This course is intended to get you thinking about your future. Learn about where GIS professionals work, what they do, and how their educational choices prepare them for different types of jobs.GoalsDiscover the types of projects that GIS professionals work on.Identify qualities and skills that can help you get a GIS-related job.Choose educational options that match your goals and support your future career plans.

This dataset maps the competences of the European Digital Competence Framework (DigComp) to the skills descriptors in ESCO, the European classification of skills, qualifications and occupations, which is the target classification used in Skills-OVATE, a database of European online job advertisements (OJA). This experimental mapping allows to reconcile the “demand side” of digital skills sought by employers with the “supply side” of education and training for digital skills, through the lens of DigComp, which is used in many EU digital skills initiatives at international, national and regional levels.

Covered employment for the growth areas, urban centers and villages, for the City of Seattle Comprehensive Plan. This is a stand alone table that includes non-spatial records.Covered employment is reported annually from the State of Washington QCEW data.The Washington State Employment Security Department, Quarterly Census of Employment and Wages (QCEW) is a federal/state cooperative program that measures employment and wages in industries covered by unemployment insurance. Data are available by industry and county and used to evaluate labor trends, monitor major industry developments and develop training programs.

An ArcGIS Dashboard used in the ArcGIS Hub site, GIS Service Center, to share information with the organization.

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.

PurposeThis job aid will lead the GIS analyst through the process of manually creating an incident map journal and how to create additional pages for the journal. This process should be used at the beginning of an incident and then the journal should be maintained to assure it remains viable. The incident map journal serves as a curated center to place maps, apps, and dashboards relevant to the incident.

This job aid assumes a working knowledge of how to create maps, apps, and dashboards on ArcGIS Online. For a tutorial, go to the Create apps from maps - ArcGIS Tutorial.Example workflow for the Geo-Enabled Plans Session at InSPIRE. Job Aid developed by FEMA GIS to enable GIS analysts to rapidly spin-up a standardized incident journal.

This layer shows workers' place of residence by mode of commute. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized by the percentage of workers who drove alone. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B08301 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

The published representation of camera jobs (video viewing of tile lines) done throughout Renville County. Organized for consumption in desktop and web applications.

Table from the American Community Survey (ACS) 5-year series on poverty and employment status related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B23025 Employment Status for the Population 16 years and over, B23024 Poverty Status by Disability Status by Employment Status for the Population 20 to 64 years, B17010 Poverty Status of Families by Family Type by Presence of Related Children under 18 years, C17002 Ratio of Income to Poverty Level in the Past 12 Months. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B23025, B23024, B17010, C17002Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.<d

A special tabulation of employment data by the Puget Sound Regional Council for monitoring employment goals in the City of Seattle 2035 Comprehensive Plan. Estimates are for the growth areas, urban centers and villages of the City of Seattle Comprehensive Plan.The comprehensive planning estimates are for "all jobs" minus the employment in the Construction/Resources sector. Employment reporting for the purposes of comparison to 2035 growth estimates are calculated as the covered employment reported from the Washington State Employment Security Department QCEW data plus an estimate of the remaining jobs not covered by unemployment insurance minus jobs in the construction / resources sector.This is a stand alone table that includes non-spatial records.

This Innovative Technology Experiences for Students and Teachers (ITEST) project has developed, implemented, and evaluated a series of innovative Socio-Environmental Science Investigations (SESI) using a geospatial curriculum approach. It is targeted for economically disadvantaged 9th grade high school students in Allentown, PA, and involves hands-on geospatial technology to help develop STEM-related skills. SESI focuses on societal issues related to environmental science. These issues are multi-disciplinary, involve decision-making that is based on the analysis of merged scientific and sociological data, and have direct implications for the social agency and equity milieu faced by these and other school students. This project employed a design partnership between Lehigh University natural science, social science, and education professors, high school science and social studies teachers, and STEM professionals in the local community to develop geospatial investigations with Web-based Geographic Information Systems (GIS). These were designed to provide students with geospatial skills, career awareness, and motivation to pursue appropriate education pathways for STEM-related occupations, in addition to building a more geographically and scientifically literate citizenry. The learning activities provide opportunities for students to collaborate, seek evidence, problem-solve, master technology, develop geospatial thinking and reasoning skills, and practice communication skills that are essential for the STEM workplace and beyond. Despite the accelerating growth in geospatial industries and congruence across STEM, few school-based programs integrate geospatial technology within their curricula, and even fewer are designed to promote interest and aspiration in the STEM-related occupations that will maintain American prominence in science and technology. The SESI project is based on a transformative curriculum approach for geospatial learning using Web GIS to develop STEM-related skills and promote STEM-related career interest in students who are traditionally underrepresented in STEM-related fields. This project attends to a significant challenge in STEM education: the recognized deficiency in quality locally-based and relevant high school curriculum for under-represented students that focuses on local social issues related to the environment. Environmental issues have great societal relevance, and because many environmental problems have a disproportionate impact on underrepresented and disadvantaged groups, they provide a compelling subject of study for students from these groups in developing STEM-related skills. Once piloted in the relatively challenging environment of an urban school with many unengaged learners, the results will be readily transferable to any school district to enhance geospatial reasoning skills nationally.

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.

