FRST 328 GIS

TERMS & CONCEPTS

The following is a listing of the material with which you should know.  It forms the basis of test material.  Obviously wording on tests will vary from what is presented below. 

Introduction to GIS (links provided go to the ESRI GIS Dictionary)

• in YOUR OWN WORDS, define/describe GIS (geographic information system)

• compare GISystems, GIScience, GIStudies

• not including da Boss, describe three types of GIS "jobs"

Spatial Data

• define spatial referencing (aka georeferencing)

  • differentiate between geographic vs. Cartesian coordinates

  • define: graticule, ellisoid, geoid, datum, MSL

• define datum and why it's important for GIS

  • provide 4 examples of spatial datums

• define map projection and why it's important for GIS

  • what 2 map projections are commonly used in BC for natural resource mgmt

• state meaning for the acronyms (for spatial data): NTS, BCGS, TRIM, VRI, TEM, SEI

Build a Geodatabase

• your mission, build a geodatabase for a new Woodlot - outline how you would approach this task

•  define and be able to compare: scan & digitize, manual & heads-up digitizing, cogo, geocoding

• define remote sensing and describe how it relates to GIS

• what is image classification

• how does traverse data makes it's way into a GIS?

Cartography

• Briefly describe basic map elements

• Describe what maps communicate (relates to Dr. Seuss)

• describe, in some detail, cartographic (map) design

Classification

• be able to define the methods and to classify data according to

  • quantile

  • equal-interval

  • natural break methods

  • std. deviation

• as per the link "How to Choose", outline the advantages/disadvantages of each method of classification

Database & Attribute Data

• define (and provide examples as appropriate)

  • database, DBMS

  • field, field name, record

  • primary key (key field), secondary key (foreign key), unique identifier

  • field types: text/string, short & long integer, single & float real numbers

  • precision & scale

• outline the advantages of database

• list 3 parts of a query

• differentiate between the Boolean operators: and, or, not  ... provide examples for each

• describe how database relates to GIS

• describe/differentiate each of the following

  • database relations

  • join vs. link (relate)

  • destination vs. source tables

  • one-one vs. many-one vs. one-many relations

Vector Analysis

• briefly describe (and provide examples and diagrams) for the following spatial analyses:

  • buffer

    • single vs. multiple ring vs. variable width

    • inside / outside of polygon

    • dissolve interior boundaries

  • "combine"

    • append

    • merge

    • dissolve

  • query by location (select by location) - intersect, contain, within, within a distance of

  • spatial join 

  • overlay

  • union

  • intersect

  • clip

  • update

  • erase

  •  

  • network routing

    • analyses

      • (911) - shortest path (quickest path considers speed of traffic)

      • efficient routing (many stops)

      • location-allocation (allocate area to points, e.g. school catchment, customer area for business)

    • factors in analysis

End for Midterm

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Analytical (Cartographic) Modeling

• Describe basic components (how to) of an analytical model

• Create an analytical model - based on a scenario provided (i.e. starting data sets and a desired end result)

Spatial Data Modeling

• Terms:

  • discrete objects vs. fields

  • vector vs. raster

  • pixel, pixel resolution, extents,

  • spatial entity types, topology

• Describe data modeling

  • describe each phase of data modeling

  • for any given real world phenomena (e.g. lakes, wetlands, lookout towers, roads, etc.) discuss how it could be captured in both the conceptual and logical data models

  • What are the five spatial entity types (point, line, network, polygon, surface) and provide examples for each and describe how they relate to the conceptual model

• Describe how discrete objects ( a point, a line, a polygon) are represented in a vector model ... in a raster model

• Describe how continuous variables are represented in a vector model ... in a raster model

• Compare the spaghetti and topology vector models

• Describe the generic file structure of a raster file; also what type of data is contained in the 'header' or 'world file'

• Compare the advantages (disadvantages) of vector vs. raster

• Note we are NOT covering the details regarding the Physical Model - all you need to know is that the physical model is the actual "digital structure" (i.e. "the computer code") and each software will have a different physical model.

Raster Analysis

• Define/ describe

  • pixel, cell, resolution, extents

  • 'surface', mask, Boolean/logic layer

  • relative path, absolute path

  • math operators, math functions
     

• briefly describe (and provide examples and diagrams) for the following spatial analyses:

  • reclassify

  • raster calculator

    • 'raster overlay' (combining logic layers)

    • applying a formula to pixels in a layer to derive a map with new information (units)

    • mathematically combining layers (e.g. add, subtract, ratio, etc.)
       

  • spatial interpolation

    • generally, what is it

    • how does IDW work?

    • describe characteristics of interpolation methods:

      • local vs. global

      • exact vs. approximate

      • gradual vs. abrupt

      • deterministic or stochastic

    • compare IDW and spline

  • surface analyses

    • contours, slope, aspect

    • hillshading (applications)

    • viewshed

  • proximity

    • (straight-line) distance surface

    • describe how to create a buffer in raster

Data Acquisition

• Define: COGO, rubber sheeting, edge-matching, primary & secondary data sources, metadata, data warehouse

• List primary & secondary data sources

• what is the difference between 'tablet digitizing' and 'heads-up' digitizing?

• What are the other 5 types of generalization (provide diagrams)

• what is topology and what are it's benefits (there are 2: one relates to analysis and the other to data)

• Define: "noise", COGO, point mode digitizing, stream mode digitizing, map registration, loops/spikes, over/undershoots, rubber sheeting, edge-matching, primary & secondary data sources, metadata, data warehouse

• Describe the 'GIS data stream' (and provide a diagram)

• With regards to digitizing:

  • list the steps in the digitizing process; what step is most time consuming?

  • What is 'prepping/cleaning a map'?

  • what is the difference between 'tablet digitizing' and 'heads-up' digitizing?

• With regards to scanning a map:

  • compare flatbed vs. drum scanners

  • what happens to dashes and symbols?

  • list the steps in scanning; what step is the most time consuming?

• With regards to editing

  • what are the typical errors that need to be corrected?

  • what types of functions are carried out in "geo-processing"?

  • differentiate between edge matching and rubber sheeting

  • what are the 2 types of map generalization that are particular to digital maps?  Which type is more likely to be used with stream-mode digitizing?

  • What are the other 5 types of generalization (provide diagrams)

• what is topology and what are it's benefits (there are 2: one relates to analysis and the other to data)

Data Quality

• Define/ describe

  • error/uncertainty, resolution, MMU, metadata

  • completeness vs. consistency vs. compatibility vs. applicability

  • absolute and relative positions

  • nominal vs ordinal vs interval vs ratio measurement scales

  • primary vs secondary data

• Discuss sources of error/ uncertainty regarding spatial data in GIS (be sure to include: data modeling, data capture, encoding, integration and output)

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