geog281 final test Flashcards
vector data vs. raster data (w/ examples)
vector:
▪ Object-based representation made up of Points, Lines, and Polygons (or Areas)
▪ Uses sets of coordinates and associated attribute data to define discrete objects
▪ Vector Data Models are an intuitive way to represent spatial data that is based on
traditional cartography
raster:
A raster is grid-based representation (i.e., array) of data where every cell contains
a value, which represents some sort of spatial information for that location
▪ Models continuous data
▪ Each cell has a uniform dimension
Raster data models can have multiple bands, i.e., multiple overlapping grids, we
call these multi-band rasters
▪ Multi-band rasters have multiple spatially coincident grids representing the same
spatial area
▪ Common examples of multi-band rasters:
▪ Aerial photo (3 bands; R G B)
▪ Digital image (3 bands; R G B)
▪ Satellite imagery (1 – x bands)
define data and give a geospatial example
gis data is different from regular data becuase of the spatial component
define map scale. what is a small scale map used for.
small scale maps look at large areas like entire provinces
name four organizations responsible for collecting spatial data
google maps
openstreetview
government
ISO, OGC
continuous vs. discrete data
continuous data is like a number (elevation ex), it can be any number
discrete is an occurance and it must be a whole number
describe two different errors in vector geometry
overlapping in topology which makes data hard to view
unconnected polygons
what are two advantages to publishing a map as a web map compared to a static map
more interactive as you can zoom to differnent extents for the data
can see the data in a table perhaps
makes clustered data more readable
what is one issue that can be created whe converting vector data to raster
loss of persion when taking points and turining them into a grid of cells. loss of points lines and polygons.
what is a focal operation
Focal, or neighborhood, operations produce an output raster dataset in which the output value at each cell location is a function of the input value at a cell location and the values of the cells in a specified neighborhood around that location.
DEM vs. DSM
The digital elevation model (DEM)
Foundational dataset used to create
various topographic products and
analysis
▪ Representation of earth’s surface
▪ ‘DEM’ is considered a generic term for
most elevation surfaces
▪ Originally derived from topographic
maps, with spot heights/elevation points
used to create a surface via interpolation
(vector to raster data!)
Digital surface model (DSM
elevation model that contains the elevation of the terrain as well as above-ground features such as buildings, vegetation, towers, and other infrastructure
Define a spatial data infrastructure and give an example
The technology, policies, standards, and human resources necessary to acquire, process, store, distribute, and improve utilization of geospatial data, services, and other digital resource
chose a type of vector geometry and describe how the attribute table and spatial data are connected
point vector geometry
primary key is attribute table
foreign key is spatial data
difference between data quality and data standards (w/ ex)
data quality is how it is presented through the resolution
data standards are rules and regulatations set for users to replicate it or form a deeper understanding
what are the two orgs that oversee the creation of geospatial data standards? what is the difference between these organizations?
iso - international standard organization
ogc - open geopatial consortium
what datasets are required to create a viewshed analysis? describe each of these datasets and explain what steps are required to create a viewshed for locating a scenic outlook over a river valley.
data sets could include
- DEM
- river/water courses
- trails and lookout location
- roads
- other surface elevation considerations
describe how you would take census data of average invcome and create a chloropleth map for a specific canadian city. what steps would you follow.
download data from statcan
can be standalone or joined to a spatial file or as a shapefile for direct use in arcgis pro
the specific census geography could be census tract, DA, csd, cma, etc
the income data would be represented as a chloropleth modfiied by colour based on average income
classification method should be metioned
what is GIS
a computer-based system to aid in the collection, maintenance, storage, analysis, output, and distribution of spatial information
- GIS as a tool (applied and theoretical use)
- GIS as tool-making (technical development)
- The science of GIS (what issues does it raise
How do we represent spatial data
geographic coordinate system:
3d spherical surface to define locations on earth, includes angular unit of measure, a prime meridian, and a datum (based on an ellipsoid/sheroid)
projected coordinate system:
the systematic mathematical rendering of coordinates from a three dimenstional spherical systems to a 2-d cartesian system
How do we define the location of spatial data
Geographic Coordinate System
Ellipsoid: An oval, with a major axis (longer), and a minor axis (shorter)
(Horizontal) Datum: Defines the position of the ellipsoid relative to the
center of the earth (or a local reference point)
Types of map projections
cylindrical
conic
azimuthal
pseudo-cylindrical
can be classified by the following properties:
equal area (equivalent)
conformal
equidistant
compromise
how do we represent spatial data that has elevation values
Ellipsoid: An oval, with a major axis (longer), and a minor axis (shorter)
Horizontal Datum: Define the position of the ellipsoid relative to the center of the earth – measures positions (e.g., latitude/longitude)
Geoid: Gravity-based vertical reference for the shape of the earth
Vertical Datum: Defines the position of the geoid relative to the center of the earth – measures land elevation and water depths
shapefile vs. feature class vs. file geodatabase
Shapefile
▪ A vector data storage format for storing the location, shape, and attributes of geographic features
▪ A shapefile is stored in a set of related files and contains one feature
class
Feature Class
▪ A collection of geographic features with the same geometry type, the same attributes, and the same spatial reference
▪ Stored inside a geodatabase
File Geodatabase (.gdb)
▪ A geodatabase is a container used to
hold a collection of datasets
▪ Uses an efficient data structure that is
optimized for performance and storage. File geodatabases use about
one-third of the feature geometry storage required by shapefiles
▪ Outperforms shapefiles for
operations involving attributes and scales the data size limits beyond
shapefile limits.
