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Introduction to Geographic Information Systems (GIS) SGO1910 & SGO4930 Fall 2005 Karen O’Brien Harriet Holters Hus, Room 215 [email protected]. Announcements. Questions about home pages? Mid-term quiz: September 27 (chapters 1, 3, 4, 5, 6). Review. Spatial Data Models - PowerPoint PPT Presentation
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Introduction to Geographic Information Introduction to Geographic Information Systems Systems
(GIS)(GIS)
SGO1910 & SGO4930SGO1910 & SGO4930 Fall 2005 Fall 2005
Karen O’BrienKaren O’BrienHarriet Holters Hus, Room 215Harriet Holters Hus, Room 215
[email protected]@sgeo.uio.no
AnnouncementsAnnouncements
• Questions about home pages?Questions about home pages?
• Mid-term quiz: September 27 Mid-term quiz: September 27
(chapters 1, 3, 4, 5, 6)(chapters 1, 3, 4, 5, 6)
ReviewReview
• Spatial Data Models Spatial Data Models
• Conceptual and Digital Conceptual and Digital RepresentationsRepresentations
• Discrete Objects and FieldsDiscrete Objects and Fields
• Vector and RasterVector and Raster
Discrete ObjectsDiscrete Objects
• Points, lines, and areasPoints, lines, and areas
• CountableCountable
• Persistent through time, perhaps Persistent through time, perhaps mobilemobile
• Biological organismsBiological organisms– Animals, treesAnimals, trees
• Human-made objectsHuman-made objects– Vehicles, houses, fire hydrantsVehicles, houses, fire hydrants
FieldsFields
• Properties that vary continuously over Properties that vary continuously over spacespace– Value is a function of locationValue is a function of location– Property can be of any attribute type, Property can be of any attribute type,
including directionincluding direction
• Elevation as the archetypeElevation as the archetype– A single value at every point on the Earth’s A single value at every point on the Earth’s
surfacesurface– Any field can have slope, gradient, peaks, pitsAny field can have slope, gradient, peaks, pits
A raster data model uses a gridA raster data model uses a grid
• One grid cell is one unit or holds one attribute. One grid cell is one unit or holds one attribute.
• Every cell has a value, even if it is “missing.” Every cell has a value, even if it is “missing.”
• A cell can hold a number or an index value A cell can hold a number or an index value standing for an attribute.standing for an attribute.
• A cell has a resolution, given as the cell size in A cell has a resolution, given as the cell size in
ground units.ground units.
Generic structure for a grid Generic structure for a grid
Figure 3.1 Generic structure for a grid.
Row
s
Columns
Gridcell
Grid extent
Resolution
Legend
Urban area
Suburban area
Forest (protected)
Water
Raster representation. Each color represents a different value of a nominal-
scale field denoting land use.
Vector DataVector Data
• Used to represent points, lines, and areasUsed to represent points, lines, and areas
• All are represented using coordinatesAll are represented using coordinates– One per pointOne per point– Areas as polygonsAreas as polygons
• Straight lines between points, connecting back to the Straight lines between points, connecting back to the startstart
• Point locations recorded as coordinatesPoint locations recorded as coordinates
– Lines as Lines as polylinespolylines• Straight lines between pointsStraight lines between points
Areas are lines are points are Areas are lines are points are coordinatescoordinates
RepresentationsRepresentations
• Representations can rarely be Representations can rarely be perfectperfect– Details can be irrelevant, or too Details can be irrelevant, or too
expensive and voluminous to recordexpensive and voluminous to record
• It’s important to know what is It’s important to know what is missing in a representationmissing in a representation– Representations can leave us uncertain Representations can leave us uncertain
about the real worldabout the real world
Fundamental problem in Fundamental problem in GIS:GIS:• Identifying what to leave in and what to Identifying what to leave in and what to
take out of digital representations.take out of digital representations.• The scale or level of detail at which we The scale or level of detail at which we
seek to represent reality often seek to represent reality often determines whether spatial and determines whether spatial and temporal phenomena appear regular or temporal phenomena appear regular or irregular. irregular.
