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.

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

Part 1. Understanding Spatial Data Structures

Introduction to GIS

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

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

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

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

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

• 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

Raster and Vector representations of the same terrain

Introduction to GIS

Raster: great for surfaces Vector: limited with surfaces

Introduction to GIS

Raster and Vector representations of the same

land use

Introduction to GIS

Raster and Vector representations of the same

land use: closer in

Vector vs. Raster: bounding

Introduction to GIS

Raster: bad with bounding Vector: boundary precision

Introduction to GIS

Vector vs. Raster: Sample pointsCancer rates across space

• 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

WHEN TO USE RASTER OR VECTOR???

Introduction to GIS

• 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

• 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

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

• 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

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

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

• 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

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

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

• 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

• 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

Part 2. Brief Intro to the Vector Data Model

Introduction to GIS

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

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

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

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

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

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

• 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

• 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

Vector Topology helps deal with:

Introduction to GIS

overshoots

slivers

dangles

Not sharing border

• 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

• 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

Vector Topology TableConsists 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

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

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

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