City of Janesville GIS Analyst Internship (Community Development Department)

 

 

Sidewalk Committee Analysis Project  

Janesville, located in south central Wisconsin, is a progressive council-manager administered city of more than 63,000 people. During my summer internship in the Community Development Department at City Hall, I assisted the GIS Coordinator, Kirby Benz, with a variety of projects powered by GIS. One such project involved analyzing areas within the Janesville Municipality that were in the greatest need for sidewalk construction. A large portion of the city as well as many surrounding neighborhoods were not equipped with sidewalks, most did not even have plans for future sidewalk construction. A community sidewalk committee had been formed by city council after the 7 year project to build 63 miles of sidewalk had came to a halt. The program was disbanded and restructured due to large community skepticism on proposed construction areas. While some residents saw the benefits of have having a more connected city, opponents to the plan did not want to pay for or maintain the new sidewalks.

One aspect of this project consisted of analyzing seven site suitability variables which were determined by the 12 person community sidewalk committee and also approved by city council members. These variables were heavily debated among council and committee members however a consensus was finally reached. The sidewalk variables were defined as follows; proximity to schools (1/4 & 1/2 mile buffer), proximity to transit bus stops (1/4 & 1/2 mile buffer), proximity to public facilities such as churches, parks, clinics and retail centers (1/4 & 1/2 mile buffer), street class (major arterial, minor arterial, collector), existing sidewalk gaps, housing density (>4 units & <2 units), and pedestrian/automotive accidents. The GIS analysis was performed on each individual sidewalk segment for each city parcel. An index ranking was then applied to sidewalk parcel segments depending on their spatial location to each of the seven variables described above.

The community sidewalk committee was in charge of developing the ranking system. Higher scores were given to sidewalk areas closer to schools, public facilities and transit stops, higher accident risk areas, locations with existing sidewalk gaps, areas adjacent to high density housing and streets classified as high use. For example, sidewalk segments within a 1/4 mile of a school were given a ranking of 20 while areas within a 1/2 mile were given a ranking of 15. Based on the seven criteria, the highest possible ranking was 100. Sidewalk construction is being analyzed by zone with there being 9 different city zones; zones 1 and 2 are referenced in the three buffer analysis maps below. These visual tools directly assisted in the sidewalk committee's analysis and subsequent recommendation on sidewalk construction priority around the city. The following three maps provide a brief insight into how we developed the sidewalk ranking index maps.

1) Sidewalk Committee: School and Population Density Analysis Map - Zones 1 and 2




Areas within a 1/4 mile school buffer and sidewalks adjacent to larger population densities were ranked higher

2) Sidewalk Committee: Transit Route Stops Analysis Map - Zones 1 and 2

Sidewalk areas within the 1/4 mile transit stop buffer were ranked higher than those in the 1/2 mile buffer

3) Sidewalk Committee: Public Facilities Buffers Analysis Map - Zones 1 and 2 



Areas located within the 1/4 mile public facilities buffer were ranked higher than areas just located within the 1/2 mile buffer

Final Product

After the total rank (out of 100) was calculated for each individual property segment based on the seven criteria, the data was then classified using a natural breaks classification method for five class intervals. The natural breaks method or (Jenks) classification, groups features with similar values while trying to maximize the differences between the means of the five different classes. The final sidewalk committee analysis map is shown below. The committee is now tasked with the difficult decisions of choosing which areas to start construction, what side of the street (if not both) should be constructed, how the project should be financed and what sort of construction time line should be established. In early July, the Janesville City Council ultimately voted to install more than two miles of sidewalk.

By the time we were finished with this project, I was able to get a firm grasp on how policy, procedures and public opinions heavily influenced the course of action within City Hall. This analysis project is just one example of how GIS can be leveraged to address important local community development decisions.



