San Francisco's Trees

Medha Bulumulla, INFO 5311/4310 Homework 1

Story of Data & Design Rationale

This visualization tells the story of how public ownership of trees, although small, can make a large difference. Most trees in San Francisco are privately owned by households, Arts Commissions, College, Fire/Health Department, etc. Privately owned trees can fall into various categories but to avoid overwhelming the viewer, this was consolidated into one group. The private trees are important to the beautification of the area and can be conveyed through the map. But most of the biggest trees are publicly owned. Without public ownership, we would not see the presence of older, bigger trees.

Through the map, the viewer has a brief overview of tree locations and ownership type in the area. Most of the dots are blue (private) but hints of green (public) show through. This gives context for the user and minimal information. In the first histogram, Diameter at Breast Height, one can see the height distribution of the trees. One can easily decipher that most of the trees are 20-40 tall without getting too bogged down by numbers and additional information. The breakdown of public and private is present in this histogram but cannot be seen due to the small percentage of public ownership and tall trees. This difficulty was solved by the information conveyed in the second histogram. Caretaker Percentages for each DBH Level shows that many of the larger trees are publicly owned. The 3 visualizations aim to show what a small impact can do. It highlights a hidden pattern about the heights and caretaker types.

Data Processing

The data was processed through the Python script: data/countDBH.py using pandas and numpy functions. All trees that did not have a caretaker of DPW or DPW for City Agency were categorized as having a private caretaker. The dataset with the binary caretaker column was exported as data/trees.csv.

To make viewership of the depth breast height (dbh) histograms easier, bins were created such that if a tree was between 0-19—it would be categorized as 0; 20-40—it would be categorized as 20, etc. Counts of each bin and the caretaker type was used for the histogram. The number of trees that were in each bin were tallied such that the percentage of public trees for each dbh bin could be calculated for the second histogram. This data was exported into the file data/trees_count.csv.

Visual Encodings

Each visualization has shared and individual visual channels. All visualizations use color hue based on private (blue) or public (green) ownership. The map uses non-aligned position to signify location. Both histograms use horizontal and vertical aligned position to convey different things. The horizontal aligned position in the first graph conveys counts of trees in each depth breast height bin. The horizontal aligned position in the second histogram conveys the percentage of trees of that bin height that are public or private. For both histograms, vertical aligned positions convey the depth breast height of the trees. By using similar visual channels throughout, the viewer can get accustomed to the visualizations easily.