• The spatial heterogeneity of data also The spatial heterogeneity of data also influences this regularity or irregularity.influences this regularity or irregularity.
Today’s Topic:Today’s Topic:
The Nature of The Nature of Geographic DataGeographic Data
(Or how phenomena vary across space, and the general nature of geographic variation)
Scale Scale
• Scale refers to the details; fine-scaled data Scale refers to the details; fine-scaled data includes lots of detail, coarse-scaled data includes lots of detail, coarse-scaled data includes less detail.includes less detail.
• Scale refers to the extent. Large-scale project Scale refers to the extent. Large-scale project involves a large extent (e.g. India); small-involves a large extent (e.g. India); small-scale project covers a small area (e.g., scale project covers a small area (e.g., Anantapur, India) Anantapur, India)
• Scale can refer to the level (national vs. local)Scale can refer to the level (national vs. local)• Scale of a map can be large (lots of detail, Scale of a map can be large (lots of detail,
small area covered) or small (little detail, small area covered) or small (little detail, large area covered) (large area covered) (Opposite of other Opposite of other interpretationsinterpretations!!)!!)
Principal objective of GIS Principal objective of GIS analysis:analysis:
• Development of representations of Development of representations of how the world looks and works.how the world looks and works.
• Need to understand the nature of Need to understand the nature of spatial variation:spatial variation:– Proximity effectsProximity effects– Geographic scale and level of detailGeographic scale and level of detail– Co-variance of different measures & Co-variance of different measures &
attributesattributes
• Space and time define the geographic Space and time define the geographic context of our past actions, and set context of our past actions, and set geographic limits of new decisions geographic limits of new decisions (condition what we know, what we (condition what we know, what we perceive to be our options, and how perceive to be our options, and how we choose among them)we choose among them)
• Consider the role of globalization in Consider the role of globalization in defining new patterns of behaviordefining new patterns of behavior
Geographic data:Geographic data:
• Smoothness versus irregularitySmoothness versus irregularity
• Controlled variation: oscillates Controlled variation: oscillates around a steady state patternaround a steady state pattern
• Uncontrolled variation: follows no Uncontrolled variation: follows no patternpattern
(violates Tobler’s Law)(violates Tobler’s Law)
Tobler’s First Law of Tobler’s First Law of GeographyGeography
• Everything is related to everything Everything is related to everything else, but near things are more else, but near things are more related than distant things.related than distant things.
Spatial AutocorrelationSpatial Autocorrelation
• The degree to which near and more The degree to which near and more distant things are interrelated. Measures distant things are interrelated. Measures of spatial autocorrelation attempt to deal of spatial autocorrelation attempt to deal simultaneously with similarities in the simultaneously with similarities in the location of spatial objects and their location of spatial objects and their attributes. (Not to be confused with attributes. (Not to be confused with temporal autocorrelation)temporal autocorrelation)
Example: GDP dataExample: GDP data
Spatial autocorrelation:Spatial autocorrelation:
• Can help to generalize from sample Can help to generalize from sample observations to build spatial observations to build spatial representationsrepresentations
• Can frustrate many conventional Can frustrate many conventional methods and techniques that tell us methods and techniques that tell us about the relatedness of events. about the relatedness of events.
The scale and spatial structure of a particular application suggest ways in which we should sample geographic reality, and the ways in which we should interpolate between sample observations in order to build our representation.
Types of spatial Types of spatial autocorrelationautocorrelation
• PositivePositive (features similar in location (features similar in location are similar in attribute)are similar in attribute)
• NegativeNegative (features similar in (features similar in location are very different)location are very different)
• ZeroZero (attributes are independent of (attributes are independent of location)location)
• The issue of sampling interval is of direct The issue of sampling interval is of direct importance in the measurement of spatial importance in the measurement of spatial autocorrelation, because spatial events autocorrelation, because spatial events and occurrences can conform to spatial and occurrences can conform to spatial structure (e.g. Central Place Theorem).structure (e.g. Central Place Theorem).
