Lecture 6 - Area Data Flashcards
TYPES OF AREA OBJECTS (2)
Two main types:
- Natural
- Imposed
Can represent with raster grid of cells or vector polygons
The areas can be either planar & non-planar enforced.
GEOMETRIC PROPERTIES OF AREAS (11)
- SHAPE - regular (like circle or square) or irregular
- AREA (size) - accuracy depends on resolution/detail
- PERIMETER
- LONG AXIS & SHORT AXIS
- LARGEST INTERNAL CIRCLE RADIUS
- SMALLEST EXTERNAL CIRCLE RADIUS
- SKELETON
- ASPECT RATIO (width to height) - shows if elongated or square
- COMPACTNESS
- ORIENTATION (dominant angle)
- SPATIAL PATTERN
LOCATION QUOTIENTS
- measures % of activity in an area relative to a % of the same activity in a wider unit
- fraction of local/global rates of an activity
- measures over or under-representation (is a crime in a specific meshblock more than city-wide crime rates?)
- LQ value <1 means under-represented
- LQ value >1 means over-represented
- LD value = 1 means ratio equal to whole
MAPPING APPROACHES
Planimetric Map Cartogram Quantile map Percentile map Box plot (Inter Quartile Range) Standard Deviation
Natural Areas
- self defined / sharp boundaries (lake, forest, mountain, etc)
- mostly homogenous within border
- often homogeneity displayed on map is fiction (some variation within area, ie. land use) for simplicity and ease of use
Imposed Areas
- boundaries are defined independently of phenomenon (by humans)
- a sampling of the underlying reality
often misleading:
- little relationship to underlying patterns
- arbitrary and modifiable (MAUP)
- makes ecological fallacy very real
- gerrymandering
Raster Aerial Objects
- cells identical & cover region of interest (raster or vector grids)
- each cell an area object
- can represent continuous & discrete data
Planar Enforced
- area objects mesh together neatly and exhaust study region (topology - common borders)
- every location fits within area
- no gaps or overlaps
Non-planar enforced
- gaps within area
- entities isolated from each other or overlapped
- more complicated to use for analysis
Largest internal circle radius
What is the radius of the largest circle that can be entirely contained in the shape?
Smallest external circle radius
What is the radius of the smallest circle that can entirely contain the shape inside?
Long axis & short axis
Used to understand length/width and orientation. What is the longest line that can be drawn from one end to the other for a shape in two (perpendicular) directions
Skeleton
Reduce shape into simple lines and vertices
- geometric central points
- tree-like structure
- reduce to a central point farthest from the original boundaries and also the centre of the largest circle inside the shape
Compactness
Measures the area of the object and compares it to the area of a circle with the same perimeter
Compactness score of 1 means the shape is a circle, smaller number more complex irregular shape
Spatial Pattern
look at how many neighbours (shared borders) each shape has
- regular shapes have the same # of neighbours
- complex shapes have different numbers of neighbours, this value is spread around the mode (# that appears most often)
- compare the mode to a random distribution to infer if the shapes are more regular or irregular (smaller than mode = regular, larger than mode = irregular)
What is missing if we just look at points?
Underlying location, population density, etc.
Unit of aggregation
Units of aggregation:
territoral authority, regional aerial units, meshblocks
Use to aggregate the point data/events than analyse in the context of population density, rates, etc. so areas can be compared.
Unit of measurement for area unit variables
- counts
- rates (per 1000 people)
- population density (people/km2)
- location quotient
Planimetric maps
used to map location quotient, shows a bar/column for the areas with over or under-representation which show how much more than the rate of the whole
intuitive but with limitations
Cartogram
a map in which some thematic mapping variable is substituted for land area or distance. Geometry or space of the map are distorted to convey the information of the specific variable
Quantile maps
Map a variable by area divided into 7 (+/-) categories with different colour coding, the categories have an equal range of values
Issues: cannot differentiate between areas in the same colour/category, will also see a difference between two areas but maybe their values are very close but fall in different categories because of how the ranges are set
Percentile map
- ranking maps
- group ranked distributions in 6 categories: 0-1, 1-10, 10-50, 50-90, 90-99, 99-100%
- highlights extremes, the top and bottom 1%, maybe not outliers?
Inter Quartile Range
- put values in a row from small to large
- divide row into four equal parts, then identify the median (middle) and the Inter Quartile Range
- lower IQ value is the median of the 1st and 2nd parts of the set
- upper IQ values is the median of the 3rd and 4th parts of the set
- the IQR is the difference between the upper IQ value and lower IQ value
Box Plot (Hinge)
Denote values 1.5 or 3x the IQR, outside of which values are regarded as outliers
Then map areas based on the quartile they fall in or if they are outliers
Standard Deviation
- find the mean
- highlights differences in units above and below the mean
- typically 7 categories: mean, +3 standard deviations above and below
- helps to see extremes