GEOM2001 L1-4
Quiz yourself by thinking what should be in
each of the black spaces below before clicking
on it to display the answer.
Help!
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| GIS | Integrates hardware, software and data for capturing, managing, analysing and displaying all forms of geographically referenced info
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| Spatial data | unique geographic coords or other spatial identifiers that allow the data to be located in geographic space
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| 6 parts of GIS | Hardware, software, people, data, procedures, all connected to a network
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| Normative GIS questions and examples | Practical and decision making/design applications
Eg. managing traffic flows
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| Positive GIS questions and examples | Discovery or the advancement of science, incorporates normative thinking
Eg. Where is global warming having the greatest impact on natural systems
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| 4 GIS architecture types | Desktop, centralised desktop, client-server and centralised server
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| What are some major challenges in representing landscapes in a GIS | 1. The world is infinitely complex and GIS can't represent all of the infinite complexities
2. Hard to try and abstract the real world
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| Continuous field | Vary continuously over a landscape eg. temp, humidity,rainfall, elevation
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| Discrete objects | Have discrete boundaries and are homogenous within the boundary eg. streets, buildings
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| Data model | set of constructs for representing objects and processes in the digital environment of a computer
Reality -> conceptual model -> logical model -> physical model
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| Raster | Grid cells, each cell contains info about spatial location and cell value
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| Benefits of raster | -Simpler to do calculations
-Cells are the same size
-Easy to find cells
-Uniformity of grid makes it simpler to work with
-Useful for representing continuous fields
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| Vector | Points, lines or polygons used to represent discrete data
Each point/line/polygon contains info on its spatial location and info about what it is
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| 4 types of raster data | Base layers - aerial photos
Thematic layers - land use
Surface layers -elevation
Attribute features - geotagged pictures
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| Limitations of raster | -Have to put in data for each cell, can be tedious with large datasets
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| Run length encoding | Simple way of reducing/compacting amount of numbers needed in a raster dataset
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| Spatial attribute data | Where something is on the earth's surface, location
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| Non-spatial attribute data | What an object actually is
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| Topology | Geometric characteristics that don't change under transformations
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| 3 elements to topography | Adjacency, connectivity and containment
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| Georeferencing | Concerned with identifying where geographic features are on the earth’s surface
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| Geographic coordinate system | Longitude and latitude define unique points on earth's surface and referenced to a Datum
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| Longitude | -180 to +180
Measured from Prime Meridian
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| Latitude | -90 to +90
Geodetic latitude requires knowledge of the earth's shape
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| Projected coordinate system | transforms a 3D GCS to a flat 2D coord system
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| Conformal projection | Preserves shapes of features - useful for navigation
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| Equidistant projection | Preserves distances - useful for calculating distances
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| Equal area projection | Preserves area of features - useful for calculating areas
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| True direction (azimuthal) projection | Preserves direction with respect to the centre - useful for navigation
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| Universal Transverse Mercator (UTM) | Minimal distortion of areas and distances
Cylindrical projection based on Transverse Mercator
World split into 60 zones
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| Data capture | Collection of geographic info from the real world and representing that digitally in GIS
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| 5 step data collection process | Planning, preparation, digitizing/transfer, editing, evaluation
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| Primary data capture | collect data directly into digital form, involves direct measurement of spatial info
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| Secondary data capture | taking spatial data used for other purposes and then using that data to be represented in a GIS
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| In-situ data capture | Collecting data actually at the location
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| Remotely sensed data capture | Not at location when collecting data
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| Examples of primary raster data | Digital remote sensing images, digital aerial photos
Mainly remote sensing
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| Examples of primary vector data | GPS measurements, survey measurements, ground surveying
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| Examples of secondary vector data | Topographic surveys, Placename data sets available from atlases, manual digitising
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| Examples of secondary raster data | Scanned maps, DEMs from maps
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| Describe how GPS works | Measures time the signal takes between location to satellite and measures the distance and narrows it down to a location on the earth’s surface
Trilateration - requires 3 satellites to get an approximate location and 4 for accurate location
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| 3 types of primary raster data resolution | Spatial - measure of the smallest angular or linear separation between 2 objects
Spectral - describe the specific wavelengths that the sensor can record within the electromagnetic spectrum
Temporal-how often a sensor can obtain imagery of an area
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| Passive primary raster data | Detect natural radiation that is emitted or reflected by the object or surrounding areas eg.photography, infrared
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| Active primary raster data | uses its own energy source for illumination, sensor emits radiation which is directed toward the target and the radiation reflected from the target is detected and measured by the sensor eg LiDAR
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| Georeferencing | Process of connecting a spatial data set to a coord system
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| Positional accuracy | Measures how close the geographic coords of features in a spatial data layer are to their real world geographic coords
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| Attribute accuracy | accuracy of the non-spatial attributes of geographic features
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| Logical consistency | having the same rules and logic applied through a dataset
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| Completeness | How complete a data set is
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| Metadata | Data about the data
Gives info on how, when, where, who collected data, coord system, data quality and accuracy
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| Difference between GIS maps and traditional maps | Differ in terms of mode, objective, scope of communication and level of interaction between map and user
GIS maps store data, provides real-time decision support, simulations and integrates non-spatial stat analyses
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| Bias in maps | Reflect the dominant power at the time
Map projection can cause distortions
Data accuracy errors
Human errors
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| Thematic mapping | Represent and illustrate spatial structure, patterns and interrelationships rather than just the location of geographical phenomena
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| Nominal data | unordered, qualitative categories eg land use, land cover classes, soil type
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| Ordinal data | ordered categories eg high, medium, low
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| Interval data | quantitative, represent positions along continuous number lines
Values are on a linear calibrated scale but not relative to a zero point in time and space
Eg Temp in C & F, year, pH value scale
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| Ratio data | quantitative, values are derived to a fixed zero point on a linear scale
There’s an absolute zero which allows the use of maths operations (+,-,/,*)
Eg distance, age, weight, length, temp in Kelvin and area
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| Equal interval | same intervals in each category
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| Quantile break | equal amount of members in each category
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| Natural breaks | plot as a chart, grouping close characteristics
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| Limitations of different data classification | Inappropriate classification may hide meaningful patterns and anomalies or give misleading info
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| Map design principles | Legibility, visual contrast, figure-ground organisation and hierarchical structure
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