Measurements in the field
Digitized maps or images
Interpolations from point sources
Estimates from out of the blue
Geometric data (x and y coordinates) and attribute data
point, lines and polygons
They are stored in a file of database
Dimensionless
A point has one pair of X Y coordinates
Each point have a unique ID-value
Have one dimension
Consist of ordered coordinate pairs
Each line segment has a start node and end node
Inbetween one or more vertices (breakpoints)
Attributes valid for the segment is linked through the ID value
Created by a line that enclose the polygon area
Have two dimensions, X and Y
Expect homogenity inside
Has a simple structure
Non topological
Stores geometrical location and attribute information in seperate files
Stores the feature geometry
stores the attribute info
reference system
link between geometry and the attributes
Storage problems (boundaries are stored twice)
Neighbor searches complicated (entire list of coordinates are searched until an identical pair is found)
Island polygons are hard to handle
The shared border coordinates are stored once, but still problems with island polygons
knowledge of the geometrical relationships and connectivity between objects
Shared lines stored once
Island polygon: easier to find
Different tables for describing different aspects of the topolgy
Simple polygon if only drawing maps
Topological polygon structure for effective spatial search and spatial analysis
It is used to analyse numerical data in databases
The purpose is to perform queries in a well defined structure
Select (columns)
From (which table)
Where (criteria)
Either alternative works
both criteria needs to be fulfilled
Geometrical objects (vector or raster)
With attribute objects (more information about the object)
Flat file system
Hierarchial file system
Network file system
Data organized in tables
Uses 'keys'
one to one (one file)
one to many (hierarchial = one parent many children)
one to many, many to one
many to many (many tables can be related in many different ways)
Avoid redundancy
For each table we must define name and column
Make many small tables
Relations are made when needed
Hybrid storage (stores spatial data and attribute data seperately, the format is shape format)
Object based data model (combines geometries and attributes in one system, format is geodatabase)
e.g. name, gender, specie
Rank ordered, totally agree/mostly agree
Temperature, aspect
Distance, area, income
Point, line, area
Normalize data and use single color grading from light to dark
selection of mapping method
classification of data into groups
selection of colors and symbols
labelling attributes
Natural breaks
Equal intervals
Quantiles
Standard deviation
Population density
basic colour we perceive, eg 12 steo wheel
lightness or darkness - Can be hard to perceive variations in value
intensity or purity compared to a neutral grey
simplification
smoothing
aggregation
merging
collapsing
displacement
Base layers
Thematic map
Computation of distance b/w 2 features
Calculating length of line objects
Calculating polygon areas
Calculating line intersections
as-the-crow flies = Pythagorean Theorem
sum of segments b/w start and end node
DEM analysis
airline routes
Points in polygons
Lines in Polygons
Polygons in polygons
Decide which points lie in which polygon
Transfer the attributes from the polygon to the points that fall within them (one-to-many)
Result: point layer with their original + polygon attributes
Find intersection between lines and polygon borders
Lines divided into new objects
Decide which new line fall into which polygon
Transfer attributes from polygon to corresponding new line objects
Length and area
Slivers
Clip
Dissolve
Merge
Eliminate
Same principle as polygon on polygon overlay but no attribute from clip layer included in the table
Uses attribute values to aggregate unit polygons into new, larger polygons which contain at least one common attribute from the smaller polygon
To remove slivers. Used to eliminate polygons with an area less than a certain threshold value.
Bringin together two adjacent data layers in order to create a larger database = map matching
Map projection
Generalisation
Precision (data type)
Shape file
Geodatabase
A three dimensional surface
All points on the surface have an equal distance to the center
end of the rotational axis
An imaginary line on the surface halfway
Halves of great circles that all come together at the poles
the angle between the plane of the prime meridian and that of the meridian through a point for east/west direction
Imaginary lines parallel to the equator
We use the rotational ellispoid model
ellipsoid + where to place the ellipsoid in relation to earth
earth or local
Centre of ellipsoid = centre of earth's mass
and suits fairly everywhere
Surface of ellipsoid
very suitable in some location, in others not
equipotential surface in the Earth gravity field.
geoid - ellipsoid
height above sea level/geoid
height above the ellipsoid
system that helps us to define a location/spot on earth
The ellipsoid model
A location of ellipsoid
A coordinate system
The plane touches earth at one point. Good for small areas and for visualisation
Normal: cylindric touches the equator
Transverse: cylindric touches the prime meridian
Oblique: cylindric touches a great circle somewhere else
Normal: the cone touches the globe along a parallel
Oblique: cone touches the globe anywhere
zero
The furhter from the prime meridian
local scale equals principal scale
Local scale is reduced
Local scale is increased
Preserves the relative sizes of geographic features. Distort the shape of features
Preserves the local shapes. The relative size of geographic features changes.
Standard meridian
A suitable projection model
How/where to locate the model
Apply a plane coordinate system
It defines where the cylinder touches the earth model. Also defines the origin of the plain coordinate system.
to estimate the coordinate pair of a point when you know the angle and distance to a point with known coordinates.
Space segment
Control segment
User segment
4
Yes, GPS uses its memory and knowledge about the earth as a sphere to cancel one of the points. But accuracy is better when using 4 satellites.
Ephemeris errors (difference between expected and actual location of satellite)
Troposphere/ionosphere/atmosphere
Clock errors
Environmental disturbance
Multiple path reflection
At least 4 satellites
Satellite configuration (DOP)
Reduce risk for multi path reflection
Time for GPS to stabilize
The represented surface, e.g. the elevation in an area, is divided into a number of raster cells
Pixel, the building stones of a raster