Now in its second year, Azavea’s Summer of Maps Program has become an important resource for non-profits and student GIS analysts alike. Non-profits receive pro bono spatial analysis work that can enhance their business decision-making processes and programmatic activities, while students benefit from Azavea mentors’ experience and expertise. This year, three fellows worked on projects for six organizations that spanned a variety of topics and geographic regions. This blog series documents some of their accomplishments and challenges during their fellowship. Our 2013 sponsors, Esri and Tri-Co Digital Humanities helped make this program possible. For more information about the program, please fill out the form on the Summer of Maps page.
Since the 2011 drought, most concern regarding tree survival in Dallas has revolved around their natural lifecycle. Urban populations are growing exponentially. Dallas is the second fastest developing city in the U.S. As time passes, land development poses an increasingly significant threat to Dallas’ well-loved trees. Since Texas lost 100 to 500 million trees in 2011, it is of the utmost importance to avoid cutting trees’ lives short for new construction and to restore Dallas’ urban tree canopy. While the weather cannot be tamed, one may opt to develop, plant and preserve responsibly.
Objectives
In partnering with the Texas Trees Foundation, my mission was threefold:
1. Identify trees in danger of being cut down in the face of development.
2. Identify planting sites where trees increase the value of developing land.
3. Quantify the cost of losing endangered trees and value of planting additional trees.
I also assessed cost by Council District to establish Dallas councilpersons as stakeholders.
Research
To prioritize tree preservation areas and additional tree planting sites, development pressure must be identified. Following in the footsteps of researchers, professors, and city planners, I took a two-pronged approach to identify development pressure: examining 1.) land supply for development then 2.) land demand. For the purposes of this project, development pressure is a heuristic measurement gauging where development might logically occur. Areas that are desirable for development and can host development have high development pressure.
Variables
Working with a slew of variables, I began familiarizing myself with the data. In the buildable land analysis, I incorporated three types of variables: un-developable, restricted development, and (re)developable land. Researching land development in Dallas, I stumbled on the forwardDallas! Land Use Assessment. The Land Use Analysis became a guide for my land demand analysis. I included the following variables: Tax Increment Financing Districts (TIFs), the forwardDallas! vision illustration (2006), and proposed construction sites (2013). Ultimately, I whittled down the list of variables from 72 to roughly 30. Converting these to raster format (a grid based data type) would allow the Texas Trees Foundation to select any 10 square meter grid cell in the City of Dallas, and see its tree planting and preservation priority rating. Once converted to grids, the variables’ were assigned a rank (coefficient or weight) usually between 5 and -5.
Method
Land supply and demand, planting sites, and preservation suitability rasters were all developed using weighted sum models. For example, compiling the land demand raster, I built the following weighted sum model:
The tool stacks the maps associated with each variable on top of one another and adds them together. The variables’ level of impact and type of influence (positive or negative) depends on its assigned rank or weight. For example, while evaluating the variables, it was clear that DART stations and TIFs have high weights and are most attractive for development.
Resulting maps were also grids with 10 square meter cells. Each cell has a rating for development, canopy preservation, and tree planting location suitability. A map of tree planting sites on public land is below:
After identifying development pressure across the City of Dallas, I began identifying preservation areas and future planting sites. Trees growing in areas that are likely to be developed were marked as endangered. The high priority preservation model is a slightly more detailed version of the following diagram:
Here’s the final map identifying areas of tree canopy that are most endangered in Dallas:
The Texas Trees Foundation has chosen to hold future planting events on public land that will increase the value of near-by developing private land. Thus the additional tree plant sites are summed as follows:
In accordance with requests of the Texas Trees Foundation but private land was not excluded, just a lower priority. Similarly some planting sites overlap with buildable land, as development is not restricted along riparian areas, which are high priority for future plantings.
Conclusions, Strengths and Weaknesses
Council Districts in Southern Dallas have the most endangered canopy per square meter of land, but also the most room for planting additional; these council districts have both the most to at risk and most potential for growth in urban tree cover.
Creating weighted sum models allows the impact of each variables to be tweaked as research reveals more about their influence on future development – an interactive feature that extends relevance of the map.
Were I to do this study again, I’d like to identify incidents of urban development by analyzing remote sensing data, then pin down the variables that influence development with machine learning, and predict future development accordingly. Of course, this depends on data availability and the length of time that may pass before the surrounding factors (including the development itself) stop having a bearing on future development.