The approved final sidewalk committee analysis map showing an individual parcel index ranking of all seven site suitability variables

Water/Sewage Utility Network Analyst

Originally, this internship was specifically for the position of Utility Network Analyst. However, I was frequently pulled off this primary project to assist in other departmental mapping endeavors (sidewalk map analysis, assessment maps). At first, the inaccurate and incomplete layers within the large utility data sets made this project seem very daunting. I quickly devised a systematic quality control plan and soon realized how important an accurate, up to date utility network is for a cities overall infrastructure plan. 

I had permission to work in the departments ArcSDE (Spatial Database Engine) geodatabase which allowed editing rights to all of the utility data files and layers. I quickly gained a new skill set in ArcGIS as I learned the in and outs of the GIS department and ArcSDE; these skills included general data structure, versioned editing (reconcile & post), advanced SQL scripts, definition query's, advanced editing tools and cartographic techniques in ArcMap's layout view to just name a few. I also gained valuable experience in photo interpretation.

In 2006, the City of Janesville contracted the Waukesha based engineering firm Ruekert Mielke to build the city's sewage, water and storm utility networks. However, budgetary constraints and limited access to asbuilt field inspection books resulted in inconsistent and incomplete data layers. To put it simply, the utility layers were lacking in attribute and spatial correctness. My job as a GIS Analyst was to contribute towards making the utility networks a more comprehensive GIS layer. This was attained primarily through quality assurance assessments as I will further describe below.

 

 

In the GIS, the city of Janesville is divided into quadrants using a map grid system. By using this map grid, I was able to systematically check for spatial and attribute inconsistencies in each quadrant (K-13, P-5, S-20, etc). The combination of 80 scale blue prints and aerial photographs provided two basic resources in which I could interpret and therefore represent the GIS data layers being examined.

 



Map Grid Utility QC Layer - Blue quadrants represent areas where feature attributes and spatial correctness was been checked



Performing quality assurance on the GIS utility network data sets required the interpretation and comparison of 80 scales (Left), and the 2011 aerial photo of Janesville Wisconsin (Right). Asbuilt field inspection books were also referenced as needed. 



 

 

The process of utility QC consisted of panning up and down streets checking both sewer and water utility layers for spatial accuracy as well as populating/updating inaccurate or missing feature attributes. Inaccuracies would then be documented or fixed on the fly. Google Earth street view provided a platform for double checking spatial discrepancies.

 

 

As I pan up and down streets, I am checking for spatial accuracy as well as populating discrepancies in missing attributes

 

 

Spatially Inaccurate Utility Feature Examples



 

 

The left image is showing a common spatial inaccuracy within the sanitary sewage layer. Note the manhole point feature is about 8 feet south of the actual manhole location on the aerial photo. Fixing this problem requires a spatial adjustment as well as an attribute update. The right image is documenting a common error within the water utility later. It is imperative to correct spatially inaccurate hydrant locations as well as update their accompanying attributes. Fixing these discrepancies contributes towards building a more accurate utility network.

 

 

 Building A Geometric Network

 

 

As many GIS professionals know, a geometric network is comprised of a set of simple and complex edge features (water mains)  and junction features (tee's, valves) that have a particular position, connectivity and shape which all participate in a linear system. Topology or "connectivity rules" must be defined within a network such as which type of junction can connect to a each edge. Solvers (downstream trace, upstream trace, isolation trace and path trace) are used to execute network analysis. Solvers help to model real world problems such as isolating mains and valves due to a break. Weights (diameter, length, material) can be applied to features within the network to also better model flow and connectivity.

 

Comparable Property Assessment Map

When property owners challenge the assessment of their parcels, the Community Development Department utilizes GIS to construct property comparability assessment maps. I created a variety of these maps (shown below) which spatially illustrated the assessed subject property being challenged (Black) along with three other properties in the area with similar credentials (Red). The Board of Review uses these maps to help facilitate their decision making on how certain parcels are assessed.

 

 

 

 

 

 

Rock Energy Coop Grid: Janesville

The Water Utility Department in Janesville requested a map that illustrated what areas are serviced by the Rock Energy Cooperative. Below is a locational map showing Rock Energy Cooperatives service grid within the Janesville municipality.

Multiple clips and a monochromatic color design were used to create the map above