Great Springs Trail Benefits Study & Master Plan
The Great Springs Project (GSP) envisions a national park-scale corridor of protected lands between the densely urban areas of Austin and San Antonio. This green corridor will be connected by a network of trails that links four of Texas’ Great Springs: Barton Springs, San Marcos Springs, Comal Springs, and San Antonio Springs. During this project, David acted as a technical lead for Alta’s benefits analysis. He provided oversight and input into the project’s analysis and visualization approach. His key focus was research into how to estimate ecosystem service and carbon storage & flux benefits of the GSP’s planned 50,000 Acre conservation purchases. Based on a literature review, he used USGS National Land Cover data to contribute to the narrative regarding the need for conservation and to estimate ecosystem service benefits to be provided by the conservation purchases.
Beyond this benefits study, David developed and implemented the approach for alignment prioritization as part of the Master Plan for the trail. The alignment analysis identified which segments would be chosen in scenarios that helped identify the balance of access and natural values of the trail. This analysis was done within a Jupyter notebook that enabled scenario-oriented analysis and could adjust weights dynamically.
Great Springs Report pages showing the changes in land cover in the study corridor.
Description of methods and estimates of ecosystem service and carbon sequestration benefits related to the conservation purchase associated with the corridor. The report also details conventional benefits to economic development and mobility associated with trail implementation.
This animation shows the rapid pace of development and land cover change within a sample location of the GSP corridor.
Beyond this benefits study, David developed and implemented the approach for alignment prioritization as part of the Master Plan for the trail. The alignment analysis identified which segments would be chosen in scenarios that helped identify the balance of access and natural values of the trail. This analysis was done within a Jupyter notebook that enabled scenario-oriented analysis and could adjust weights dynamically.