1. Lecture 3: Introduction to GIS Part 1. Understanding Spatial Data Structures Part 2. An introduction to the Vector data model Lecture by Austin Troy, University of Vermont

2. Part 1. Understanding Spatial Data Structures Introduction to GIS

3. Perception, Semantics, and Space How do we deal with representing semantic constructions of spatial objects, like “mountain,” “river,” “street,” “city,” How about representing more conceptual semantic constructions like “temperature,” “migration pattern,” “traditional homeland,” “habitat,” “geographic range,” etc? Answer: we have various data models which use different abstractions of reality Introduction to GIS

4. Entities and Fields There are two general approaches for representing things in space: –Entities/ Objects: precise location and dimensions and discrete boundaries (remember, points are abstractions). –Fields, or phenomena: a Cartesian coordinate system where values vary continuously and smoothly; these values exist everywhere but change over space

5. Entities and Boundaries There are two general types of boundaries, bona fide and fiat (D. Mark, B. Smith, A. Varzi) Pure bona fide boundaries represent real discontinuities in the world, like roads, faults, coastlines, power lines, rivers, islands, etc. Pure Fiat boundaries are a human cognitive or legal construction, based on a categorization, such as administrative unit, nation state, hemisphere Some have elements of both, like soil type areas Introduction to GIS

6. Two major data models Entity approach roughly corresponds with the vector model Field approach roughly corresponds with raster model Any geographic phenomenon can be represented with both, but one approach is usually better for a particular circumstance Introduction to GIS

7. Raster Spatial features modeled with grids, or pixels Cartesian grid whose cell size is constant Grids identified by row and column number Grid cells are usually square in shape Area of each cell defines the resolution Raster files store only one attribute, in the form of a “z” value, or grid code. Consider the contrary…. Introduction to GIS

8. Vector layers either represent: –Points (no dimensions) –Lines, or “arcs” (1 dimension) or –Areas, or “polygons” (2 or 3 dimensions) Points are used to define lines and lines are used to scribe polygons Each point line or polygon is a “feature,” with its own record and its own attributes Introduction to GIS Vector

9. Raster and Vector representations of the same terrain Introduction to GIS Raster: great for surfacesVector: limited with surfaces

10. Introduction to GIS Raster and Vector representations of the same land use

11. Introduction to GIS Raster and Vector representations of the same land use: closer in

12. Vector vs. Raster: bounding Introduction to GIS Raster: bad with boundingVector: boundary precision

13. Introduction to GIS Vector vs. Raster: Sample points Cancer rates across space

14. In Arc View and Arc GIS, we can covert vector layers to grids, based on an attribute, or grids to vector layers The disadvantage of vector to raster is that boundaries can be imprecise because of cell shape Each time you convert, you introduce more error too Moving between vector and raster Introduction to GIS

15. WHEN TO USE RASTER OR VECTOR??? Introduction to GIS

16. where boundaries are not precise that occur everywhere within a frame and can be expressed as continuous numeric values where change is gradual across space where the attribute of a cell is a function of the attributes of surrounding cells Raster data analysis is better for representing phenomena: Introduction to GIS

17. Simple file structure Simple overlay operations Small, uniform unit of analysis Raster technical advantages : Introduction to GIS Raster technical disadvantages : Big file size, especially for fine-grained data Difficult and error-prone reprojections Square pixels are unrealistic

18. Vector analysis is better : Where there are definable regions Where the relative position of objects is important Where precise boundary definition is needed Where multiple attributes are being analyzed for a given spatial object For modeling of routes and networks For modeling regions where multiple overlapping attributes are involved EG: units with man-made boundaries (cities, zip codes, blocks), roads, rivers Introduction to GIS

19. Smaller file size (in general) More graphically interpretable Allows for topology (see further on) Vector technical advantages : Introduction to GIS Vector technical disadvantages : Complicated file structure Minimum mapping units are inconsistent between overlapping layers

20. Specific Vector Usages All legal and administrative boundaries (zip codes, states, property lines, land ownership) Building footprints and 3-D models Roads Bedrock geology Pipelines, power lines, sewer lines Flight paths and transportation routes Coastlines Introduction to GIS

21. Specific Raster Usages Terrain modeling where micro-locational variability is present and matters Groundwater modeling, where surface flow outside of channels is important Representation of slope and aspect Representations of distance and proximity to features Spatial representation of probabilities (logit) Modeling phenomena in nature with continuous spatial variability and numeric attributes, like soil moisture, depth to bedrock, percent canopy cover, vegetative greenness index, species richness index Introduction to GIS

22. In many cases, though, the choice between raster and vector may not be so clear. Often it depends on the application The following are some examples where you could go either way: Tossups Introduction to GIS

23. Soil Soil type: Vector –Soil types are meant to represent discrete and homogeneous areas and are qualitative. There is no “slight gradation” between soil types like with pH Soil pH: raster –pH is numeric, not categorical, and that number may vary slightly within a single soil type polygon –If pH were turned into categories, like High, Medium and Low, vector might be better Introduction to GIS

