Your Presenters:
Rebecca Davis, Project Manager
10 years GIS experience focused on municipal government data from parcels to utilities systems.
Ashley Tardif, Data Scientist
8 years of GIS experience focused on ETL processes, data analysis, and data visualizations leveraging both proprietary and open-source tools.
Highlights and Soundbites
Ashley: Some of the tools that we use primarily here at Sanborn include Python and R, which are coding solutions. We use various packages within these, such as GeoPandas and ArcPy. Both Python and R are open source, and are great tools to implement on client’s machines if need be. We also use SQL especially when we need to work directly in or with a database. Some non-code solutions include FME and Alteryx.
Ashley: As some of you might know, we have a tool called the CAMA uploader. This is a script that updates the CAMA data from the Assessor’s database onto MapGeo nightly, and it also has another use, which is to upload essential spatial and tabular data. This can include parcels, utility data, [and] zoning annotation just to name a few examples, however, in order to upload that data to MapGeo we need a process that will read the data directly from the city’s database and convert it for use on MapGeo.
Ashley: (on school redistricting) Where scripting is super beneficial for us is that we can automate our statistic and summary workflows for how we apply student data to components and district scenarios. These workflows are also repeatable, and can be used for different towns and cities.
Rebecca: Essentially what this is doing it’s taking your input source data which are in this case your roads, your buildings, your drainage basins, and other depth rasters. It’s pulling all of that into and looking at our flood risk scoring criteria, which is saying if a building is in this depth of a flood raster, it receives a score.
