Caltrans Vulnerability Risk Assessment (VRA) Script Conversion

[natam1]

User story

Caltrans DDS is tasked with helping the Air Quality and Climate Change Office with the Vulnerability Risk Assessment (VRA). The assessment is being conducted by a few different consultants, with the goal of Caltrans running future assessments in house with the most updated asset data (data layers can be updated daily on some cases).

The initial task is for DDS is to migrate scripts from one of the consultants to our environment so that we (Caltrans) can run the data prep for the Bridge and State Highway System layers. This includes segmenting and tagging the assets so that the next phase of adding climate exposure analysis can be done at the segment level. This task is the first task and holds up rest of the analysis.

Caltrans received scripts from the consultants, which have hard dependencies in PostgreSQL. Our understanding is that these scripts were run with some older asset data and therefore need to be run again with the updated data. We want to ensure that these scripts are able to run with the new data received, as well any future data. To do that, we will have to rewrite the scripts to that they work with our environment and can be run/updated annually (possible for this to be run more often). Ideally, we would want to do a full rewrite. However, due to the quick turnaround time, we are hoping to use as much as we can from the existing scripts and then work on a refactor once the segmented data is handed off.

Each part of the analysis has a different owner.
  
Currently, I am working on prepping the bridge data in a notebook in the hub with the most recent data received. Looking to see what kinds of possibilities there are for this analysis in our warehouse, or other workflows that would benefit the project.

Acceptance Criteria

Being able to run the prep data scripts in our environment for a start.

Notes

Additional information on this issue can be found in this epic issue in the vra-analysis repo

tagging our other analyst on the project: @noah-ca

@hunterowens @tiffanychu90