University of Palestine Faculty of Applied Engineering and Urban Planning GIS Course Spatial Analysis Eng. Osama Dawoud 1 st Semester 2009/2010

Content Retrieval, classification and measurement Measurement Spatial selection queries Classification Overlay functions Vector overlay operators Raster overlay operators Neighbourhood functions Proximity computation Spread computation Seek computation Network analysis

Analytical GIS Capabilities There are many ways to classify the analytic functions of a GIS. The classification used for this lecture makes the following distinctions in function classes: Measurement, retrieval, and classification functions Overlay functions Neighbourhood functions Connectivity functions

Retrieval, classification and measurement Measurement : Measurements on vector data Measurements on raster data

Retrieval, classification and measurement Measurements on vector data: Location, Length, Area, Minimal Distance Minimal Bounding Box determines the minimal rectangle—with sides parallel to the axes of the spatial reference system—that covers the feature.

Measurement Length (Lines) by Pythagorean theorem Area (Polygons) by dividing the polygon into triangles whose areas can easily be calculated 1 2 D

Retrieval, classification and measurement Measurements on raster data: The geometric information stored with the raster data is: Horizontal and vertical resolution, and the location of an anchor point so all other measurements by the GIS are computed. The anchor point is fixed by convention to be the lower left (or sometimes upper left) location of the raster.

Spatial selection queries Spatial selection by attribute conditions

Spatial selection queries Spatial selection using topological relationships Inside Intersect Adjacent In distance with

Classification An example classification: Anderson Land Cover classification (Anderson et al., 1976) 1 urban or built-up 2 agricultural 3 rangeland 4 forest deciduous forest 42 evergreen forest 43 mixed forest

Classification Line Dissolve (Map Dissolve) 1 grain crops 2 orchards 3 residential 4 commercial 1 agricultural 2 non-agricultural

Overlay Functions These functions (Operators) are as follows: polygon intersection spatial join polygon clipping polygon overwrite

Overlay A series of registered data layers ‘overlaying’ each other Arguably the most important GIS analysis function

Overlay Derived from manual cartographic overlay using Mylar sheets (transparent plastic) that were physically overlaid on top of one another.

Overlay An overlay operation takes two or more data layers as input and results in an output data layer Three types of overlay: Point in polygon Line in polygon Polygon (polygon on polygon)

Point in Polygon Overlay A B C ID Tree A Elm B Maple C Elm Point Table ID Tree Cover A Elm Rural B Maple Rural C Elm Urban Point Table ID Cover 1 Rural 2 Urban Poly Table 12 + A B C= Land CoverTreesNewTrees

Line in Polygon Overlay A B C ID Street A Race B Race C Arch Line Table ID Street Cover A Race Rural B Race Urban C Arch Urban D Race Urban Line Table ID Cover 1 Rural 2 Urban Poly Table 12 += Land CoverStreetsNewStreets A B C D

Polygon Overlay Intersection (and)Union (or) Identity

Polygon Overlay: Intersection Agriculture A B A Land Cover ID Owner A Brown B Smith ID Cover A commercial B industrial B Area of intersection New node

Polygon Overlay: Intersection Output ID Owner Cover A Brown commercial B Smith industrial A B Area of intersection New node

Polygon Overlay: Union Agriculture A B A ID Owner A Brown B Smith ID Cover A commercial B industrial B Area of union New node Land Cover

Polygon Overlay: Union Area of union New node Output ID Owner Cover A commercial B Brown commercial C Brown D Smith E Smith industrial A BC DE

Polygon Overlay: Identity Agriculture (input layer) A B A Land Cover (identity layer) ID Owner A Brown B Smith ID Cover A commercial B industrial B Area of identity New node

Polygon Overlay: Identity Area of identity New node Output ID Owner Cover A Brown commercial B Brown C Smith D Smith industrial AB CD

Raster Overlay GISs that support raster processing - as do most - usually have a full language to express operations on rasters.

Neighbourhood functions To perform neighbourhood analysis, we must: 1.state which target locations are of interest to us, and what is their spatial extent, 2.define how to determine the neighbourhood for each target, 3.define which characteristic(s) must be computed for each neighbourhood.

Neighbourhood functions Proximity computation: 1.Buffer zone generation 2.Thiessen polygon generation

Neighbourhood functions

Buffer Definition of what is within/without a given proximity Point buffer Line buffer Polygon buffer

Doughnut Buffer e.g. within 10 meters but not within 5 meters 10 5 Buffer polygon ‘Hole’

Variable Buffer Buffer distance varies by some feature attribute or friction surface

Variable Buffer Buffer polygon A B C ID Dist A 3 B 2 C Original line

Neighbourhood functions

Table 12.3 Computing water use based on land-use area Node Total Node Area (ha) Land Use Type Land Use Area (ha) Unit Demand (l/day/ha ) Demand (l/day) Node Total (l/day) J-16.88Industrial6.8811,20077,100 J Industrial Commercial Residential ,200 4,700 7,500 15,500 4,300 40,400 60,200 J Commercial Residential Undeveloped ,700 7, ,100 38, ,800 J Industrial Commercial Residential Undeveloped ,200 4,700 7, , , ,800 J Industrial Commercial ,200 4,700 72,500 7,600 80,100 J Industrial Commercial Residential ,200 4,700 7,500 2,200 6,400 24,800 33,400

Network Analysis A network is a connected set of lines, representing some geographic phenomenon, typically of the transportation type. Network analysis can be done using either raster or vector data layers, but they are more commonly done in the latter, as line features can be associated with a network naturally, and can be given typical transportation characteristics like capacity and cost per unit.

Network Analysis