GROUP MEMBERS KAVIVENTHAN A/L VISUVANATHAN THAMIL VAANI A/P KRISHNAN TEE SENG TECK TANG LI WAH KHAIRUL ARIFFIN SUIB SITI SHAHHIDA ABDULLAH NUR AIN ABD.
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SPATIAL DATA ANALYSIS
GROUP MEMBERS
• KAVIVENTHAN A/L VISUVANATHAN• THAMIL VAANI A/P KRISHNAN
• TEE SENG TECK• TANG LI WAH
• KHAIRUL ARIFFIN SUIB• SITI SHAHHIDA ABDULLAH
• NUR AIN ABD HAKAM
SPATIAL ANALYSISSpatial analysis is the vital part of GIS. Spatial
analysis in GIS involves three types of operations• attribute query (also known as non-spatial), • spatial query• and generation of new data sets from the
original databases.
SPATIAL DATA ANALYSIS Representation of reality Purpose is to understand, describe, predict
the real world scenarios Gives a simplified , manageable view of the
real world
ATTRIBUTE QUERYArcView’s Query Builder([State name] = “California” or “New York”)([City name] = “San*”)New SetAdd to SetSelect from Set
Command line Query (Arc/Info)find in states where state_name = ‘California’<1 record in result>calculate in states population_density = population / area<50 records in result>restrict in states where population_density > 1000<20 records selected in result>>
ATTRIBUTE QUERY USING BOOLEAN LOGIC
Data retrieval is done by applying the rules of Boolean logic to operate on the attributes.
Boolean algebra uses the operators AND, OR, XOR and NOT to see whether a particular condition is true or not.
Ex. TYPE = ‘ASPHALT’ AND LENGTH = 4000 AND LANES = 4
Simple Boolean logic is often portrayed visually in the form of Venn diagrams
A B A
A A
A A
B
B B
B B
C C
A AND B A NOT B
A OR B A XOR B
(A AND B) OR C A AND (B OR C)
VENN DIAGRAM
A AND B = ResultT T TT F FF T FF F F
A OR B = ResultT T TT F TF T TF F F
A XOR B = ResultT T FT F TF T TF F F
SPATIAL SEARCH/QUERY Overlay is a spatial retrieval operation
that is equivalent to an attribute join. Buffering is a spatial retrieval around
points, lines, or areas based on distance.
FIND ALL HOUSES WITHIN A CERTAIN AREA THAT HAVE TILED ROOFS AND FIVE BEDROOMS, THEN LIST THEIR CHARACTERISTICS.
BUFFERING can be constructed around a point, line
or area. Buffering algorithm creates a new area
enclosing the buffered object. The applications of this buffering
operations include, for example, identifying protected zone around lakes and streams, zone of noise pollution around highways, service zone around bus route, or groundwater pollution zone around waste site.
SPATIAL OVERLAY An operation that merges the
features of two coverage layers into a new layer and relationally joins their feature attribute table.
When overlay occurs, spatial relationships between objects are updated for the new, combined map.
In some circumstances, the result may be information about relationships (new attributes) for the old maps rather than the creation of new objects.
GIS USAGE IN SPATIAL ANALYSISGIS operational procedure and analytical task that are
particularly useful for spatial analysis• Single layer operations• Multi layer operations/ Topological overlay• Spatial modeling• Geometric modeling
Calculating the distance between geographic features
Calculating area, length and perimeter Geometric buffers.
• Point pattern analysis• Network analysis• Surface analysis• Raster/Grid analysis• Fuzzy Spatial Analysis• Geostatistical Tools for Spatial Analysis
POINT PATTERN ANALYSIS It deals with the
examination and evaluation of spatial patterns and the processes of point features.
Distribution of an endangered species examined in a point pattern analysis
VECTOR BASED SPATIAL DATA ANALYSIS
There are multi layer operations, which allow combining features from different layers to form a new map and give new information and features that were not present in the individual maps.
Topological overlays: Selective overlay of polygons, lines and points enables the users to generate a map containing features and attributes of interest, extracted from different themes or layers.
TOPOLOGICAL OVERLAYS
Point-in-polygon algorithm overlays point objects on areas and compute "is contained in" relationship.
The result is a new attribute for each point specifying the polygon it belongs to.
Map overlay - point in polygon
Point-in-polygon overlay
LINE-ON-POLYGON OVERLAY
Line-on-polygon algorithm overlays line objects on area objects and compute "is contained in" relationship.
Lines are broken at each area object boundary to form new line segments and new attributes created for each output line specifying the area it belongs to.
POLYGON-ON-POLYGON OVERLAY Polygon-on-polygon
algorithm overlay two layers of area objects.
Boundaries of polygons are broken at each intersection and new areas are created.
During polygon overlay, many new and smaller polygons may be created, some of which may not represent true spatial variations.
OVERLAY OPERATION
NETWORK ANALYSIS: Designed specifically for line features organized in connected networks, typically applies to transportation problems and location analysis such as school bus routing, passenger plotting, walking distance, bus stop optimization, optimum path finding etc.
SURFACE ANALYSIS Deals with the spatial
distribution of surface information in terms of a three-dimensional structure.
The distribution of any spatial phenomenon can be displayed in a three dimensional perspective diagram for visual examination.
GRID ANALYSIS Involves the
processing of spatial data in a special, regularly spaced form.
The following illustration shows a grid-based model of fire progression. The darkest cells in the grid represent the area where a fire is currently underway.
GEOSTATISTICAL TOOLS FOR SPATIAL ANALYSIS
Geostatistics studies spatial variability of
regionalized variables:
Variables that have an attribute value and a location in a two or three- dimensional space.