• Note: it is also important in the Note: it is also important in the measurement of temporal autocorrelationmeasurement of temporal autocorrelation
Spatial SamplingSpatial Sampling
• Sample frames (“the universe of Sample frames (“the universe of eligible elements of interest”)eligible elements of interest”)
• Probability of selectionProbability of selection
• All geographic representations are All geographic representations are samplessamples
• Geographic data are only as good as Geographic data are only as good as the sampling scheme used to create the sampling scheme used to create themthem
Sample DesignsSample Designs
• Types of samplesTypes of samples– Random samples (based on probability Random samples (based on probability
theory)theory)– Stratified samples (insure evenness of Stratified samples (insure evenness of
coverage)coverage)– Clustered samples (a microcosm of Clustered samples (a microcosm of
surrounding conditions)surrounding conditions)
• Weighting of observations (if spatial Weighting of observations (if spatial structure is known)structure is known)
• Usually, the spatial structure is Usually, the spatial structure is known, thus it is best to devise known, thus it is best to devise application-specific sample designs.application-specific sample designs.– Source data available or easily collectedSource data available or easily collected– Resources available to collect themResources available to collect them– Accessibility of all parts to samplingAccessibility of all parts to sampling
Spatial InterpolationSpatial Interpolation
• Judgment is required to fill in the Judgment is required to fill in the gaps between the observations that gaps between the observations that make up a representation.make up a representation.
• To do this requires an understanding To do this requires an understanding of the effect of increasing distance of the effect of increasing distance between sample observationsbetween sample observations
Spatial InterpolationSpatial Interpolation
• Specifying the Specifying the likely distance decaylikely distance decay– linear: linear: wwij ij == -b d -b dijij
– negative power: negative power: wwij ij == d dijij-b-b
– negative exponential: negative exponential: wwij ij == e e-bdij-bdij
• Isotropic (uniform in every direction) Isotropic (uniform in every direction) and regular – relevance to all and regular – relevance to all geographic phenomena?geographic phenomena?
Key point:Key point:
• An understanding of the spatial An understanding of the spatial structure of geographic phenomena structure of geographic phenomena helps us to choose a good sampling helps us to choose a good sampling strategy, to use the best or most strategy, to use the best or most appropriate means of interpolating appropriate means of interpolating between sampled points, and to build between sampled points, and to build the best spatial representation for a the best spatial representation for a particular purpose.particular purpose.
Spatial AutocorrelationSpatial Autocorrelation
• Induction: reasoning from the data to Induction: reasoning from the data to build an understanding.build an understanding.
• Deduction: begins with a theory or Deduction: begins with a theory or principle. principle.
• Measurement of spatial Measurement of spatial autocorrelation is an inductive autocorrelation is an inductive approach to understanding the approach to understanding the nature of geographic datanature of geographic data
Spatial Autocorrelation Spatial Autocorrelation MeasuresMeasures• Spatial autocorrelation measures: Spatial autocorrelation measures:
– Geary and Moran; nature of observationsGeary and Moran; nature of observations
• Establishing dependence in space: Establishing dependence in space: regression analysisregression analysis– Y = f (XY = f (X11, X, X2 2 , X, X3 3 , . . . , X, . . . , XKK))
– Y = f (XY = f (X11, X, X2 2 , X, X3 3 , . . . , X, . . . , XKK) + ε) + ε
– YYii = f (X = f (Xi1i1, X, Xi2 i2 , X, Xi3 i3 , . . . , X, . . . , XiKiK) + ε) + εii
– YYii = b = b00 + b + b11 X Xi1i1 + b + b22 X Xi2i2 + b + b33 X Xi3 i3 + . . . b + . . . bKK X XiKiK + ε + εii
Y is the dependent variable, X is the independent variable
Y is the response variable, X is the predictor variable
Spatial AutocorrelationSpatial Autocorrelation
• Tells us about the interrelatedness of Tells us about the interrelatedness of phenomena across space, one phenomena across space, one attribute at a time. attribute at a time.
