Flashcards
GIS
Flashcards do conjunto (28)
- 1How would you find data freely?Many publicly funded agencies mandate free access to GIS data – Web is great repository for GIS data (might only be subject to slower download speeds if not purchased -> e.g. QSpatial) – University departments and legacy projects
- 2Where would you buy data?– Government agencies (local council, state/territory, federal) – GIS (re)sellers (check online) – Can be expensive; may not be able to “try before you buy” (quality of data &/or resolution often unknown); layers of interest may be formatted for incompatible software; raster vs. vector availability – If it’s what you need, no further work to do (quick); can share costs with similar users (legal issues with usage license)
- 3How would you modify paid or free data sources an/or layers?Change objects of existing data • Example: You have a layer showing local government authorities (LGAs), but need state boundary. Delete internal lines (merge features) & voilà! – Change attributes of existing data • Example: You have 2007 data layers (businesses and locations) but need 2008 data. Spend a lot of money for mostly same information or spend a bit of time updating 2008 details into your 2007 layer. – Combine existing data (attribute join) • Example: Relate georeferenced map file (e.g. Southport properties) with non-georeferenced data file (e.g. property values or census results), each of which has a common field (e.g. street address, or ‘lotplan’ number)
- 4How Would you create your own data sources?Points and lines from Global Positioning System (GPS) readings GPS = Device to collect readings on ground (latitude, longitude, elevation, speed, time, etc.) as measured by orbital satellites • GPS satellites have built-in error (1 m – 200 m, normally ~ 5 to 20 m), which may affect the accuracy of your final analyses – Digitize from hard copy or scanned images • Plenty of old maps and photos available online or in libraries • May require special hardware (scanner, digitizing table, digitizing puck) and software • Time- and labour-intensive (especially final corrections), but some software allows automation of the process • Georeferencing likely to be less accurate (3D real-world coordinates to 2D map coordinates to 2D screen estimate of coordinates transformed back to 3D coordinates)
- 5What are the three principles errors in GIS?1. Systematic
2.Human
3. Random - 6What is systematic error?(Instrumental/Cumulative) – (generic) problems with the
processes involved with data collection, measure, or analysis
• Can be removed (or sometimes corrected) if caught
– Example: GPS under high atmospheric disturbances will vary wildly from
their “true” positions – usually indicated by some quality index, can be
accommodated (error buffer) or corrected (post-processing differential
GPS)
– Example: automatic conversion of type of attribute when importing EXCEL
file (text instead of numeric); - 7What is Human error?n (unnecessary gross errors/blunders/stuff-ups) – problems
with inattentiveness or carelessness during data collection (manual
entry), review, measure, or analysis
• Tight protocols and post-collection/analysis checks can be used to
minimize, catch, and correct errors
– Example: Mix up of units entered (e.g. different users entered angle
measurement first in degrees then radians)
– Example: typos, e.g. entering text (string) using capital letters in some
cases but not others - 8What is Random Error?(Compensating) – Errors present after first two types of
error have been corrected (= errors not readily explained)
• Can’t be corrected (& often not even detected), only minimized. Assume
these errors throughout & that they all balance out. Or, to minimize total
measurement error, apply function (like square root) to all of your data.
– Example: Snap mode was used at some stage during screen digitizing but
this was not realised, next user started w/ default setting (snap mode was
turned off) & continued;
– Example: “Mistakes” from last week’s workshop. - 9How would you minimise error?Examine your (attribute and spatial) data
• Examine it again, this time more closely (summary stats)
• Share examination duties with a co-worker, supervisor, or
friend so as to have two sets of eyes to pick up any errors
• Read the metadata and compare what is written with what
you see to help pick up any problems
• Get to know your data. Everything may look fine, but
perhaps only because you are unfamiliar with how it should
really look. This takes time and experience
• Keep back-up copies of everything. Maybe any errors
come from your error-checking abilities! You may
inadvertently make changes that weren’t needed - 10What does C.O.A.S.T stand for?-Computational = incorrect interpolations, transformations,
analyses, precision, etc.
-Output/Presentational = shoddy maps
-Attribute= wrong values applied to features
-Spatial/Positional = things in wrong place
-Topological = incorrect spatial relationships - 11How could you have error in Attribute datafiles?Incorrect Values
– Written incorrectly (CAPS, typ0s)
– Field types incorrect
– Information completely wrong
• Missing Values
• Basically, attribute errors - 12Errors in Graphics (Vector map data)Undershoots & dangles,
sliver & weird polygons
– Usually derive from bad digitising
or mismatched overlays
– Can be fixed with snap-, threshold-,
& tolerance-setting
• But this can introduce errors, too
• 3D into 2D (S-road example)
• Basically, spatial and topological
errors - 13Errors in Graphics (Raster)You have less to worry about with rasters
• Basically, spatial errors
• BUT! This increases importance of attribute errors.. - 14How can you end up with error in analysis in terms of map projections?Wrongly applied or transformed projections (often
dependent on scale and place)
Remember your transatlantic cable exercise from the workshops:
– unless you use a projection that is specifically designed for your
feature of interest, you’ll end up w/ an error (sometimes only a very
small one) = just be careful what statement you make based on your
input data (possibly with some small errors) and your analyses
– (another example: ignoring elevation) - 15How can you make an error of anaysis in terms of false precision?Over- or under-generalization (grid cell size & other
examples of false precision)
Frequent mistakes:
– resampling a grid to generate a smaller cell size;
– using GPS readings for analyses of spatial relationships at very
large scales (eg. < 1:200, building footprints on 1 ha block);
– Using weather data interpolated from local weather stations at local
scales (e.g. the Gold Coast City local government area) - 16How can you make an error of analysis in terms of incorrect methodologyIncorrect methodology used during analyses:
– Search distances for spatial analyses set too small or too large
(e.g. for analysing point patterns -> includes too many points or
not enough);
– No removal of (spatial) bias due to spatially clustered
observations….
