 System Administrators and GIS practitioners at different levels such as local government, tribal, County government, metropolitan planning organizations (MPO), whom support any of the 9-1-1 systems.Community. Initial Document created in 2017, Version 2 updated in 2020 based on new NENA standards and GIS platforms in Arizona.
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Excel files include the raw database and the processed data that led to the quadrat analyses. The "Matrix_raw data" file includes the raw data as downloaded from the server. This data was cleaned and organized for its posterior use. "Quadrat analyzes "file includes all the quadrat analyses resulting in each research question in the paper except question four. Question 4 can be seen in the file "Water analysis_Blaarmeersen." All excel files come with a "CODE" tab that describes each of the codes used, their meaning, and ways that were calculated where necessary. Two zip files include all the GIS files. The first one includes the GIS files from which "Matrix_raw data" was built from. The second folder includes the resulting maps from the quadrat analyses. In order to visualize them as in the paper, configure the symbology tab at the GIS software in quantile and the categories number, as shown in the paper. The production of the files in the "GIS_Processed data" folder was done via a repetitive line of commands in ArcGIS pro. The same process was followed for each one of the quadrat analysis described in the paper. Refer to "Reproduction commands and parameters.pdf" for further information.
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This GIS dataset shows where Geoscience Australia (GA) has acquired regional seismic reflection data as a part of Australian Government's Onshore Energy Security Program (OESP) in collaboration with State and Territory geological surveys, AuScope and Australian National Seismic Imaging Resource (ANSIR). During 2006-2011 GA collected over 6,500 line kilometres of new world-class seismic reflection data within Australia for use by industry and government. This dataset is generated from files containing CDP (Common Depth Point) coordinates of all OESP seismic surveys. The CDP line is a curve of best fit through the midpoints between sources and receivers, which optimises the fold of the data while minimising the subsurface area of reflections contributing to each nominal CDP. Each trace (source-receiver pair) is allocated to the nearest CDP bin to its midpoint. The interval between each CDP traces is 20 metres.
Links to recordings of the Integrated Services Program and 9-1-1 & Geospatial Services Bureau webinar series, including NG9-1-1 GIS topics such as: data preparation; data provisioning and maintenance; boundary best practices; and extract, transform, and load (ETL). Offerings include:Topic: Virginia Next Generation 9-1-1 Dashboard and Resources Update Description: Virginia recently updated the NG9-1-1 Dashboard with some new tabs and information sources and continues to develop new resources to assist the GIS data work. This webinar provides an overview of changes, a demonstration of new functionality, and a guide to finding and using new resources that will benefit Virginia public safety and GIS personnel with roles in their NG9-1-1 projects. Wednesday 16 June 2021. Recording available at: https://vimeo.com/566133775Topic: Emergency Service Boundary GIS Data Layers and Functions in your NG9-1-1 PSAP Description: Law, Fire, and Emergency Medical Service (EMS) Emergency Service Boundary (ESB) polygons are required elements of the NENA NG9-1-1 GIS data model stack that indicate which agency is responsible for primary response. While this requirement must be met in your Virginia NG9-1-1 deployment with AT&T and Intrado, there are quite a few ways you could choose to implement these polygons. PSAPs and their GIS support must work together to understand how this information will come into a NG9-1-1 i3 PSAP and how it will replace traditional ESN information in order to make good choices while implementing these layers. This webinar discusses:the function of ESNs in your legacy 9-1-1 environment, the role of ESBs in NG9-1-1, and how ESB information appears in your NG9-1-1 PSAP. Wednesday, 22 July 2020. Recording available at: https://vimeo.com/441073056#t=360sTopic: "The GIS Folks Handle That": What PSAP Professionals Need to Know about the GIS Project Phase of Next Generation 9-1-1 DeploymentDescription: Next Generation 9-1-1 (NG9-1-1) brings together the worlds of emergency communication and spatial data and mapping. While it may be tempting for PSAPs to outsource cares and concerns about road centerlines and GIS data provisioning to 'the GIS folks', GIS staff are crucial to the future of emergency call routing and location validation. Data required by NG9-1-1 usually builds on data that GIS staff already know and use for other purposes, so the transition requires them to learn more about PSAP operations and uses of core data. The goal of this webinar is to help the PSAP and GIS worlds come together by explaining the role of the GIS Project in the Virginia NG9-1-1 Deployment Steps, exploring how GIS professionals view NG9-1-1 deployment as a project, and fostering a mutual understanding of how GIS will drive NG9-1-1. 29 January 2020. Recording available at: https://vimeo.com/showcase/9791882/video/761225474Topic: Getting Your GIS Data from Here to There: Processes and Best Practices for Extract, Transform and Load (ETL) Description: During the fall of 2019, VITA-ISP staff delivered workshops on "Tools and Techniques for Managing the Growing Role of GIS in Enterprise Software." This session presents information from the workshops related to the process of extracting, transforming, and loading data (ETL), best practices for ETL, and methods for data schema comparison and field mapping as a webinar. These techniques and skills assist GIS staff with their growing role in Next Generation 9-1-1 but also apply to many other projects involving the integration and maintenance of GIS data. 19 February 2020. Recording available at: https://vimeo.com/showcase/9791882/video/761225007Topic: NG9-1-1 GIS Data Provisioning and MaintenanceDescription: VITA ISP pleased to announce an upcoming webinar about the NG9-1-1 GIS Data Provisioning and Maintenance document provided by Judy Doldorf, GISP with the Fairfax County Department of Information Technology and RAC member. This document was developed by members of the NG9-1-1 GIS workgroup within the VITA Regional Advisory Council (RAC) and is intended to provide guidance to local GIS and PSAP authorities on the GIS datasets and associated GIS to MSAG/ALI validation and synchronization required for NG9-1-1 services. The document also provides guidance on geospatial call routing readiness and the short- and long-term GIS data maintenance workflow procedures. In addition, some perspective and insight from the Fairfax County experience in GIS data preparation for the AT&T and West solution will be discussed in this webinar. 