System, apparatus and method for mapping

• US 7,979,205 B2
• Filed: 11/12/2010
• Issued: 07/12/2011
• Est. Priority Date: 12/18/2003
• Status: Expired due to Fees

• Current Assignee: 1626628 Ontario Limited
• Original Assignee: 1626628 Ontario Limited
• Inventors: Burchfield, Marcy L., Geile, Wolfhard, Coombes, Anthony C.
• Primary Examiner(s): Black; Thomas G
• Assistant Examiner(s): LOUIE, WAE LENNY
• Application Number:
  US12/944,905
• Publication Number:
  US 20110074783A1
• Time in Patent Office: 242 Days
• Field of Search: 701/208, 701/50, 703/1, 455/3.01, 705/35
• US Class Current: 701/208
• CPC Class Codes: G01C 21/3852 Data derived from aerial or satellite images
• CPC Class Codes: G06T 11/20 Drawing from basic elements, e.g. lines or circles
• CPC Class Codes: G06V 30/422 Technical drawings; Geographical maps
• CPC Class Codes: G09B 29/10 Map spot or coordinate position indicators; Map reading aids optical projection apparatus per se G03B
• CPC Class Codes: G09B 29/106 using electronic means

Abstract

The present invention provides a novel apparatus and method for mapping of urban regions. An apparatus includes the remote sensing equipment that is connected to a computer processor. The remote sensing equipment gathers imaging data about an urban region. The computer processor interprets the imaging data to generate a map of the urban region comprising representations that identify a first set of indicia representing physiographic characteristics, a second set of indicia representing different types of built forms, and a third set of indicia representing patterns of human activity associated with both the physiographic characteristics and the built forms. The map can also include a fourth set of indicia representing an intensity level that at least one of the other types of indicia occurs.

Claims

1. An apparatus for generating a map comprising:

at least one input device for receiving a first set of data of an urban region representing physiographic characteristics,

a second set of data of said urban region representing different types of built forms and their locations and a third set of data of said urban region representing patterns of human activity inferred from said different types of built forms;

associated with both said physiographic characteristics and said built forms;

a microprocessor connected to said input device operable to determine different types of entities for each said set of data; and

a user output device connected to said microprocessor for generating a representation of at least one precinct;

each precinct occupying an area less than an area of said map;

each precinct comprising indicia respective to each set of data that corresponds to said entities.

2. The apparatus of claim 1 wherein said indicia is presented in a graphical form that includes a plurality of precincts, each of said precincts defined by areas within said region that have a predefined set of common indicia.

3. The apparatus of claim 1 further comprising the step of associating an intensity level associated with each set of indicia.

4. The apparatus according to claim 1 wherein said first set of data and said second set of data are obtained from remotely sensed data sources.

5. The apparatus according to claim 1 wherein said third set of data is obtained from census data.

6. A computer-implemented method of generating a map comprising:

receiving, in at least one processing unit, remotely sensed data of an urban region that includes a plurality of built forms;

determining, using said at least one processing unit, a type of each said built form in said remotely sensed data based on a comparison of said built forms found in said remotely sensed data with a known database of a plurality of different types of built forms; and

generating, using said at least one processing unit, user output containing indicia identifying said determined type of each built form in said region, said user output presented in a graphical form that represents said region and including a location of each said built form according to said determined type.

7. The computer-implemented method of claim 6 wherein said database contains data representing at least one of a detached house, a semi-detached house, a row house, a mid-rise apartment building, a high-rise apartment building, and a single detached trailer, a mid-rise office building, a high-rise office tower, a main street shop building, a strip mall, a shopping mall, a big box store, a factory, a road, a highway, an electricity transmission right of way, a railway.

8. The computer-implemented method according to claim 6 wherein said user output is in a graphical form that represents said region;

said graphical form including a plurality of squares bounded by a set of coordinates on a grid;

each of said squares representing a predominance of said determined type of built form located in each said square.

9. The computer-implemented method of claim 6 wherein said graphical user output further includes a plurality of precincts, each said precinct formed based on groupings of substantially identical built forms within a predefined area of said region.

10. The computer-implemented method of claim 9 wherein said precinct is formed based on at least one additional criteria in addition to built forms.

11. The computer-implemented method of claim 10 wherein said at least one additional criteria includes at least one of a user selection, political boundaries, physiography, and human activity.

12. The computer-implemented method of claim 6 wherein said determining additionally includes determining said type of said built forms based on at least one artifact within said remotely sensed data;

said at least one artifact corresponding to at least one identifier stored in said known database;

said identifier associated with a corresponding known type of a built form.

