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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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TwitterThrough the Department of the Interior-Bureau of Indian Affairs Enterprise License Agreement (DOI-BIA ELA) program, BIA employees and employees of federally-recognized Tribes may access a variety of geographic information systems (GIS) online courses and instructor-led training events throughout the year at no cost to them. These online GIS courses and instructor-led training events are hosted by the Branch of Geospatial Support (BOGS) or offered by BOGS in partnership with other organizations and federal agencies. Online courses are self-paced and available year-round, while instructor-led training events have limited capacity and require registration and attendance on specific dates. This dataset does not any training where the course was not completed by the participant or where training was cancelled or otherwise not able to be completed. Point locations depict BIA Office locations or Tribal Office Headquarters. For completed trainings where a participant location was not provided a point locations may not be available. For more information on the Branch of Geospatial Support Geospatial training program, please visit:https://www.bia.gov/service/geospatial-training.
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This dataset holds all materials for the Inform E-learning GIS course
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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.
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TwitterThe Civil Engineering Students Society organized an 'ArcGIS Online Training for Beginners.' Geographical Information System (GIS) technology provides the tools for creating, managing, analyzing, and visualizing data associated with developing and managing infrastructure.
It also allowed civil engineers to manage and share data, turning it into easily understood reports and visualizations that could be analyzed and communicated to others. Additionally, it helped civil engineers in spatial analysis, data management, urban development, town planning, and site analysis.
It is equally important for beginner geospatial students.
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TwitterAbstract: Community Engaged Learning (CEL) is a pedagogical approach that involves students, community partners, and instructors working together to analyze and address community-identified concerns through experiential learning. Implementing community-engagement in geography courses and, specifically, in GIS courses is not new. However, while students enrolled in CEL GIS courses critically reflect on social and spatial inequalities, GIS tools themselves are mostly applied in uncritical ways. Yet, CEL GIS courses can specifically help students understand GIS as a socially constructed technology which can not only empower but also disempower the community. This contribution presents the experiences from a community-engaged introductory GIS course, taught at a Predominantly White Institution (PWI) in Virginia (USA) in Spring ’24. It shows how the course helped students gain a conceptual understanding of what is GIS, how to use it, and valuable software skills, while also reflecting about their own privileges, how GIS can (dis)empower the community, and their own role as a GIS analyst. Ultimately, the paper shows how the course supported positive changes in the community, equity in education, reciprocity in university/community relationships, and student civic-mindedness.
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TwitterThe Pennsylvania Department of Education approves nurse aide training programs in Pennsylvania. These programs must be at least 80 hours in length and include at least 37.5 hours of clinical practice. Student/graduate nurses may also be authorized to test as CNAs. Previously these programs were provided to the public through a pdf available on the website. The Nurse Aide Training Programs GIS application allows prospective students and constituents to search for programs by Class Type (Nursing Facility (NF), Educational Entity (ED)), County, or within a location or area of interest. Searches can be exported to easily share the programs resulting from an inquiry. The selection of a program location allows users to see all associated information such as address, contact information, and even click open driving directions to the location.
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In this course, you will explore the concepts, principles, and practices of acquiring, storing, analyzing, displaying, and using geospatial data. Additionally, you will investigate the science behind geographic information systems and the techniques and methods GIS scientists and professionals use to answer questions with a spatial component. In the lab section, you will become proficient with the ArcGIS Pro software package. This course will prepare you to take more advanced geospatial science courses. You will be asked to work through a series of modules that present information relating to a specific topic. You will also complete a series of lab exercises, assignments, and less guided challenges. Please see the sequencing document for our suggestions as to the order in which to work through the material. To aid in working through the lecture modules, we have provided PDF versions of the lectures with the slide notes included. This course makes use of the ArcGIS Pro software package from the Environmental Systems Research Institute (ESRI), and directions for installing the software have also been provided. If you are not a West Virginia University student, you can still complete the labs, but you will need to obtain access to the software on your own.
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Dataset contains training material on using open source Geographic Information Systems (GIS) to improve protected area planning and management from a workshop that was conducted on October 19-23, 2020. Specifically, the dataset contains lectures on GIS fundamentals, QGIS 3.x, and global positioning system (GPS), as well as country-specific datasets and a workbook containing exercises for viewing data, editing/creating datasets, and creating map products in QGIS. Supplemental videos that narrate a step-by-step recap and overview of these processes are found in the Related Content section of this dataset.
Funding for this workshop and material was funded by the Biodiversity and Protected Areas Management (BIOPAMA) programme. The BIOPAMA programme is an initiative of the Organisation of African, Caribbean and Pacific (ACP) Group of States financed by the European Union's 11th European Development Fund. BIOPAMA is jointly implemented by the International Union for Conservation of Nature {IUCN) and the Joint Research Centre of the European Commission (EC-JRC). In the Pacific region, BIOPAMA is implemented by IUCN's Oceania Regional Office (IUCN ORO) in partnership with the Secretariat of the Pacific Regional Environment Programme (SPREP). The overall objective of the BIOPAMA programme is to contribute to improving the long-term conservation and sustainable use of biodiversity and natural resources in the Pacific ACP region in protected areas and surrounding communities through better use and monitoring of information and capacity development on management and governance.
