vector data model Flashcards
Object view of the world (vector)
collection of well defined, discrete and spatially referenced objects
boundaries are well defined
the entire geographic space is not occupied, only where objects exist
each object is indentified and described through the attribute table
time cahnges represented as object location, shape and attribute changes
field view of the world (raster)
events that vary continuously across geographic space
boundaries are fuzzy
the geographic space is mutually exclusive and collectively exhaustive
each space partition is represented by a category or value
time changes represented as a snapshot of cell changes
ways of representing reality
2D: vector, raster
3D: DEM (digital elevation meter)
vector data terminology
data layers: points, lines, polygons/areas
–> features: objects of interest
features
shape and geometry (vertices and edges)
size (map scale cahnges, level of detail)
location (based on coorinate system)
attributes (numbers or text)
spatial relationships (nearness, contain)
new features (created from areas of overlap
specifying geometry for the vector model
point, line, polygon
topology
science and math studying properties of objects that do not change as the object is distorted
degree of connectedness
types of topology
arc node: share endpoint
polygon: share boundaries
route: share segments with other line features
region: overlap with other area features
node: share endpoint vertices with point features
point events: share vertices with line features
raster (natural world)
good for continuous data
better representation of spatial variability
good for data derived from remote sensing
vector (human world)
good fro data with definite boundaries
network analysis capabilities are possible
best fro graphic output
maps as spatial data (draW)
slide 20
levels of measurement
data
info
vaariables: qualitative/quantiative
discrete/continuous