24. Rivers Most people think of a river as a discretely bounded entity, hence vector What about where the river size fluctuates seasonally, e.g. desert rivers? Or where the location of the river bed changes slowly and gradually over the years Or where the river becomes delta, and the distinction between “river” and “swamp” becomes fuzzy? Or where the river has a certain probability of flowing or being dry at any given location and time Introduction to GIS

25. Depends on the type of analysis being done With vector can do network modeling of stream and river system, but only in the arcs –Vector stream model can take advantage of topologically enabled analysis tools With raster, can do surface flow modeling –More realistic, because when it rains water flows everywhere, not just in channels, shows accumulation –Think of every piece of land as mini stream channel Rivers Introduction to GIS

26. Vector works well for modeling vegetation stand type where categories are broad, e.g. mixed conifer, deciduous hardwood Raster works better where there is micro-locational heterogeneity in species distribution Raster also works better for representing ecotones, or edges between two stands The more specific and variable the classification, the more likely the raster approach will be needed Vegetation Mapping Introduction to GIS

27. Part 2. Brief Intro to the Vector Data Model Introduction to GIS

28. Intro to Vector Recall that there are three basic “feature” or “object” types in the vector data type: –Point –Arc –Polyons In general a given layer holds a given feature type (e.g. “roads” is a line layer, “counties” is a polygon layer, “weather stations” is point) Introduction to GIS

29. Intro to Vector A point layer only consists of a bunch of (x,y) coordiantes In a line (arc) layer, points define lines In a polygon layer, lines define areas Hence each level of vector features builds on the last Introduction to GIS

30. Intro to Vector Each point has a unique location 2 points define a line segment One or several line segments define an arc The endpoints of an arc are “nodes The angle points are “vertices” (sing. Vertex) The feature is the arc, not the line Two arcs meet at the nodes Introduction to GIS

31. Intro to Vector Several arcs can scribe a polygon Polygons are closed regions whose boundaries are made up of line segments connected at many angles. Polygons generally define an area of homogenous phenomena (e.g. forest stand, building, zip code, lake) These phenomena can be described by one or more stored attributes Introduction to GIS

32. Vector Representation:lines Ring: this is a series of line segments (a string) that close upon each other It is NOT a polygon!! The computer does not know that the area inside “belongs” to that object Introduction to GIS

33. Vector Representation:lines A polygon is encoded differently, because the computer “knows” that the areas within those arcs “belongs” to that polygon, while it does not with a ring Introduction to GIS

34. Topology: spatial relationships between objects are encoded; the spatial location of each point, line and polygon is defined in relation to every other point, line and polygon Topology allows for behaviors of objects in relation to other objects to be defined Topology allows for powerful analysis tools and can significantly reduce error and increase quality Vector files in ARC INFO are topologically encoded. Arc GIS 8.3 geodatabases will be as well. Currently geodatabases are partially topological Introduction to GIS Vector: Topology

35. One of the most important functions of topology is ensuring data quality and “logical consistency” When you bring in line and polygon data from external sources, you will often find errors such as lines (arcs) that dangle or overshoot, polygons that don’t close, adjacent polygons that show up as not sharing a border (we’ll return to this later in the semester) Introduction to GIS Vector Topology: purpose

36. Vector Topology helps deal with: Introduction to GIS overshoots slivers dangles Not sharing border

37. A topological structure helps ensure these problems don’t happen because it allows for enforcing of user-defined spatial rules ArcGIS 8.3 (coming soon) will include new tools for defining and validating topology rules Topology can also be used for defining spatial rules between layers to minimize errors and ensure logical consistency between them Introduction to GIS Vector Topology

38. Say we have the following layers: property lots, sidewalk, building footprints, zoning map We can specify topological rules, like: –Lots must be enclosed polygons –Buildings must be entirely within a lot –Sidewalks must be outside a lot polygon –Lots must fall entirely within a single zone –Lots must either share a border with another lot or with city land, including streets and sidewalks. –In a low-density zone, no more than 20 lots can be touching We can’t do this yet, but will be able to shortly Introduction to GIS Topology rules: Example

39. Vector Topology Table Consists of four elements 1.Polygon topology table Lists arcs/links comprising polygon 2.Node topology table Lists links/arcs that meet at each node 3.Arc, or “link” topology table Lists the nodes on which each link/arc ends and polygons to right and left of each link/arc, based on start and finish nodes 4.Table with real world coordinates for each point Introduction to GIS

40. Vector Topology Table Graphical display of arcs, nodes, vertices and lines Topology table for the ARCs making up the polygons A table of the polygon topology Introduction to GIS

41. Spaghetti Data Model Just because feature looks like a point, line or polygon does not mean it’s topological Spaghetti Model is: Non-topological data model that looks like vector collections of line segments and points with no real connection or topology Only stores features coordinates; there are no relative relationships encoded in this model each feature has no knowledge of other features that it intersects, is adjacent to, contiguous with or near Introduction to GIS

42. Spaghetti Data Generally have loose ends, nodes not “snapped,” polygons don’t fully close, etc Polygons defined by coordinates of circumscribing points, so common boundaries between two polygons are often registered twice. Generally come from CAD files or digitizing They often look fine to the user, but are useless from the standpoint of spatial analysis This approach is memory inefficient Can “clean” these data, using user-defined tolerances Introduction to GIS