About this itemBack in 2017, I made a Cascade story map to compile GIS career resources for my current and future interns. Fast forward seven years, and I finally rebuilt it as an ArcGIS StoryMap. From job title descriptions to certifications and to salaries, it covers the main areas I find emerging professionals asking about when they're looking at a career in GIS. There are multiple shout outs to the Consortium in it too, of course.😎Author/ContributorJohn NergeOrganizationPersonal workOrg Websitehttps://bit.ly/JohnNerge

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for geographic information systems gis in the U.S.

Classification establishes and maintains the County's job classifications and compensation systems and practices, with equity, consistency, and due regard for pay competitiveness. Positions are analyzed and assigned to appropriate job classificationsJob Descriptions -- Frequently Asked Questions -- Classification and Compensation Documents

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for gis in the U.S.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for forest engineering (gis) in the U.S.

Tempe is among Arizona's most educated cities, lending to a creative, smart atmosphere. With more than a dozen colleges, trade schools, and universities, about 40 percent of our residents over the age of 25 have Bachelor's degrees or higher. Having such an educated and accessible workforce is a driving factor in attracting and growing jobs for residents in the region.The City of Tempe is a member of the Greater Phoenix Economic Council (GPEC), and with the membership, staff tracks collaborative efforts to recruit business prospects and locations. The Greater Phoenix Economic Council (GPEC) is a performance-driven, public-private partnership. GPEC partners with the City of Tempe, Maricopa County, 22 other communities, and more than 170 private-sector investors to promote the region’s competitive position and attract quality jobs that enable strategic economic growth and provide increased tax revenue for Tempe. This dataset provides the target and actual job creation numbers for the City of Tempe and the Greater Phoenix Economic Council (GPEC). The job creation target for Tempe is calculated by multiplying GPEC's target by twice Tempe's proportion of the population. This page provides data for the New Jobs Created performance measure.The performance measure dashboard is available at 5.02 New Jobs Created. Additional Information Source:Contact: Madalaine McConvilleContact Phone: 480-350-2927Data Source Type: Excel filesPreparation Method: Extracted from GPEC monthly and annual reports and proprietary Excel filesPublish Frequency: AnnuallyPublish Method: ManualData Dictionary

The County of Suffolk Annual Salaries File for the Year 2024 is a yearly summary of Payroll Data for all Suffolk County employees. This file contains the Employee Names and Hired Date along with their most recent Job Title and Department. In addition, the file contains the Employee’s Regular Pay Rate (Hourly, Biweekly or Annual Salary), the Year to Date Regular Earnings, Longevity Pay, Overtime Pay, and Other Payments (comprised of Holiday Pay, Night Differential Pay, Cleaning and Clothing Allowances, Taxable Legal Benefit Amounts, etc.). If an employee has been terminated or has separated from County employment, the Separation Payment Amount (if applicable), and Termination Date is also included.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for applied geospatial science in the U.S.

Costs to the City for salary and benefits listed by job title. Costs to the City for salary and benefits listed by job title. Data contains historical information from year 2014 to Present

Louisville Metro Human Resources (HR) Department, with the support of department leaders and their agency HR Representatives, provides support to all metro agencies in personnel management, benefits administration, labor relations, training, recruitment, occupational health & safety, payroll administration and onboarding. This data is presented in a publicly available report, located HERE

Please review the FAQ located at https://louisvilleky.gov/government/human-resources/salary-data-faq

Field Name

Field Description

Cal Year

Calendar year the row data is referencing

Employee Name

Full employee name (LAST, FIRST MIDDLE)

Department

Metro department of employee during the referenced calendar year

job Title

Job title of employee during the referenced calendar year

Annual Rate

Yearly compensation rate of employee (Hourly Rate X Annual Work Hours)

Regular Rate

Gross payments received in the referenced calendar year for hours worked

Overtime Rate

Amount of overtime payment(s) within the calendar year referenced

Incentive Allowance

Additional payments for work allowances (i.e.: uniform allowances, call out payments etc.)

Other

Any additional payments issued to employee not captured in the other categories

YTD Total

Year To Date (YTD) compensation paid

The Long Island Sound Study developed these digital data from 1:100,000-scale National Oceanic & Atmospheric Administration (NOAA) and United States Geological Survey (USGS) maps as a general reference to the depth of water in Long Island Sound. In 1996, these data were digitized from paper maps by the Long Island Sound Study (http://www.longislandsoundstudy.net) and incorporated into a Long Island Sound GIS database. Not intended for maps printed at map scales greater or more detailed than 1:100,000 scale (1 inch = 1,578 feet.) Dataset credit: Applied Geographics, Inc. of Boston, Massachussets was contracted by the Long Island Sound Study to automate and digitize these bathymetry data for Long Island Sound. Linda Bischoff, GIS Analyst, digitized the data and created the orginal metadata.

eBook that explains GIS.

