3D Garden Design
The Lewis Ginter Botanical Garden in Richmond, Va., is open year-round to visitors who enjoy over 50 acres of plants in more than a dozen themed gardens. Facilities include an education and library complex with conference, classroom and laboratory space as well as a visitors center featuring a café, tea room, garden shop, meeting space, and exhibit areas. The garden’s iconic structure is a classical domed conservatory that houses exotic plants from around the world and is the anchor for its Central Garden--a progression of garden “rooms” that cover three acres.
Although stunning in its array of colorful blooms, exotic plants and splashing fountains, the Central Garden needed enhancements in balance and symmetry. In 2010, the board of directors embarked on a project to improve this area of the garden by adding new beds and irrigation, better lighting, more seating and shaded areas, a new water feature, and added pathways that will improve the flow of foot traffic and offer more direct access to other garden areas. In addition, the board began working on a stormwater master plan, recognizing their responsibility to practice and promote best water management practices that affect the watershed draining into the Chesapeake Bay, the largest estuary in the United States.
Originally, the project team hoped to use an aerial survey as the starting point for its landscape design and stormwater master planning. However, they quickly realized they needed another solution. They turned to the Timmons Group, a multi-disciplined engineering and technology firm also located in Richmond. “The tolerances from an aerial survey were completely insufficient for this project,” explains Dwayne Dunevant, LS, principal at the Timmons Group and surveyor in responsible charge on this project.
The only way to meet the tolerance requirements and fill in the missing stormwater data was through a field survey. Construction was slated to begin in the winter of 2011--the garden’s slowest time of the year. But that meant the survey would have to take place the summer before, during the garden’s busiest time of the year. To add to the complexity, the garden is a not-for-profit organization, and capital campaign funds used for the renovation project were understandably tight. “They needed approximately 20 acres of topography surveyed and mapped in less than four weeks, and they didn’t have the budget for a large field crew,” says Chris Marston, a survey project manager at Timmons Group.
“As you can imagine, the garden is heavily vegetated but we couldn’t damage any of that vegetation during our survey,” says Dunevant. “And we had to get the job done without disrupting the operations of the garden or its visitors. So even without the budget restrictions, a large survey crew was impractical.”
Conventional surveying workflows typically require field work to be completed before processing data in the office. This workflow can be a problem on projects with tight timelines like this one. Model-based surveying workflows eliminate this issue by allowing firms to process field data in parallel with the collection, helping to reduce the time it takes to complete work.
The team was able to regain lost time in the office. When the data was brought into the model for processing, the AutoCAD Civil 3D software created near production-ready drawings based on how the data was captured and coded in the field. As the survey data was imported, symbols and linework were automatically placed in the drawing, which not only helped save time but also cut down on any confusion that might have otherwise resulted from trying to interpret survey points, notes and site sketches. An existing conditions digital terrain model was created using point groups that represented topography shots and break lines that were defined in the field. Contours could then be automatically generated from these terrain models.
The software provided a dynamic link between the original survey data, 3D model objects, production drafting objects, and any design elements. Entities in a drawing, such as points and surfaces, were intelligent objects that maintained relationships with the drawing and with other objects in the model. The model automatically reflected any changes to drafting and annotation objects, and vice versa. For example, if the elevation of a topography point was adjusted in the model, this automatically updated the whole terrain model, redisplayed contours, updated annotations, and corrected all existing plan, section and detail sheets.
“The field crew sent their data to the office at the end of every day, and the next day we would upload it into a 3D model of the project,” Marston says. “We could QC the data on a daily basis instead of waiting until the end of the survey”--which was a good thing on this project, since it took almost the full length of the job to complete the field work.
Another efficiency gain of this model-based approach was the use of double, triple or multi-coded points to define more than one object or line with a single point measurement. “Using conventional surveying, the field crew would sometimes reshoot a point again and again,” Marston says. “For example, if there was a power pole with a phone line connected to it, they would have to first shoot and code the power pole, then reshoot it but code it as a phone line. With our model-based approach, we can define multiple points with a single shot.”
Flexible field coding was also useful for documenting the large amount of vegetation that had to be surveyed. “Throughout the garden, the trees, shrubs, perennials, and annuals all have identification plaques with the name of the plant,” Dunevant says. “The surveyors included those names, often with information about the size of the plant, in the field codes. When the field data was uploaded to the model, the names were automatically imported as well. We didn’t have to rely on cryptic field notes or, even worse, go back out to identify the plants. It came along for free.”
One of the most important advantages of the model-based workflow was the ability to incorporate and react to changes. “In the past, any manipulation of the terrain model--moving it horizontally or changing vertical data for example--was basically a redo,” Marston says. Any change or update meant recreating the terrain model, redrawing the contour lines, and recreating contour labels and spot elevations. “But by using a dynamic model, there was no editing or reprocessing needed,” Marston continues. “If we needed to incorporate a new spot elevation, for example, the terrain model, the contours and the associated annotation were updated instantly. We could see, in real time, the effect of any edits we made.”
The bottom line, Marston says, is that modeling significantly reduces both field and processing time. “With a model-based approach, we’re working in a 3D world from field to finish. We’re not flattening 3D field data onto 2D sheets. We don’t have to wait until the field work is done to process the survey data and we don’t have to manipulate that data. We’re not redoing things when changes or updates occur. The whole process is just faster.”
Dunevant agrees. “On average, we’re cutting our time by at least 30 percent,” he reports. “But more than that, model-based workflows and technology help us improve our accuracy and overall quality, and ultimately deliver a better product to our clients.”