13. The computer-implemented method of claim 12 wherein said known type of a built form is an apartment building;

said artifact including plurality of squares within a rectangular;

said at least one identifier corresponding to said artifact being a pair elevator shafts.

14. The computer-implemented of claim 13 wherein said at least one artifact including a shadow;

said at least one identifier corresponding to a first one of said artifacts being a first shadow of a first length;

said at least one additional identifier corresponding to a second one of said artifacts being a second shadow of a second length greater than said first length;

wherein said determining step includes corresponding said shadows to a respective one of said built form types.

15. The computer-implemented method of claim 14 wherein said first shadow corresponds with a house and said second shadow corresponds with an apartment building.

16. The computer-implemented method of claim 14 wherein said first shadow corresponds with an apartment building and said second shadow corresponds with an office tower.

17. The computer-implemented method of claim 14 wherein said known type of a built form is a house;

said artifact is an inclined roof;

said at least one identifier corresponding to said artifact being a peak line in said roof.

18. The computer-implemented method according to claim 6 further comprising, after said determining:

receiving data representing physiographic characteristics of said urban region; and

receiving data representing patterns of human activity associated with both said physiographic characteristics and said built forms, and wherein said user output further contains indicia identifying said physiographic characteristics and said patterns of human activity in relation to said built forms.

19. The computer-implemented method of claim 18 wherein said built forms include residential built forms;

said patterns of human activity include residence corresponding to said residential built forms and said intensity level includes an occupancy rate respective to said residential built forms.

20. The computer-implemented method of claim 18 wherein said patterns of human activity includes at least one of residential, administrative, retail, manufacturing, employment, office, and transportation.

21. The computer-implemented method of claim 18 wherein said patterns of human activity are based on at least one corresponding one of said built forms.

22. The computer-implemented method of claim 18 wherein said patterns of human activity include residential activities and said corresponding one of said built forms includes at least one of a house and an apartment building.

23. The computer-implemented method of claim 18 wherein said patterns of human activity includes administrative activities and said corresponding one of said built forms includes an office tower.

24. The computer-implemented method of claim 18 wherein said patterns of human activity includes retail activities and said corresponding one of said built forms includes at least one of a strip mall, a shopping mall and a big box store.

25. The computer-implemented method of claim 18 wherein said patterns of human activity includes manufacturing and said corresponding one of said built forms includes a factory.

26. The computer-implemented method of claim 18 wherein said patterns of human activity include transportation and said corresponding one of said built forms includes at least one of a road or a highway, or a railway.

27. The computer-implemented method of claim 18 further comprising, prior to said generating:

receiving data representing a level of intensity associated with at least one of said physiographic characteristics, said patterns of human activity and said built forms and wherein said user output further contains indicia representing-said level of intensity.

28. The computer-implemented method of claim 18 wherein said physiographic characteristics include a plurality of types of physiography;

said patterns of human activity include a plurality of types of activity; and

said built forms include a plurality of types of built forms.

29. The computer-implemented method of claim 28 wherein said level of intensity is expressed as a percentage, such that a total of said level of intensity for each of said types of physiography totals 100%;

and a total of said level of intensity for each of said types of activity totals 100%; and

a total of said level of intensity for each of said types of built forms totals 100%.

30. A computer-implemented method of generating a map of an urban region comprising:

receiving, in at least one processing unit, a first set of data of an urban region representing physiographic characteristics;

receiving, in said at least one processing unit, a second set of data of said urban region representing built forms and their locations;

receiving, in said at least one processing unit, a third set of data of said urban region representing patterns of human activity associated with both said physiographic characteristics and said built forms;

wherein said patterns of human activity are inferred from said types of built forms;

determining, using said at least one processing unit, different types of entities for each said set of data; and

generating, using said at least one processing unit, user output containing a representation of at least one precinct occupying an area less than an area of said map;

each precinct comprising indicia respective to each set of data that corresponds to said determined entities.

31. The computer-implemented method according to claim 30 wherein said user output is in a graphical form that includes a plurality of precincts, each of said precincts formed based on areas within said region that have a predefined set of common indicia.

32. The computer-implemented method of claim 30 further comprising associating, using said at least one processing unit, an intensity level associated with each set of indicia.

33. The computer-implemented method according to claim 30 wherein said first set of data and said second set of data are obtained from remotely sensed data sources.

34. The computer-implemented method according to claim 30 wherein said third set of data is an electronic representation of census data.