This layer contains the fireworks exclusion zone data for the City of Round Rock, located in Williamson County, Texas. This layer was created by Kim Jones, GIS Analyst for the Fire Marshall Captain Selby to be able to quickly see where exactly fireworks are not allowed in a given area. The Fire Marshal utilizes this data primarily around Independence Day on July 4th, and around New Year's Eve on December 31st. This layer is represented as a buffer, which extends 5000 feet from the city limits. The purpose of this layer is to show which areas surrounding city limits are permissible to set off fireworks in.

The County of Suffolk Annual Salaries File for the Year 2023 is a yearly summary of Payroll Data for all Suffolk County employees. This file contains the Employee Names and Hired Date along with their most recent Job Title and Department. In addition, the file contains the Employee’s Regular Pay Rate (Hourly, Biweekly or Annual Salary), the Year to Date Regular Earnings, Longevity Pay, Overtime Pay, and Other Payments (comprised of Holiday Pay, Night Differential Pay, Cleaning and Clothing Allowances, Taxable Legal Benefit Amounts, etc.). If an employee has been terminated or has separated from County employment, the Separation Payment Amount (if applicable), and Termination Date is also included.

This layer (hosted feature layer) depicts the current customers of sewer services in the City of Canton, GA. This data set is maintained by the City of Canton's GIS division, and is updated on a regular basis to reflect current customers. For specific questions about this data or to provide feedback, please contact the City's GIS division: Alaina Ellis GIS Analyst alaina.ellis@cantonga.gov (770) 546-6780 Canton City Hall 110 Academy Street, Canton, GA 30114

Using the coronavirus infographic template in Business/Community Analyst Web (ArcGIS Blog).

Off-road ATV usage is widespread in many regions of the Izembek Refuge, especially adjacent to official roads north and west of Cold Bay. GIS analysts manually digitized ATV tracks in this region using aerial imagery collected in May 2022 and processed by Mark Laker (Alaska Refuge Remote Sensing Coordinator) during that summer. This aerial imagery has a ground-resolution of 10-20 cm. GIS Analyst Tristan Amaral (Alaska Refuge Natural Resources Program) created this layer and GIS Analysts Dan Quinn (Alaska Refuge Natural Resources, daniel_quinn@fws.gov) completed the project. The layer exists as a Hosted Feature Layer on ArcGIS Online.

This layer (hosted feature layer) depicts water lines in the City of Canton, GA. This data set is maintained by the City of Canton's GIS division.For specific questions about this data or to provide feedback, please contact the City's GIS division: Alaina Ellis GIS Analyst alaina.ellis@cantonga.gov (770) 546-6780 Canton City Hall 110 Academy Street, Canton, GA 30114

Yearly effective energy and mass transfer (EEMT) (MJ m−2 yr−1) was calculated for the Catalina Mountains by summing the 12 monthly values. Effective energy and mass flux varies seasonally, especially in the desert southwestern United States where contemporary climate includes a bimodal precipitation distribution that concentrates in winter (rain or snow depending on elevation) and summer monsoon periods. This seasonality of EEMT flux into the upper soil surface can be estimated by calculating EEMT on a monthly basis as constrained by solar radiation (Rs), temperature (T), precipitation (PPT), and the vapor pressure deficit (VPD): EEMT = f(Rs,T,PPT,VPD). Here we used a multiple linear regression model to calculate the monthly EEMT that accounts for VPD, PPT, and locally modified T across the terrain surface. These EEMT calculations were made using data from the PRISM Climate Group at Oregon State University (www.prismclimate.org). Climate data are provided at an 800-m spatial resolution for input precipitation and minimum and maximum temperature normals and at a 4000-m spatial resolution for dew-point temperature (Daly et al., 2002). The PRISM climate data, however, do not account for localized variation in EEMT that results from smaller spatial scale changes in slope and aspect as occurs within catchments. To address this issue, these data were then combined with 10-m digital elevation maps to compute the effects of local slope and aspect on incoming solar radiation and hence locally modified temperature (Yang et al., 2007). Monthly average dew-point temperatures were computed using 10 yr of monthly data (2000–2009) and converted to vapor pressure. Precipitation, temperature, and dew-point data were resampled on a 10-m grid using spline interpolation. Monthly solar radiation data (direct and diffuse) were computed using ArcGIS Solar Analyst extension (ESRI, Redlands, CA) and 10-m elevation data (USGS National Elevation Dataset [NED] 1/3 Arc-Second downloaded from the National Map Seamless Server at seamless.usgs.gov). Locally modified temperature was used to compute the saturated vapor pressure, and the local VPD was estimated as the difference between the saturated and actual vapor pressures. The regression model was derived using the ISOHYS climate data set comprised of approximately 30-yr average monthly means for more than 300 weather stations spanning all latitudes and longitudes (IAEA).