Integration of attribute data

1. Integration of attribute data • Actions requiring no spatial properties • comparing income levels, computing measures such as average income • actions using only spatial properties • determine parcels in floodplain • actions that combine both • determine parcels in flood plain that have an assed value > 2,000

2. Pre-computation of spatial properties • determine all streets that are connected to HY 71 • can perform analysis at time question asked or store as attributes in database on each node • storage improves performance • pre-computations can present problems if data are dynamic • some processes that store spatially derived data in database can yield complex database structures and other problems

3. Geo-relational model for data • tables for attributes and other tables for coordinates (and possibly topological properties) • example find all parcels that arre worth more than $2,000 that are in the flood plain • step one: database query to parcel table to find polygon identifiers that are worth more than $2,000 • step two: similar search to land use to find flood plain polygons • step three: perform polygon overlay • step four: associate both land use and parcel data to each new polygon • create map/do report etc.

4. Some details of the geo-relational model

5. Allocations of attributes in geo-relational models Land Ownership Parcel ID Owner Address 123 Brown Rt 3 456 Smith Main Street Soil type soil map ID pH texture AA 4.5 loam BB 5.6 sand Joint key unit ID Parcel ID soil map id 10000 123 AA -- OR -- Soil/parcel table unit ID parcel id owner address soil id Ph texture

6. Planar network operations • paths • shortest, fastest, avoids obstacles, passes by passengers, or package drop off/pick up • facility siting • place gas station on transportation network that is intersection of street with interstate • allocation • place school at point where enough students are within 3 miles

7. Street networks • strict planar structure is inadequate to reflect connectivity/flow through network • one way streets • turn restrictions • flow restrictions • traffic density changes through time • flow restrictions often termed impedances

8. Network turn restrictions

9. Attributes for transportation networks • Dyads are commonly used • traffic planning • market studies • offsets related to construction design • dynamic segmentation • partitioning of linear data at locations NOT defined by a node • very common transportation data issue • reflects difference between an attribute view and a topological view • can be based on insertion of (pseudo) nodes or via new attribute data tables

10. Routing and allocation factors Traffic Count Street ID 8 AM 9 AM 10 AM ... • centers • school, warehouse etc. • has capacities • number of students, • volume of packages • loads • student addresses • package pick up

11. Creating regions • common problem • school districts • voting districts • store marketing areas • cell phone service areas • basic problem is to distribute smaller units into some aggregate that meets defined characteristics • smaller units may be • polygons (census blocks) • points (student addresses) • Issues • can overlap? Can have enclaves (holes)? Is all territory to be allocated?

12. Location problem solving • use of a transportation network to define areas of interest • means applying (in turn) routing - allocation and district delineation

13. Example set of district criteria • substantially equal in population • one piece with no holes • do not have “unusual” shape • recognize major natural features (e.g. rivers) • where feasible avoid battles w/ incumbents • don’t dilute minority voting strength • recognize existing communities of common interests

14. Region/district creation

15. Map overlay operations • the “logical” operators of union, intersection etc. have spatial equivalents

16. Polygon overlay w/ lines and points

17. Maps or themes Cartographic Modeling “flowcharting” operations