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Review: Exam I GEOG 370 Instructor: Christine Erlien Slide 2 Learning Goals: Ch 1 To be able to define GIS and describe the components necessary to working with GIS To be able to describe the reasons (and advances) that allowed for the development of the first GIS systems To be able to define CAC and CAD and compare their capabilities with those of GIS Slide 3 Learning Goals: Ch 1 To be able to describe the steps of the cartographic process and the differences between traditional cartography and GIS To be able to describe the GIS subsystems and how they differ from traditional cartographic map production Slide 4 GIS: Geographic Information Systems GIS is built on collective knowledge Geography Cartography Computer science Mathematics Many definitions, depending on whom you ask Demers (our textbook) cites Marble & Pequet (1983), who talk about what we do with a GIS and how we do it Slide 5 Data: Both spatial and temporal Spatial: Related to the space around us Temporal: Related to time The what and how of GIS: Data input subsystem: Collecting & preprocessing data Data storage & retrieval subsystem: Retrieval, updating, editing Data manipulation & analysis subsystem: Analysis & modeling Reporting subsystem: Display What this boils down to: GIS is an information system that allows for capture, storage, retrieval, analysis and display of spatial data. Marble and Pequet (1983) Slide 6 Computer hardware Software Data management and analysis procedures Spatial data People needed to operate the GIS Components necessary for Doing GIS Slide 7 The rise of GIS Canada, early 1960s, Dr. Roger Tomlinson Need: inventory & map natural resources A huge task, aided by advances in computing technology Computers: vacuum tubes transistors Faster, more reliable, cheaper Larger memories information storage as well as calculations possible Mainframe used had 512K of memory!!!! IBM develops the drum scanner to scan lines on maps 1 st in the world Interested in more history? See http://www.casa.ucl.ac.uk/gistimeline/ http://www.casa.ucl.ac.uk/gistimeline/ for an interactive timeline Slide 8 How does GIS differ from CAC and CAD? Computer-aided cartography (CAC): Primarily used in map-making (display) Computer-aided drafting (CAD) Used by architects to produce graphic images (display) Images not linked to descriptive files What key capability of GIS is lacking in both CAC and CAD? Slide 9 Cartographic Process Cartographic process: The steps in producing a map, beginning with data collection & resulting in a map product. Data Collection Data Processing Aggregation, classing, etc. Map Production Slide 10 Comparing traditional cartography & GIS: Inputs Traditional Data sources Aerial photography Digital remote sensing Survey Census & statistical data Data recorded as points, lines, areas on paper or Mylar GIS Data sources Same, plus DLGsDLGs DEMsDEMs Digital orthophotoquadsDigital orthophotoquads Data recorded as points, lines, areas using electronic devices Slide 11 Comparing traditional cartography & GIS: Storage & Retrieval Traditional Storage: points, lines, areas drawn on map Retrieval: Map reading GIS Storage: Points, lines, areas stored with spatial reference data (coordinates) & pointers Tables of characteristics (attributes) associated with coordinates Retrieval: Computer tracks where data are stored Slide 12 Comparing traditional cartography & GIS: Analysis & Output Traditional Analysis: Limited to data as presented on map Output: Mapping GIS Analysis: Allows access to raw data can change aggregation or classification, or analyse further Output: May include maps, tables, charts Slide 13 Learning Goals: Ch. 2 To be able to explain how real world objects may be generalized in the digital environment, and how their representation may change based on the scale of observation To be able to explain the difference between and identify examples of discrete and continuous data To be able to identify differences between nominal, ordinal, interval, and ratio scales. To also be able to discuss factors that may determine which spatial measurement levels we use. Slide 14 Learning Goals: Ch. 2 To understand the necessity for a grid system for determining locations as well as the meaning of absolute versus relative location To be able to describe spatial patterns and relationships using terms such as random, regular, clustered, orientation, arrangement, diffusion, density, and spatial association To be able to explain how data collection may differ for small versus large areas and discuss the different the use of ground sampling methods for data collection Slide 15 Generalizing Real World Objects Point Location only Line 1-D: length Made up of a connected sequence of points Polygon 2-D: length & width Enclosed area Surface 3-D: length, width, height Incorporates elevation data Slide 16 Slide 17 Generalizing Spatial Objects Representing an object as point? line? polygon? Depends on Scale (large scale vs. small scale) Data Purpose of your research Example: House Point (small scale mapping) Polygon 3D object (modeling a city block) Slide 18 Data: Continuous vs. discrete Continuous Data values distributed across a surface w/out interruption Examples: elevation, temperature, LULCelevationtemperatureLULC Discrete Occurs at a given point in space; at a given spot, the feature is present or not Examples Points: Town, power pole Lines: Highway, stream Areas: U.S. Counties, national parks Slide 19 Slide 20 http://weather.unisys.com/surface/sst.gif Slide 21 LULC http://landcover.usgs.gov Slide 22 http://maps.unc.edu/MapBook/Index.asp Slide 23 Continuous & discrete? Some data types may be presented as either discrete or continuous Example Population at a point (discrete) Population density surface for an area (continuous) Slide 24 http://www.citypopulation.de/World.html Population: Discrete Slide 25 http://sedac.ciesin.columbia.edu/gpw/ Population: Continuous Slide 26 Generalities Continuous data Raster Discrete data Vector Slide 27 Spatial Measurement Levels Three levels of spatial measurement: Nominal scale Ordinal level Interval/ratio Slide 28 Measurement Levels & Mathematical Comparisons Nominal scale Not possible Ordinal scale Compare in terms of greater than, less than, equal to Interval/ratio scales Mathematical operations Interval: addition, subtraction Ratio: add, subtract, multiply, divide Slide 29 From ESRI Map Book Volume 18, ESRI (2003) Slide 30 A B C From Mapping Census 2000, Brewer & Suchan (2001) Slide 31 From ESRI Map Book Volume 18, ESRI (2003) Slide 32 Spatial Location and Reference Communicating the location of objects Absolute location Definitive, measurable, fixed point in space Requires a reference system (e.g., grid system such as Latitude/Longitude) Relative location Location determined relative to other objects in geographic space Giving directions UTM Slide 33 Spatial Location and Reference: Geographic Coordinate System (lat/long) Lines of latitude are called parallels Lines of longitude are called meridians Slide 34 Latitude / Longitude Prime Meridian & Equator are the reference points used to define latitude and longitude Slide 35 Slide 36 Spatial Comparisons Pattern analysis: An important way to understand spatial relationships between objects. Three point distribution patterns: Regular: Uniform Clustered Random: No apparent organization Slide 37 Slide 38 A B C Slide 39 Describing Spatial Patterns Proximity: Nearness Orientation: Azimuthal direction (N,S,E,W) relating the spatial arrangement of objects Diffusion: Objects move from one area to another through time Density: # of inhabitants, dwellings, etc., per unit area Slide 40 Collecting Geographic Data Small areas Ground survey Census Large areas Census (less often every 10 years) Remote sensing GPS (e.g., collared animals) Slide 41 Collecting Geographic Data: Sampling & Sampling Schemes Sampling: When a census isnt practical Types of sampling Directed: Particular study areas selected based on experience, accessibility, etc. Probability-based: For the total population of interest, each element has a known probability of being selected Slide 42 Sampling & Sampling Schemes Probabilistic sampling methods Random: Each feature has same probability of selection Systematic: Repeated pattern guides sample selection Homogeneous: Similar characteristics throughout the study area Stratified: Characteristics vary throughout study area (subdivisions internally homogeneous) Features sampled w/in subdivisions Slide 43 Probabilistic sampling methods