This week in lab we utilized the business suitability modeler in ArcPro in order to inform Los Angelas City planners on how many trees to allocate to each census tract. There have 90,000 trees to plant and they are motivated to increase shade throughout the city to reduce disparities amongst different groups. There were nine separate demographic criteria the model was given based on equity and susceptibility, and three criteria based on the environment like surface temperature and air quality.
Visualizing data
Prior to this lab I had not explored bivariate coloring of a map to visualize how two separate variables play together. Using symbology and the bivariate primary setting I was able to add two fields, like tree shade coverage and non-hispanic black populations by census track to gain an understanding of where the inputs are more or less dense independently and together.
Data Engineer
Data engineering allows you to pull in fields from a data set and calculate statistics for each field entry. In this lab we utilized data engineer to gain a sum for each census tract value, this could be counted as a household in the case of poverty or individual in the case of asthma medication. I found this feature easy to use and operate and its value when needing summary statistics quickly is immeasurable.
Practice adding and calculating fields
Much of what was done in this lab was calculating and adding fields to one data set (that is eventually used for the suitability model). For the nine demographic criteria I used the sum from data engineer and calculated percents for each row/cell).
For Air Quality(AQ) and Surface Temperature zonal statistics were used which essentially created a field within the dataset, in this case looking for the mean or average of each input. Higher values for either criteria indicates more vulnerability( worse air quality or more susceptible to high temperature during heat waves), so by calculating the mean of the raster values in the tract this can be extrapolated to the overarching dataset that is used for the suitability model.
Business Suitability model
This business suitability model allows you to allocate more priority towards certain tracts based on inputs, in this case looking to assess where trees should be planted. The directions gave simple values to assign each of the criteria based on what category they fell under (susceptibility, equity, environment), and in the case of factoring in tree coverage an inverse was assigned. Assigned a criteria an an inverse indicates to the model that a higher value(more shade) will have less priority when ranking the cells/rows in the original data set.
The business suitability model is a new feature in ArcPro and the lab was my first exposure to it. I thought the process was straightforward I would just make sure the data is being conveyed in a way that makes sense in your model. If you are averaging out values, be sure to use the mean/average for all criteria as to insure when you weight your model it is representative. Also, it was really important to include tree shade that was already present but if did not weight it in an inverse manner the results of the suitability model would be incorrect.