This submission includes publicly available data extracted in its original form. If you have questions about the underlying data stored here, please contact Thomas John (thomas.john@epa.gov)/EPA Office of Sustainable Communities. If you have questions or recommendations related to this metadata entry and extracted data, please contact the CAFE Data Management team at: climatecafe@bu.edu. "The Access to Jobs and Workers Via Transit tool is a free geospatial data resource and web mapping tool for comparing the accessibility of neighborhoods via public transit service. Its indicators summarize accessibility to jobs as well as accessibility by workers, households, and population. Coverage is limited to metropolitan regions served by transit agencies that share their service data in a standard format called GTFS . A collection of performance indicators and regional benchmarks for consistently comparing neighborhoods (census block groups) across the US in regards to their accessibility to jobs or workers via public transit service. Accessibility was modeled by calculating total travel time between block group centroids inclusive of walking to/from transit stops, wait times, and transfers. Block groups that can be accessed in 45 minutes or less from the origin block group are considered accessible. Indicators reflect public transit service in December 2012 and employment/worker counts in 2010. Coverage is limited to census block groups within metropolitan regions served by transit agencies who share their service data in a standardized format called GTFS." Quote from https://catalog.data.gov/dataset/access-to-jobs-and-workers-via-transit-download7 and https://www.epa.gov/smartgrowth/smart-location-mapping

Learn the basics of GIS. Work with ArcGIS Online to interact with GIS maps, explore real world problems, and tell a story. Find out how workers use GIS and what it takes to become a GIS professional.

Employment Protection Districts are economically viable industrial and employment-rich areas, having policies that prevent the conversion of industrial land to non-industrial uses. These are for areas in UNINCORPORATED Los Angeles County only.Please see Figure 14.1 and the the Economic Development Element of the Los Angeles County General Plan 2035 for more information. https://planning.lacounty.gov/generalplan/Source: L.A. County Dept. of Regional Planning (DRP) GIS Section; created November 5, 2015.NEED MORE FUNCTIONALITY? If you are looking for more layers or advanced tools and functionality, then try our suite of GIS Web Mapping Applications.

Active position information for the City of Greensboro. The dataset contains position current status, position title, and mid-range pay for the position.City of Greensboro FY 2019-2020 Executive and General Salary Structures Effective September 01, 2019 through August 31, 2020City of Greensboro FY2019-2020 Fire Sworn Salary Structure Effective July 1, 2019 through November 30, 2020The City of Greensboro currently employs more than 3,500 people in a wide variety of jobs. We are proud to offer administrative positions, public safety jobs, technical careers, trades work, and more. We hire for all jobs based on qualifications, knowledge, skills, and abilities.The City of Greensboro appreciates our skilled and qualified workforce. We offer a competitive and generous benefits and compensation package.The City of Greensboro is an equal opportunity, affirmative action employer. (Read more about the City's Diversity and Inclusion program.) Additionally, the City is committed to a family-friendly and drug-free work place environment.Our Mission Statement Maximizing service excellence through human capital management.BenefitsAre you are an employee or are you are interested in employment with the City of Greensboro? Learn more about our benefits by viewing the latest Benefits Book.Careers If you are interested in a career with the City of Greensboro, please go to iApplyGreensboro to see current vacant positions. Read more about the application process. Top Requested DocumentsOverview of the City of Greensboro Total Compensation Program (with links to the executive and general, fire, and police pay structures)Benefits Book Job DescriptionsPolicy Manual

There is a Boulder County focus inherited from the Boulder Creek Critical Zone program. If you are aware of a resource worth sharing please let us know. Files are in the versatile KML format for ease of sharing. If you have trouble importing these into ArcGIS or another program just let us know.

SITE EXTENTS: Kml's that shows study site extents. The main set of extents was created by Kyotaek Hwang.

SITE: BOULDER CREEK BOULDER COUNTY More Boulder County data can be found here: https://opendata-bouldercounty.hub.arcgis.com/ Selected kmls include: - Archaeologically_Sensitive_Areas - County_Open_Space - Lakes_and_Reservoirs (included modern glaciers) - mun_wtrsheds_czo (restricted areas) - Open_space_czo - Riparian_Areas_-_2013_ERE - Road_Map_Roads

GEOLOGY - Geological map by Ogden Tweto, clipped here to Boulder Creek, geo_czo_tweto https://coloradogeologicalsurvey.org/publications/tweto-geologic-map-colorado-1979/

• Clipped Cole & Braddock geologic map

SOILS Natural Resources Conservation Service soil maps https://www.nrcs.usda.gov - soilmu_a_co643_bc (boulder County) - soilmu_a_co645_arnf (Arapaho National Forest

GLACIERS Madole's Glaciers LGM. No online source. Check licensing before using in publication

TOPOGRAPHIC Topographic Lines created but the BcCZO from 30m USGS DEM

LIDAR For Lidar: OpenTopgraphy 2010 Lidar, Snow ON Snow Off https://portal.opentopography.org/dataSearch?search=Boulder%20creek%20CZO

SITE: COAL CREEK Coal Creek Trails

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.

This web map shows the location of Job Centres and Industry-based Recruitment Centres in Hong Kong. It is a set of data made available by the Department of Health under the Government of Hong Kong Special Administrative Region (the "Government") at https://GEODATA.GOV.HK/ ("Hong Kong Geodata Store"). The source data is in GML format and has been processed and converted into Esri File Geodatabase format and uploaded to Esri's ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Hong Kong Geodata Store at https://geodata.gov.hk/.