• Identifies the direction and strength Identifies the direction and strength of the relationshipof the relationship
• Examining the residuals (error terms) Examining the residuals (error terms) through Ordinary Least Squares through Ordinary Least Squares regression regression
Discontinuous VariationDiscontinuous Variation
• Fractal geometryFractal geometry– Self-similaritySelf-similarity– Scale dependent measurementScale dependent measurement– Each part has the same nature as the Each part has the same nature as the
wholewhole
• Dimensions of geographic features:Dimensions of geographic features:– Zero, one, two, three… fractalsZero, one, two, three… fractals
ConsolidationConsolidation
• Representations build on our Representations build on our understanding of spatial and understanding of spatial and temporal structurestemporal structures
• Spatial is special, and geographic Spatial is special, and geographic data have a unique naturedata have a unique nature
• This unique natures means that you This unique natures means that you have to know your application and have to know your application and datadata
GeoreferencingGeoreferencing
GeoreferencingGeoreferencing
Geographic information contains Geographic information contains either an explicit either an explicit geographic geographic referencereference (such as latitude and (such as latitude and longitude coordinates), or an implicit longitude coordinates), or an implicit reference such as an address, road reference such as an address, road name, or postal code. name, or postal code.
Geographic references allow you to Geographic references allow you to locate features for analysis.locate features for analysis.
GeoreferencingGeoreferencing
Is essential in GIS, since all information Is essential in GIS, since all information must be linked to the Earth’s surfacemust be linked to the Earth’s surface
The method of georeferencing must be:The method of georeferencing must be:– Unique, linking information to exactly one Unique, linking information to exactly one
locationlocation– Shared, so different users understand the Shared, so different users understand the
meaning of a georeferencemeaning of a georeference– Persistent through time, so today’s Persistent through time, so today’s
georeferences are still meaningful tomorrowgeoreferences are still meaningful tomorrow
UniquenessUniqueness
• A georeference may be unique only A georeference may be unique only within a defined domain, not globallywithin a defined domain, not globally– There are many instances of Storgatas There are many instances of Storgatas
in Norway, but only one in any cityin Norway, but only one in any city– The meaning of a reference to The meaning of a reference to
Greenwich may depend on context, Greenwich may depend on context, since there are cities and towns called since there are cities and towns called Greenwich in several parts of the worldGreenwich in several parts of the world
Georeferences as Georeferences as MeasurementsMeasurements Some georeferences are metricSome georeferences are metric
They define location using measures of They define location using measures of distance from fixed placesdistance from fixed places E.g., distance from the Equator or from the E.g., distance from the Equator or from the
Greenwich MeridianGreenwich Meridian
Others are based on orderingOthers are based on ordering E.g. street addresses in most parts of the world E.g. street addresses in most parts of the world
order houses along streetsorder houses along streets Others are only nominalOthers are only nominal
Placenames do not involve ordering or Placenames do not involve ordering or measuringmeasuring
PlacenamesPlacenames
The earliest form of georeferencingThe earliest form of georeferencing And the most commonly used in everyday And the most commonly used in everyday
activitiesactivities Many names of geographic features are Many names of geographic features are
universally recognizeduniversally recognized Others may be understood only by localsOthers may be understood only by locals
Names work at many different scalesNames work at many different scales From continents to small villages and From continents to small villages and
neighborhoodsneighborhoods Names may pass out of use in timeNames may pass out of use in time
Where was Camelot? Or Atlantis?Where was Camelot? Or Atlantis?
