Introduction to Geographic Information Systems Miles Logsdon

GIS - consists of: zComponents yPeople, organizational setting yProcedures, rules, quality control yTools, hardware & software yData, information zFunctions yData gathering yData distribution

Geographic Data ( i.e. not spatial information ) zSpatial Data ylocation yshape yrelationship among features zDescriptive Data yattributes, or ycharacteristics of the features Spatial Data: the spatial attribute is explicitly stated and linked to the thematic attribute for each data item.

Spatial Information zThree Attributes of Geographic Data that constitutes Information yThematic (Value Variable) xNominal, … name, label xOrdinal, … rank ordered xInterval / Ratio, … measurement on a scale ySpatial (location) yTemporal After Sinton, 1978: Components of spatial information: time, space, theme (attribute) Sounds obvious. One must be fixed, one controlled, one measured.

Spatial - thematic value types Sta. 94, DOC 4.9 WELL 200’ 100’ 200’ Former Land Fill URBAN Duvall, pop 1170 FOREST AGRICULTURE Snoqualmie River, 1 Brush Creek, 2 Stream,3

Geographies Layers, Coverages, Themes Land use Soils Streets Hydrology Parcels

Concept of Spatial Objects z POINTS z LINES z AREA

Spatial Encoding - RASTER POINT LINE AREA

Spatial Encoding - VECTOR POINT- x, y LINE - x1, y1 - x2, y2. - xN, yN Area (Polygons) - x1, y1 - x2, y2. - xN, yN (closure Point) * a single node with NO area * a connection of nodes (vertices) beginning with a “to” and ending with a “from” (Arcs) * a series of arc(s) that close around a “label” point

Vector - Topology Object Spatial Descriptive x1,y1 x2,y2 x3,y VAR1 VAR2 Fnode Tnode x1y1, x2y2 1 2 xxyy, xxyy 2 3 xxyy,xxyy 10, 11, 12, 15 10, ……

Raster Data Model

Set Selections Reduce Select - RESEL GT 5 = [ ] Add Select - ASEL EQ 5 = [ ] Unselect - UNSEL GE 9 = [ ] Null Select - NSEL = [ ] [ ]

AND, OR, XOR AND= 2 OR XOR = 1,2,3 = 1

Spatial Overlay - UNION # attribute # IN attribut OUT attribute ABCDABCD A A 102 B 102

Spatial Overlay - INTERSECT # attribute # IN attribut OUT attribute ABCDABCD A 102 B 102 A 103 B

Spatial Overlay - IDENTITY # attribute # IN attribut OUT attribute ABCDABCD A A 102 B 103 B

Spatial Poximity - BUFFER Constant Width Variable Width

Spatial Poximity - NEAR Assign a point to the nearest arc

Spatial Proximity - Pointdistance ,045 1,899 1,743 DISTANCE

Spatial Proximity - Thiessen Polygons

Map Algebra In a raster GIS, cartographic modeling is also named Map Algebra. Mathematical combinations of raster layers several types of functions: Local functions Focal functions Zonal functions Global functions Functions can be applied to one or multiple layers

Local Function Sometimes called layer functions - Work on every single cell in a raster layer Cells are processed without reference to surrounding cells Operations can be arithmetic, trigonometric, exponential, logical or logarithmic functions

Local Functions: Example Multiply by constant value X 3 = Multiply by a grid X =

Focal Function Focal functions process cell data depending on the values of neighbouring cells We define a ‘kernel’ to use as the neighbourhood for example, 2x2, 3x3, 4x4 cells Types of focal functions might be: focal sum, focal mean, focal max, focal min, focal range

Focal Function: Examples Focal Sum (sum all values in a neighborhood) = = Focal Mean (moving average all values in a neighborhood) (3x3)

Zonal Function Process and analyze cells on the basis of ‘zones’ Zones define cells that share a common characteristic Cells in the same zone don’t have to be contiguous A typical zonal function requites two grids a zone grid which defines the size, shape and location of each zone a value grid which is processed Typical zonal functions zonal mean, zonal max, zonal sum, zonal variety

Zonal Function An Example Zonal maximum – Identify the maximum in each zone Useful when we have different regions “classified” and wish to treat all grid cells of each type as a single “zone” (ie. Forests, urban, water, etc.) =

Global function In global functions - The output value of each cell is a function of the entire grid Typical global functions are distance measures, flow directions, or weighting measures. Useful when we want to work out how cells ‘relate’ to each other

Golbal Function An Example Distance Measures – Euclidean distance based upon cell size Or – some function which must consider all cells before determining the value of any cell – (“cost” associated with a path across the surface) =

Examples outgrid = zonalsum(zonegrid, valuegrid) outgrid = focalsum(ingrid1, rectangle, 3, 3) outgrid = (ingrid1 div ingrid2) * ingrid3

Spatial Modeling Spatial modeling is analytical procedures applied with a GIS. Spatial modeling uses geographic data to attempt to describe, simulate or predict a real-world problem or system. There are three categories of spatial modeling functions that can be applied to geographic features within a GIS: geometric models, such as calculating the Euclidean distance between features, coincidence models, such as topological overlay; adjacency models (pathfinding, redistricting, and allocation) All three model categories support operations on spatial data such as points, lines, polygons, tins, and grids. Functions are organized in a sequence of steps to derive the desired information for analysis. The following references are excellent introductions to modeling in GIS: Goodchild, Parks, and Stegaert. Environmental Modeling with GIS. Oxford University Press, Tomlin, Dana C. Geographic Information Systems and Catograhic Modeling. Prentice Hall, 1990.