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TwitterSeattle Parks and Recreation Golf Course locations. SPR Golf Courses are managed by contractors.Refresh Cycle: WeeklyFeature Class: DPR.GolfCourse
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The Geographic Information System (GIS) Solutions market is experiencing robust growth, driven by increasing adoption across diverse sectors. The market, estimated at $15 billion in 2025, is projected to expand significantly over the forecast period (2025-2033), fueled by a Compound Annual Growth Rate (CAGR) of approximately 8%. This growth is attributed to several key factors. Firstly, the rising need for precise spatial data analysis and visualization across industries like agriculture (precision farming), oil & gas (resource exploration and management), and construction (infrastructure planning and development) is driving demand. Secondly, advancements in GIS software and services, including cloud-based solutions and AI-powered analytics, are enhancing efficiency and accessibility. Thirdly, government initiatives promoting smart cities and infrastructure development are further boosting market expansion. The market is segmented by application (Agriculture, Oil & Gas, AEC, Transportation, Mining, Government, Healthcare, Others) and type (Software, Services), with software solutions currently holding a larger market share due to increasing digitization and data-driven decision-making. North America and Europe are currently the leading regional markets, benefiting from established infrastructure and high technology adoption rates, but Asia-Pacific is poised for significant growth driven by rapid urbanization and infrastructure development. Despite the promising growth trajectory, certain challenges remain. High initial investment costs for GIS software and implementation can be a barrier to entry for smaller businesses. Furthermore, the need for skilled professionals to effectively utilize and manage GIS data poses a considerable constraint. However, the ongoing development of user-friendly interfaces and accessible training programs is mitigating this issue. The competitive landscape is characterized by a mix of established players like ESRI, Hexagon, and Pitney Bowes, alongside emerging technology providers. These companies are actively investing in R&D and strategic partnerships to maintain their competitive edge and capitalize on the market's expansion. The long-term outlook for the GIS solutions market remains positive, with continuous innovation and expanding applications across various sectors paving the way for sustained growth throughout the forecast period.
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TwitterSeattle Parks and Recreation ARCGIS park feature map layer web services are hosted on Seattle Public Utilities' ARCGIS server. This web services URL provides a live read only data connection to the Seattle Parks and Recreations Golf Courses dataset.
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Phoenix Golf Features:
Five 18-hole championship courses
Three 9-hole courses
Conveniently located throughout the city
Overseeded annually for optimum playing conditions
Full-service golf shops and restaurants
Full amenity practice facilities
Equipment rentals
PGA/LPGA professional course managers
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TwitterOur Certification & Restoration Program currently licenses water and wastewater treatment plant operators as well as water distribution plants throughout Florida. Obtaining one of these licenses is a prerequisite to obtaining employment as a plant operator, excluding owner-operators.See Metadata for contact information.
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TwitterThe dataset contains locations and attributes of Golf Courses, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies.
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TwitterPublic Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
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Dataset contains training material on using open source Geographic Information Systems (GIS) to improve protected area planning and management from workshops that were conducted on February 19-21 and October 6-7, 2020. Specifically, the dataset contains lectures on GIS fundamentals, QGIS 3.x, and global positioning system (GPS), as well as country-specific datasets and a workbook containing exercises for viewing data, editing/creating datasets, and creating map products in QGIS. Supplemental videos that narrate a step-by-step recap and overview of these processes are found in the Related Content section of this dataset.
Funding for this workshop and material was funded by the Biodiversity and Protected Areas Management (BIOPAMA) programme. The BIOPAMA programme is an initiative of the Organisation of African, Caribbean and Pacific (ACP) Group of States financed by the European Union's 11th European Development Fund. BIOPAMA is jointly implemented by the International Union for Conservation of Nature {IUCN) and the Joint Research Centre of the European Commission (EC-JRC). In the Pacific region, BIOPAMA is implemented by IUCN's Oceania Regional Office (IUCN ORO) in partnership with the Secretariat of the Pacific Regional Environment Programme (SPREP). The overall objective of the BIOPAMA programme is to contribute to improving the long-term conservation and sustainable use of biodiversity and natural resources in the Pacific ACP region in protected areas and surrounding communities through better use and monitoring of information and capacity development on management and governance.
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Dataset contains training material on using open source Geographic Information Systems (GIS) to improve protected area planning and management from a workshop that was conducted on August 17-21, 2020. Specifically, the dataset contains lectures on GIS fundamentals, QGIS 3.x, and global positioning system (GPS), as well as country-specific datasets and a workbook containing exercises for viewing data, editing/creating datasets, and creating map products in QGIS. Supplemental videos that narrate a step-by-step recap and overview of these processes are found in the Related Content section of this dataset.
Funding for this workshop and material was funded by the Biodiversity and Protected Areas Management (BIOPAMA) programme. The BIOPAMA programme is an initiative of the Organisation of African, Caribbean and Pacific (ACP) Group of States financed by the European Union's 11th European Development Fund. BIOPAMA is jointly implemented by the International Union for Conservation of Nature {IUCN) and the Joint Research Centre of the European Commission (EC-JRC). In the Pacific region, BIOPAMA is implemented by IUCN's Oceania Regional Office (IUCN ORO) in partnership with the Secretariat of the Pacific Regional Environment Programme (SPREP). The overall objective of the BIOPAMA programme is to contribute to improving the long-term conservation and sustainable use of biodiversity and natural resources in the Pacific ACP region in protected areas and surrounding communities through better use and monitoring of information and capacity development on management and governance.
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Climate data and geographic data from Madagascar for learning multi-criteria analysis in GIS courses.
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TwitterThe City of Galveston participated in GeoWeek. This is a week long event to bring Geographic and GIS awareness. The City of Galveston presented How the City of Galveston Uses GIS. The City participated in and presented to Texas A&M - Galveston and the City of Seabrook's GIS Day events.This event provided an opportunity for the City of Galveston to share its GIS history, why we use an enterprise system, ways our departments use GIS to assist in their workflows, our future projects, and a call to action. During the City of Galveston's GIS Day event, in addition to How the City of Galveston Uses GIS, the GIS Training Program: A Highlight Reel was presented. This training program has been in development since 2018 and will provide City Staff the ability to learn, or continue learning, GIS tools and workflows to assist them in their daily work.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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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.