Leadership in Energy and Environmental Design (LEED) is a certification program that encourages the adoption of sustainable design, construction and operation practices as applied to buildings and communities. Think of LEED as a way of promoting a green approach to community development.
From a civil engineering perspective, LEED for Neighborhood Development (LEED ND) is an opportunity to bring together engineering design and GIS analysis methods in order to meet a set of documented requirements for achieving LEED certification. For example, the Smart Location and Linkage category encourages brownfield developments to reduce urban sprawl. Maximum credit can be attained if the project is located in a previously developed infill site that is also in a high-density area. In this case, high-density is a function of the number of street intersections within a half-mile of the project boundary.
To determine how well a project complies with these criteria, we can apply an Engineering GIS approach that leverages both CAD and GIS data. First, rather than using an import/export method to bring together the required data, FDO data providers are used to connect the GIS-based parcel and street centerline data to the CAD-based site design. Next, a geospatial buffer is created at a distance of a half-mile from the site boundary. The buffer is used to determine proximity and involves generating a polygon at a specified distance from the proposed site boundary. Finally, in this simplified example, a geographic query is used to determine the number of intersections within the buffer and this number is compared to the LEED criteria.
Some of the benefits of this approach include the following:
From a civil engineering perspective, LEED for Neighborhood Development (LEED ND) is an opportunity to bring together engineering design and GIS analysis methods in order to meet a set of documented requirements for achieving LEED certification. For example, the Smart Location and Linkage category encourages brownfield developments to reduce urban sprawl. Maximum credit can be attained if the project is located in a previously developed infill site that is also in a high-density area. In this case, high-density is a function of the number of street intersections within a half-mile of the project boundary.
To determine how well a project complies with these criteria, we can apply an Engineering GIS approach that leverages both CAD and GIS data. First, rather than using an import/export method to bring together the required data, FDO data providers are used to connect the GIS-based parcel and street centerline data to the CAD-based site design. Next, a geospatial buffer is created at a distance of a half-mile from the site boundary. The buffer is used to determine proximity and involves generating a polygon at a specified distance from the proposed site boundary. Finally, in this simplified example, a geographic query is used to determine the number of intersections within the buffer and this number is compared to the LEED criteria.Some of the benefits of this approach include the following:
- Data conversion and data redundancy can be avoided as a result of using FDO data providers to connect to the data directly rather than relying on an import/export process.
- Efficiency is improved as a result of applying an approach that embraces CAD tools for site design and geospatial tools for analysis all in one software platform.
- Better designs are possible because more design alternatives can be evaluated against LEED criteria.
Check out the video to see the process in action using AutoCAD Map 3D.
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3 comments:
Thanks for creating the video. It's a good intro to the fundamentals of buffering and node counting.
I'm interested in the definition of intersection type "F" that you used in the query. There was a complex intersection next to the project parcel with several street centerlines running through it. At first, each centerline intersection was marked with a node, but after you ran the query, the whole intersection was simplified to one node, which is correct for LEED-ND. That's a handy function.
The process you outlined is good for getting a first estimate. But please be careful with the definition of connectivity in LEED-ND. The definition counts alley-street intersections, but not alley-alley intersections. The definition counts nonmotorized path-street intersections, up to 20% of the total.
And the most complex part of the definition is that "If one must both enter and exit an area through the same intersection, such an intersection and any intersections beyond that point are not counted". This is intended to filter out pods in the street network that function as dead ends on a multiple-street scale.
The upshot of the LEED-ND connectivity definition is that some hand counting may be required. I haven't yet heard of an algorithm that can filter dead end pods, but hopefully someone will figure that out.
Laurence Aurbach
http://pedshed.net
Thanks for your comments Laurence. Regarding the intersection nodes where Type='F', each node was manually classified according to its applicability to LEED NC criteria. All non-applicable nodes where given a Type value of ‘F’. Unfortunately, the street centerline data that was available to me, did not classify the intersections to the degree I needed for this analysis; hence, the need for manual classification. I also tried to validate each node post process. As you indicated, additional manual review of the intersections may be required to ensure accurate counts (eg dead ends on a multiple-street scale). A more automated method for classifying the intersections would certainly make this analysis easier. Even so, the buffer analysis does give one an opportunity to get a rough intersection count very quickly which is useful when multiple sites are being considered.
I believe construction of such projects requires knowledge of engineering and management principles and business procedures, economics, and human behavior.
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