31 July 2019. Recording available at: https://vimeo.com/showcase/9791882/video/761224774Topic: NG9-1-1 Deployment DashboardDescription: I invite you to join us for a webinar that will provide an overview of our NG9-1-1 Deployment Dashboard and information about other online ISP resources. The ISP website has been long criticized for being difficult to use and find information. The addition of the Dashboard and other changes to the website are our attempt to address some of these concerns and provide an easier way to find information especially as we undertake NG9-1-1 deployment. The Dashboard includes a status map of all Virginia PSAPs as it relates to the deployment of NG9-1-1, including the total amount of funding requested by the localities and awards approved by the 9-1-1 Services Board. During this webinar, Lyle Hornbaker, Regional Coordinator for Region 5, will navigate through the dashboard and provide tips on how to more effectively utilize the ISP website. 12 June 2019. Recording not currently available. Please see the Virginia Next Generation 9-1-1 Dashboard and Resources Update webinar recording from 16 June 2021. Topic: PSAP Boundary Development Tools and Process RecommendationDescription: This webinar will be presented by Geospatial Program Manager Matt Gerike and VGIN Coordinator Joe Sewash. With the release of the PSAP boundary development tools and PSAP boundary segment compilation guidelines on the VGIN Clearinghouse in March, this webinar demonstrates the development tools, explains the process model, and discusses methods, tools, and resources available for you as you work to complete PSAP boundary segments with your neighbors. 15 May 2019. Recording available at: https://www.youtube.com/watch?v=kI-1DkUQF9Q&feature=youtu.beTopic: NG9-1-1 Data Preparation - Utilizing VITA's GIS Data Report Card ToolDescription: This webinar, presented by VGIN Coordinator Joe Sewash, Geospatial Program Manager Matt Gerike, and Geospatial Analyst Kenny Brevard will provide an overview of the first version of the tools that were released on March 25, 2019. These tools will allow localities to validate their GIS data against the report card rules, the MSAG and ALI checks used in previous report cards, and the analysis listed in the NG9-1-1 migration proposal document. We will also discuss the purpose of the tools, input requirements, initial configuration, how to run them, and how to make sense of your results. 10 April 2019. Recording available at: https://vimeo.com/showcase/9791882/video/761224495Topic: NG9-1-1 PSAP Boundary Best Practice WebinarDescription: During the months of November and December, VITA ISP staff hosted regional training sessions about best practices for PSAP boundaries as they relate to NG9-1-1. These sessions were well attended and very interactive, therefore we feel the need to do a recap and allow those that may have missed the training to attend a makeup session. 30 January 2019. Recording not currently available. Please see the PSAP Boundary Development Tools and Process Recommendation webinar recording from 15 May 2019.Topic: NG9-1-1 GIS Overview for ContractorsDescription: The Commonwealth of Virginia has started its migration to next generation 9-1-1 (NG9-1-1). This migration means that there will be a much greater reliance on geographic information (GIS) to locate and route 9-1-1 calls. VITA ISP has conducted an assessment of current local GIS data and provided each locality with a report. Some of the data from this report has also been included in the localities migration proposal, which identifies what data issues need to be resolved before the locality can migrate to NG9-1-1. Several localities in Virginia utilize a contractor to maintain their GIS data. This webinar is intended for those contractors to review the data in the report, what is included in the migration proposal and how they may be called on to assist the localities they serve. It will still ultimately be up to each locality to determine whether they engage a contractor for assistance, but it is important for the contractor community to understand what is happening and have an opportunity to ask questions about the intent and goals. This webinar will provide such an opportunity. 22 August 2018. Recording not currently available. Please contact us at NG911GIS@vdem.virginia.gov if you are interested in this content.
The Digital Geologic-GIS Map of Great Sand Dunes National Park, Colorado is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (grsa_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 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. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (grsa_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (grsa_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (grsa_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (grsa_geology_metadata_faq.pdf). Please read the grsa_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. 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). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). 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 (grsa_geology_metadata.txt or grsa_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 1:35,000 and United States National Map Accuracy Standards features are within (horizontally) 17.8 meters or 58.3 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 Pro, QGIS 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).