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.

Analysis of ‘5.02 New Jobs Created (summary)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/73bc502b-2b3a-4ab7-83ad-4649019064d0 on 11 February 2022.

--- Dataset description provided by original source is as follows ---

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 locates. 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 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: Jill Buschbacher
Contact E-Mail: Jill_Buschbacher@tempe.gov
Data Source Type: Excel files
Preparation Method: Extracted from GPEC monthly and annual reports and proprietary excel files
Publish Frequency: Annually
Publish Method: manual
Data Dictionary

--- Original source retains full ownership of the source dataset ---

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The CURE vegetation mapping project area was divided into 11,133 polygons and 42 map classes. A total of 10,520 map polygons represent 27 natural and semi-natural vegetation map classes. Fifteen land use map classes describe 613 other polygons within the mapping area. Average polygon size across all map classes is 4.4 ha (10.8 acres). The mapping component of the CURE project used a combination of methods to interpret and delineate vegetation polygons. Initial line work was prepared by USBOR photointerpreters who delineated the most contrasting signatures, e.g., water bodies, exposed shoreline, unvegetated geology, land use types, and vegetation at the physiognomic level. The project photo interpreter used this baseline mapping and refined it by examining digital orthophotos in stereo. The stereo photography was used as needed to distinguish fine scale vegetation patterns. Ancillary datasets including plot and observation point data and classification and local descriptions of plant associations were used by the photointerpreter to assist with map class definitions and guide manual delineations. Polygons were drawn on Mylar overlays of printed orthophotos that were later scanned, or were drawn digitally on a computer screen. Heads-up digitizing consisted of delineating map class polygons on an electronic version of the digital orthophotos at a computer workstation. Digitizing was performed using vector editing in ArcGIS. The line work was refined and finalized by the SEUG GIS Specialist and the map class and other descriptive attributes for each polygon were assigned. The recreation area and the environs were interpreted and mapped to the same level of detail.

Analysis of ‘1.11 Feeling Safe in Work (summary)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/b64ed601-7b96-495a-a42e-1dc8705fe304 on 11 February 2022.

--- Dataset description provided by original source is as follows ---

This dataset comes from the biennial City of Tempe Employee Survey question about feeling safe in the physical work environment (building). The Employee Survey question relating to this performance measure: “Please rate your level of agreement: My physical work environment (building) is safe, clean & maintained in good operating order.” Survey respondents are asked to rate their agreement level on a scale of 5 to 1, where 5 means “Strongly Agree” and 1 means “Strongly Disagree” (without “don’t know” responses included).

The survey was voluntary and employees were allowed to complete the survey during work hours or at home. The survey allowed employees to respond anonymously and has a 95% confidence level.

This page provides data about the Feeling Safe in City Facilities performance measure.

The performance measure dashboard is available at 1.11 Feeling Safe in City Facilities

Additional Information

Source: Employee Survey

Contact: Wydale Holmes

Contact E-Mail: Wydale_Holmes@tempe.gov

Data Source Type: CSV

Preparation Method: Data received from vendor and entered in CSV

Publish Frequency: Biennial

Publish Method: Manual

Data Dictionary

--- Original source retains full ownership of the source dataset ---