TOOLS TO CHARACTERIZE THE SPATIAL VARIABILITY ARE:
1)Spatial Autocorrelation Function
statistics measure and analyze the degree of dependency among observations in a geographic space.
Classic spatial autocorrelation statistics include Moran's I and Geary's C.
2) Semivariogram
The semivariogram functions quantifies the assumption that things nearby tend to be more similar than things that are farther apart.
Semivariogram measures the strength of statistical correlation as a function of distance.
TYPES OF SEMIVARIOGRAM MODELS Geostatistical Analyst provides the
following functions to choose from to model the empirical semivariogram: 1. Circular 2. Spherical 3. Tetraspherical 4. Pentaspherical 5. Exponential 6. Gaussian 7. Rational Quadratic 8. Hole Effect 9. K-Bessel 10. J-Bessel 11. Stable
INTERPOLATION Method to estimate variables based on
values at observed locations. Assumption
The influence of one known point over an unknown point increases as distance between them decreases.
4 methods included:
a) Inverse distance weighting - reduce the variable with decreasing
nearness from observed locationb) Kriging method -interpolates space according to spatial lag
relationship with both systematic & random components
c)Thiessen mehod d)Spline method
ACCURACY OF INTERPOLATION Depends on accuracy, number and
distribution of the known points used in the calculation
Depends on how accurate the mathematical function used correctly models the phenomenon. As the assumptions of the model are more severely violated, the interpolation results become less accurate.
No matter which interpolator is selected, the more input points and the greater their distribution, the more reliable the results.
RASTER BASED SPATIAL DATA ANALYSIS A raster is a GIS data structure
comprised of a matrix of rectangular grid cells.
Each cell represents a specific area on the ground.
Resolution of raster is defined by the ground area represented by the raster grid cell.
The higher the resolution of the grid, the more cells are required to portray a given area of ground surface.
The resolution of raster is often a function of the scale of the map from which the spatial data may have been scanned or digitized.
In raster analysis, geographic units are regularly spaced and the location of each unit is referenced by row & column positions.
Because geographic units are of equal size & identical shape, area adjustment of geographic units is unnecessary & spatial properties of geographic entities are relatively easy to trace
ADVANTAGES OF USING THE RASTER FORMAT IN SPATIAL ANALYSIS
Efficient processing: Because geographic units are regularly spaced with identical spatial properties, multiple layer operations can be processed very efficiently.
Numerous existing sources: Grids are the common format for numerous sources of spatial information including satellite imagery, scanned aerial photos, and digital elevation models, among others.
Different feature types organized in the same layer: For instance, the same grid may consist of point features, line features, and area features, as long as different features are assigned different values
RASTER OVERLAY
Replace all 0’s in B
with data from A
A B
PIXELS
• A term employed in the field of remote sensing.• Like grid cell, portray an area subdivided into very
small square cells.• The result of capturing data through the digitization
of aerial/satellite imagery.• Image resolution is stated by defining the ground area
represented by one pixel.• Identified by unique numerical codes called a digital
number.• Each cell has only one digital number.
GRID FORMAT DISADVANTAGES
Data redundancy: When data elements are organized in a regularly spaced system, there is a data point at the location of every grid cell, regardless of whether the data element is needed or not.
Resolution confusion: Gridded data give an unnatural look and unrealistic presentation unless the resolution is sufficiently high. Conversely , spatial resolution dictates spatial properties. For instance, some spatial statistics derived from a distribution may be different, if spatial resolution varies, which is the result of the well-known scale problem.
Cell value assignment difficulties: Different methods of cell value assignment may result in quite different spatial patterns.
RECLASSIFICATION Reclassification is to reassign new
thematic values or codes to units of spatial feature, which will result in merging polygons.
A set of "reclassify attributes", "dissolve the boundaries" and "merge the polygons" are used frequently in aggregating area objects
GRID OPERATIONS USED IN MAP ALGEBRA
Map Algebra performs following four basic operations:• Local functions: that work on every single cell,• Focal functions: that process the data of each cell
based on the information of a specified neighborhood,
• Zonal functions: that provide operations that work on each group of cells of identical values, and
• Global functions: that work on a cell based on the data of the entire
GRID OPERATIONSLocal Function Focal Function
Zonal Function Global Function
SOME IMPORTANT RASTER ANALYSIS OPERATIONS Renumbering areas in a grid file Characterizing Terrain Feature Performing a Cost surface analysis Performing on Optimal Path analysis Performing proximity Search Creating Variable-Width Buffers
Classification A-B : agriculture soil C-E : non agriculture soil
Soil map Agricultural soil
map
-Altering attribute values without changing geometry.
-to see new pattern and connection
CHARACTERIZING TERRAIN FEATURE
Identifying Convex and Concave features by deviation from the trend of the terrain.
Source:Lecture notes from the Asian Institute of Technology
Figures from Asia Asian Institute of Technology
CHARACTERIZING TERRAIN FEATURE 2-D, 3-D and draped displays of terrain slope
Source:Lecture notes from the Asian Institute of Technology
Figures from Asia Asian Institute of Technology
ROUTING AND OPTIMAL PATHS
The steepest downhill path from the Substation over the Accumulated Cost surface identifies the Most referred Route minimizing visual exposure to houses.
Source:Lecture Notes from Asian Institute of Technology
Figures from Asia Asian Institute of Technology
ROUTING AND OPTIMAL PATHS
Alternate routes are generated by evaluating the model using weights derived from different group perspectives
Source:Lecture notes from the Asian Institute of Technology
Figures from Asia Asian Institute of Technology
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