Geospatial modeling system providing building roof type identification features and related methods

• US 7,752,018 B2
• Filed: 07/20/2006
• Issued: 07/06/2010
• Est. Priority Date: 07/20/2006
• Status: Active Grant

• Current Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Original Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Inventors: Rahmes, Mark, Connetti, Stephen, Yates, Harlan, Smith, Anthony O'Neil
• Primary Examiner(s): Rodriguez, Paul L
• Assistant Examiner(s): OSBORNE, LUKE R
• Application Number:
  US11/458,839
• Publication Number:
  US 20080021683A1
• Time in Patent Office: 1,447 Days
• Field of Search: 703/1, 703/2, 382/181
• US Class Current: 703/2
• CPC Class Codes: G06F 30/13 Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
• CPC Class Codes: G06V 20/176 Urban or other man-made structures

Abstract

A geospatial modeling system may include a geospatial model database and a processor. The processor may cooperate with the geospatial database for identifying a building roof type defined by building roof data points as being from among a plurality of possible building roof types. This may be done based upon applying multi-directional gradient calculations to the building roof data points.

Claims

1. A geospatial modeling system comprising:

a geospatial model database; and

a processor cooperating with said geospatial model database for identifying a building roof type defined by building roof data points as being from among a plurality of possible building roof types based upon applying multi-directional gradient Robert'"'"'s cross calculations to the building roof data points using a grid centered for each building data point, summing distances of opposite sides in the grid, and identifying building roof data points whose sum is within a threshold from zero as being localized peak data points, the multi-directional gradient Robert'"'"'s cross calculations comprising eight-way Robert'"'"'s cross calculations.

2. The geospatial modeling system of claim 1 wherein said processor identifies the building roof type as being from among a flat roof type, a sloped roof type, a complex sloped roof type, and a domed roof type.

3. The geospatial modeling system of claim 1 wherein said processor further removes ground and vegetation data points from geospatial model data to select the building roof data points.

4. The geospatial modeling system of claim 1 wherein the multi-direction gradient Robert'"'"'s cross calculations further comprise determining a standard deviation for localized peak data points over a selected building roof area, and if the selected building roof area is greater than a threshold portion of a total building roof area, and if the standard deviation is below a threshold standard deviation, then identifying the building roof type as a flat roof type.

5. The geospatial modeling system of claim 1 wherein the multi-direction gradient Robert'"'"'s cross calculations further comprise removing groups of contiguous localized peak data points being less than a threshold in number.

6. The geospatial modeling system of claim 5 wherein the multi-direction gradient Robert'"'"'s cross calculations further comprise determining if a length of contiguous localized peak data points remains, and, if so, then identifying the building roof type as a sloped roof type.

7. The geospatial modeling system of claim 6 wherein the multi-direction gradient Robert'"'"'s cross gradient calculations further comprise determining a plurality of intersecting lengths of contiguous localized peak data points, and, if so, identifying the building roof type as a complex sloped roof type.

8. The geospatial modeling system of claim 1 wherein said processor further determines whether the building roof data points define a circular shape, and calculates at least one elevation histogram for the roof building data points based thereon.

9. The geospatial modeling system of claim 8 wherein said processor further determines if a standard deviation of the elevation histogram data is below a threshold and, if so, indicates the building roof type as a domed roof type.

10. The geospatial modeling system of claim 1 wherein said geospatial model database stores at least one respective building roof shape for each of the plurality of possible building roof types;

and wherein said processor cooperates with said geospatial model database to substitute in place of the building roof data points the at least one respective building roof shape for the identified building roof type.

11. A geospatial modeling system comprising:

a geospatial model database for storing at least one respective building roof shape for each of a plurality of possible building roof types; and

a processor cooperating with said geospatial model database for

identifying a building roof type defined by building roof data points as being from among the plurality of possible building roof types based upon applying multi-directional gradient Robert'"'"'s cross calculations to the building roof data points using a grid centered for each building data point, summing distances of opposite sides in the grid, and identifying building roof data points whose sum is within a threshold from zero as being localized peak data points, the multi-directional gradient Robert'"'"'s cross calculations comprising eight-way Robert'"'"'s cross calculations, and

substituting in place of the building roof data points the at least one respective building roof shape for the identified building roof type.

12. The geospatial modeling system of claim 11 wherein said processor identifies the building roof type as being from among a flat roof type, a sloped roof type, a complex sloped roof type, and a domed roof type.

13. The geospatial modeling system of claim 11 wherein said processor further removes ground and vegetation data points from geospatial model data to select the building roof data points.

14. A geospatial modeling method comprising:

storing building roof data points in a geospatial model database; and

identifying a building roof type defined by building roof data points as being from among a plurality of possible building roof types using a processor based upon applying multi-directional gradient Robert'"'"'s cross calculations to the building roof data points using a grid centered for each building data point, summing distances of opposite sides in the grid, and identifying building roof data points whose sum is within a threshold from zero as being localized peak data points, the multi-directional gradient Robert'"'"'s cross calculations comprising eight-way Robert'"'"'s cross calculations.

15. The method of claim 14 wherein identifying comprises identifying the building roof type as being from among a flat roof type, a sloped roof type, a complex sloped roof type, and a domed roof type.

16. The method of claim 15 wherein the multi-direction gradient Robert'"'"'s cross calculations further comprise determining a standard deviation for localized peak data points over a selected building roof area, and if the selected building roof area is greater than a threshold portion of a total building roof area, and if the standard deviation is below a threshold standard deviation, then indicating the building roof type as a flat roof type.

17. The method of claim 15 wherein the multi-direction gradient Robert'"'"'s cross calculations further comprise removing groups of contiguous localized peak data points being less than a threshold in number.

18. The method of claim 17 wherein the multi-direction gradient Robert'"'"'s cross calculations further comprise determining if a length of contiguous localized peak data points remains, and, if so, then identifying the building roof type as a sloped roof type.

19. The method of claim 18 wherein the multi-direction gradient Robert'"'"'s cross calculations further comprise determining a plurality of intersecting lengths of contiguous localized peak data points, and, if so, identifying the building roof type as a complex sloped roof type.

20. The method of claim 14 further comprising:

determining whether the building roof data points define a circular shape using the processor; and

calculating elevation histogram data for the roof building data points, and, if a standard deviation of the elevation histogram data is below a threshold, then identifying the building roof type as a domed roof type.

21. The method of claim 14 wherein the geospatial model database stores at least one respective building roof shape for each of the plurality of possible building roof types;

and further comprising using the processor to substitute in place of the building roof data points the at least one respective building roof shape for the identified building roof type.