• Poor interpolative or model rules
– point to raster interpolations: using an algorithm that does not
match the assumed or known behaviour of the attribute variable
(z-value) used.
• Basically, ‘algorithm-selection’ errors - 17How can you make an error within maps?TOSSLAD (more about this in Lecture 7 [map design])
– or SADLOST or LASTSOD or ASSDOLT...
• No metadata
• Presenting erroneous (map extent, scale, etc.) or confusing
information (e.g., reversed colour ramps for elevation or
temperature data)
• Basically, output errors (duh!) - 18What are some common forms of vector data?-Shapefile = proprietary (old ArcView 3.x) format for storing vector and tabular data; not topological; editable
Geodatabase = proprietary (ArcGIS 10.x) format for storing vector, raster and tabular data; can be topological; editable - 19What are some common types of Vector Layers?Cadastre (DCDB) = vector; specialised layer of land parcel/real estate information (ownership, dimensions, cost, etc.), the basis of administrative boundaries, urban planning instruments, land use layers (often used in conjunction with digital orthophotos)
-Road (transport) networks = vector; specialised layer of line network data, the basis for all (car) navigation systems)
-ABS census data = vector; several levels of spatial detail (e.g. suburb to State & Territories), linked to several census attribute tables (or information categories) - 20Common forms of Raster Data?Grid = raster layer as we have seen before (ESRI grid, GeoTIFF, ASCII grid, CSV..
- 21Common types of Raster Layers?DEM (DTM) => special raster = digital elevation model; specialized grid containing elevation values (mostly as height of ground above mean
-Scanned Aerial Photograph = raster; uncorrected photo taken from plane (B/W, colour, IR; low – high altitude)
-Digital Orthophoto = raster; geometrically corrected, aerial photo (no problems with lens distortion, plane angle, etc.)
-Satellite Image = raster; picture taken from orbital satellite - 22Common Types of derived layers- DSM = as DEM raster, digital surface (NOT terrain!!) model, discrete points interpolated to fill in intermediate spaces (any surface, e.g. tree canopy height)
- TIN = triangular irregular network (meshes); vector (nodes and lines) representation of a surface
- geodatabase (gdb) = vector and raster, a special database management system (DBMS) for ArcGIS to enable storage of a wide range of spatial and other data, incl. multiple feature (vector) data, raster data, tables - 23Data within your data base will come in what two forms?- Continuous = Values change throughout space; points in any particular area likely to contain different values; used most often with raster data (if vector, most likely with point layers) • Examples: elevation; pollution levels; rainfall
- Discrete = Values change inconsistently and distinctly through space; points in any particular area more likely to have same value; used most often with vector data (if raster, used to speed spatial analyses) • Examples: habitat type; political names; speed limit - 24What three ways can your data be saved?1. Numeric
2. Text
3. Date - 25What are the three formats are tables stored?1. Spreadsheet or Flat File = All of your records (objects you can see on map) in one basket – similar to using Microsoft Excel to store data
2. Hierarchical (Parent-Child, One-to-Many) = Several tables that are linked by specific field “pointers” • Can think of as branching somewhat like a tree with roots • Assumes “lower-level” data present in only one “higher-level” table • Good for simple analyses, not so much for more difficult analyses
3. Relational (Many-to-One or Many-to-Many) = Records in several tables linked through commonality in data not specific pointers • Most flexible system & particularly suited for database analyses • Most popular format for GIS - 26What is the numeric way for your data to be saved?1. Numeric = Numbers only (no text)
Short Integer = Whole numbers (positive or negative), typically used for coding. Used for lists such as land-use codes, vegetation types, and Booleans (i.e., true/false). Range: +/- 32,768
Long Integer = Whole numbers (positive or negative), typically used to store quantity values such as population figures. Range: +/- 2,140,000,000
Float = Single-precision floating-point numbers that can support numbers with an accuracy to 6 places past the decimal. Floats are used to store simple decimal numbers such as percentages. Range: +/- 3.41,308
Double = Double-precision floating point numbers that can support numbers with an accuracy to 15 places past the decimal. Doubles are used to store decimal numbers with a high level of detail such as latitude and longitude. Range: +/- 3.410,308 - 27What is the text way for you to save data?2. Text (String) = Stores any character string (names, abbreviations, alphanumeric codes, and numeric codes that begin with 0 such as postal codes). Range: 1 – 255 characters
- 28What is the way you can save data by date?3. Date = Stored in Coordinated Universal Time (UTC) format (= time and date at Prime Meridian = 0° +/- 7.5° longitude) and are translated into the current day and time in the local time zone. Range: 1 January 100 – 31 December 9999. • Can take on a variety of formats (and sometimes converted to Text or Numeric), so make sure to error-check if involved in analyses
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- Environmental Studies FlashCards sobre GIS, criado por Duran Sealee em 01-08-2017.
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- Duran Sealee
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