Postal Addresses and Postal Addresses and PostcodesPostcodes• Every dwelling and office is a potential Every dwelling and office is a potential
destination for maildestination for mail• Dwellings and offices are arrayed along Dwellings and offices are arrayed along
streets, and numbered accordinglystreets, and numbered accordingly• Streets have names that are unique within Streets have names that are unique within
local areaslocal areas• Local areas have names that are unique Local areas have names that are unique
within larger regionswithin larger regions• If these assumptions are true, then a If these assumptions are true, then a
postal address is a useful georeferencepostal address is a useful georeference
Where Do Postal Addresses Fail as Where Do Postal Addresses Fail as Georeferences?Georeferences?
• In rural areasIn rural areas– Urban-style addresses have been extended Urban-style addresses have been extended
recently to many rural areas recently to many rural areas
• For natural featuresFor natural features– Lakes, mountains, and rivers cannot be located Lakes, mountains, and rivers cannot be located
using postal addressesusing postal addresses
• When numbering on streets is not When numbering on streets is not sequentialsequential– E.g. in JapanE.g. in Japan
Postcodes as GeoreferencesPostcodes as Georeferences
• Defined in many countriesDefined in many countries– E.g. ZIP codes in the USE.g. ZIP codes in the US
• Hierarchically structuredHierarchically structured– The first few characters define large areasThe first few characters define large areas– Subsequent characters designate smaller areasSubsequent characters designate smaller areas– Coarser spatial resolution than postal addressCoarser spatial resolution than postal address
• Useful for mappingUseful for mapping
ZIP code boundaries are a convenient way to summarize data in the US. The dots on the left have been summarized as a density per square
mile on the right
Linear ReferencingLinear Referencing
A system for A system for georeferencing georeferencing positions on a road, positions on a road, street, rail, or river street, rail, or river networknetwork
Combines the name of Combines the name of the link with an offset the link with an offset distance along the link distance along the link from a fixed point, most from a fixed point, most often an intersectionoften an intersection
Users of Linear ReferencingUsers of Linear Referencing
Transportation authoritiesTransportation authorities To keep track of pavement quality, To keep track of pavement quality,
signs, traffic conditions on roadssigns, traffic conditions on roads
PolicePolice To record the locations of accidentsTo record the locations of accidents
Problem CasesProblem Cases
Locations in rural areas may be a Locations in rural areas may be a long way from an intersection or long way from an intersection or other suitable zero pointother suitable zero point
Pairs of streets may intersect more Pairs of streets may intersect more than oncethan once
Measurements of distance along Measurements of distance along streets may be inaccurate, streets may be inaccurate, depending on the measuring device, depending on the measuring device, e.g. a car odometere.g. a car odometer
CadastersCadasters
Maps of land ownership, showing property Maps of land ownership, showing property boundariesboundaries
The Public Land Survey System (PLSS) in The Public Land Survey System (PLSS) in the US and similar systems in other the US and similar systems in other countries provide a method of countries provide a method of georeferencing linked to the cadastergeoreferencing linked to the cadaster
In the Western US the PLSS is often used In the Western US the PLSS is often used to record locations of natural resources, to record locations of natural resources, e.g. oil and gas wellse.g. oil and gas wells
Portion of the Township and Range system (Public Lands Survey System) widely used in the western US as the basis of land ownership. Townships are laid out in six mile squares
on either side of an accurately surveyed Principal Meridian. The offset shown between townships 16N and 17N is needed to accommodate the Earth’s curvature (shown much
exaggerated). The square mile sections within each township are numbered as shown in (A) east of the Principal Meridian, and reversed west of the Principal Meridian.
T15N
T16N
T17N
T18N
R1W R1E
T14N
T19N
R2W R2E
1 2 3 4 5 6
12 11
10
9 8 7
13 14
15
16
17
18
24 23
22
21
20
19
25 26
27
28
29
30
36 35
34
33
32
31