Latest Contributions by KyleGonterwitz

Try importing pandas and using df = pd.DataFrame.from_records(data=arcpy.da.SearchCursor(fc,fields),columns=fields) where fc is your GIS feature class layer and fields are a list of fields in fc you define format the data frame and print tables, display tables, or display(HTML(table.to_html())) for larger outputs  try using group by with .sum or .apply and lambda functions for fast results printed in the jupyter output window ... View more

I burned culverts recently and ran into this.  One way around this is to create a polygon that is the size of your DEM extent with a value of zero.  Then merge your culvert buffer polygons with nonzero cut depth with that zero polygon and make the cut raster, so that your cut values are zero or desired cut values and not null values.  If there is an easier way to calculate null values in the raster to zero I have not found it. ... View more

 I didn't develop the approaches, I only programmed and tried to document it in the jupyter notebook.  It's just like you said, its ages, materials, any factors you can identify, then relationships to breaks, put things in bins or categories, and try to figure out what makes sense - that's where the AI approach would be helpful in making it less arbitrary and examining sensitivity of various factors in your system (its the scientific method - guess and test).  It would be interesting to do more comparison with relation between breaks and weather data as well.   I have tried looking at emergent hot spots but the break data isn't dense enough over time to make real useful statistics  determinations.   ... View more

I've updated a couple existing organization processes for this into a Jupyter notebook, shared here. https://github.com/gontek/CMED/blob/main/AssetPrediction.ipynb https://github.com/gontek/CMED/blob/main/WaterMainAssessment.ipynb I know of other people in the business doing great research into this stuff utilizing AI to explore deeper into what causes breaks and poor service.  You are right that there are many factors to consider and each system is different and unique, and you are very fortunate if you have good break/leak data to work with.          ... View more

for OSOW one business case for certain would be having the routes as the common operating platform for referencing of construction projects and bridge locations. ... View more

In the meeting the question about impedances comes up, one answer to that question (and it was discussed in the meeting) and the solution this discussion topic proposes is to close the gap between State DOT Linear reference systems and non-State DOT organization transportation and logistics management. ... View more

Cities and Counties could easily calculate impacts to traffic improvements by comparing before and after crash rates along the routes when traffic safety countermeasures are applied. ... View more

Pavement Condition Index and PM2 (pavement performance measures) for MPOs could be easily collected and referenced over time on the same routes for pavement lifecycle analysis and management across DOT and MPO jurisdictions.   ... View more