In celebration of GIS Day, 2020, I interviewed my brother, John Foster, Senior Manager, GIS at Apex Clean Energy to learn how he uses GIS in his profession.
In 2001 John received a master’s in Environmental Planning at UVA’s School of Architecture. While in graduate school, he happened to take a class in GIS, which was a relatively new discipline at the time. Upon graduating, this experience helped him land a job at a local land trust. There was one other colleague at the time working on GIS and the two of them worked together for seven years, honing their analytical and mapping skills.
In 2009, John was hired by a renewable energy development start up, Apex Clean Energy, based in Charlottesville, VA. At the time the company had around 20 employees, and had its sights set on developing utility scale wind projects throughout the Midwest for utilities and corporate entities. Helping answer the question of where (and where not) to develop, the need for GIS support increased as the company grew to 200+ employees. While the GIS team at Apex currently consists of 8 full time Analysts and Developers, the company’s Environmental, Land, and New Markets departments have also added team members proficient in GIS. Apex’s projects completed to date range in size from 100 to 525MW, and total over 4GW of wind and solar power providing electricity to hundreds of thousands of homes, and companies such as Apple, Facebook, Starbucks, IKEA and McDonalds.
Data Gathering with GIS
Within the GIS team, Analysts are assigned to specific solar and wind project development teams, and provide critical information throughout the development process. The wind projects tend to be more complex, because they range in size from 20,000 to 45,000 acres, and can include thousands of parcels of land owned by hundreds of landowners, whereas the solar projects are significantly smaller in scale geographically.
The majority of the data used to site wind and solar facilities is publicly available and gathered by Apex’s New Markets GIS Analysists, and then handed off to the GIS team, which uses it to create the blank canvas on which project facilities (turbines, underground 34kV collection lines, access roads, and overhead transmission lines) are designed. Areas to avoid, otherwise known as setbacks, are calculated using a Python script which takes into account the type of feature- houses, barns, pipelines, roads, and then the dimensions of the wind turbine, which typically exceed 500’ in height. These setback distances are determined by local zoning ordinances, as well as industry accepted safety standards. Additional data is collected by wildlife consultants who conduct surveys for the presence of endangered species, such as eagles, bats and prairie dogs. Consultants also provide GIS data related to air space constraints, and geology, but ultimately it’s the landowners who agree to lease their land to the project that determine if a project gets sited within a community.
The foundation of the GIS team’s ability to share data throughout the company is a web map, known internally as “Atlas,” which is built on ESRI’s Portal and Enterprise GIS software platforms. As the quantity of data managed has grown, new web maps have been created specific to solar and wind, as well as project and department specific web maps. As the goal of the GIS team is to provide as much transparency as possible into the spatial data influencing the placement of facilities, company wide facing web maps offer the best visibility into the data the GIS team manages.
Everyday Work, Changes, and Possibilities
What John likes about his job is helping people find answers to questions quickly and efficiently using this powerful software. Although some of the spatial analysis can be repetitive, the use of Python, algorithms, and machine learning have automated many of the processes and increased the accuracy of analysis. John thinks the future of GIS will bring more automation, and an ever increasing flood of data from companies like Google, Microsoft, and local governments. The biggest challenge at the moment seems to be quality control. While many operations have been automated, the human eye is still required to catch many of the nuances that are difficult to decipher in an aerial image or a complex map.
Although John has learned most everything he knows on the job, he does recommend taking advantage of the immense amount of training on ESRI’s website, as well as online courses available at colleges, universities and community colleges in your area. While programming languages such as Python are becoming essential, having the ability to effectively communicate details and complexity with a single map or image is equally critical.
If this post interests you, check out Apex’s paid internships, where you will be on the front lines assisting the company with their next project.
— Contributed by Kate Foster Boyd and John Foster