▪ Keeps your data neat and organized
topology & topology rules
Topology: management of
relationships of vector representations
▪ Connectivity
▪ Adjacency
▪ Planarity
▪ Having no topology rules enforced in data creation can result in ‘messy’ data,
and severely hinders spatial analysis
RULE: must not overlap as to not create duplicate dataets
The Modifiable Areal Unit Problem (MAUP)
A fundamental challenge in spatial analysis with vector data is that polygons may
be reclassified and grouped in many different ways
▪ MAUP is the effect that point-based measurements of spatial phenomena being
aggregated into arbitrary spatial units has on an outcome or analysis
normal forms in databases and unnormalized
We can place our database into normal forms to avoid issues with updating the database, improve searching capabilities, and to reduce data redundancy
database terminology
Primary Key – A chosen attribute or set of attributes that uniquely
identifies each row in a table
▪ Foreign Key – A chosen attribute or set of attributes in a target table
that may be used to unambigously link to rows in another table
▪ The link created a primary key and foreign key is based on the cardinality
of the relationship
Cardinality - refers to the relationship between data in two tables, and
has 3 common forms
1:1
1:n*
n:n
feature map
Feature Maps are a common way to display vector data as-is
▪ Different cartographic abstraction techniques are used to show where
vector data is
▪ Common to employ feature generalizations, i.e., fuse, simplify, omit, displace, exaggerate, etc
choropleth map
Choropleth maps depict quantitative
information for specific geographic
areas using a color mapping symbology
▪ Polygons define discrete areas, and
each polygon is given a color that
corresponds to values for a mapped
variable (a color gradient is most
commonly used)
▪ The choropleth map is one of the most
common and time-honored
cartographic techniques
dot density and graduated symbols
Dot Density Maps show quantitative
data using dots or symbols to represent
values
▪ Dots are randomly or semi-randomly
placed within a polygon
▪ Graduated Symbol Maps show a
quantitative difference between
mapped data by varying the size of
dots or symbols
▪ Data is classified into ranges that are
each then assigned a symbol size to
represent the range
▪ Graduated symbols show an
aggregated real-world location of the
underlying points
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contour/isopleth maps
Contour/Isopleth maps display
lines of equal value
▪ Used to model vector data as a semi-
continuous surface with discrete
breakpoints, e.g., rainfall, elevation,
temperature
advantages of using raster data model
A simple data structure for continuous data —A matrix of cells with values
▪ The most efficient data format for spatial analysis (think about how easy it is to
write code that performs a function on a 2d array versus an arbitrary list of
coordinates)
▪ Most compact data structure
▪ The ability to uniformly store data
▪ The ability to perform fast overlays with complex datasets with multiple layers
map algebra operators
Operators are different types of spatial extent calculations performed on raster data
(from highest to lowest)
* Local: output is a function of the associated value
* Focal: ouput is function of input
* Zonal: calculates statistics on cell values of a raster (a value raster) within the zones defined by another dataset
* Global: compute an output raster dataset in which the output value at each cell location is potentially a function of all the cells combined from the various input raster datasets
liDAR vs. RADAR
LiDAR – Light Detection and Ranging
▪ Uses light pulses in the near-infrared range (wave lengths of 905nm or 1550nm
typically)
RADAR – Radio Detection and Ranging
▪ Uses radio waves (wave lengths of 2 – 3m)
web mercator projection
a cylindrical, compromise
projection
▪ Used for all ESRI cloud services, like ArcGIS Online, de facto standard for web
mapping
▪ Global Projection
unnormalized
§ Tables with repeat groupings
Common to collect data this way and split/rearranges tables as the database is normalized
first normal form (1nf)
§ No repeat columns
§ Suffers from storage redundancy, inefficient searches, and potential loss of data upon updating
Functional dependancy: attributes are functionally dependant if at a given point in time, each value of the dependent attribute is determined by a value of another attribute
second normal form (2nf)
§ No repeat colums and every non-key attrubute is functionally dependent only on the primary key, or on transitive functional dependencies of the primary key
§ Tables in 2NF have transitive functional dependencies (chain of dependencies), which may cause data loss when the database is updated
Get rid of duplications caused by overlapped
third normal form (3nf)
§ All tansitive functional dependencies must be removed to achieve 3NF
§ Should know that tables in 3NF have no functional or transitive functional dependencies
NO DATA DUPLICATION
