Date post: | 15-Jul-2015 |
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Data & Analytics |
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WHAT IS SPATIAL ANALYSIS?
Spatial analysis is a set of techniques for analysing spatial data.
The results of spatial analysis are dependent on the locations of the objects being analysed.
Software that implements spatial analysis techniques requires access to both the locations of objects and their attributes.
but that’s not it.
ASTRONOMY, TOPOLOGY, FABRICATION ENGINEERING, ECONOMICS
also make use of spatial analysis.
WHAT are the most suitable locations for dams?
WHEN will the water table be re-instated?
WHY land use pattern needs variety?
WHERE are the densest places in the city?
HOW will traffic look like in next 3 days?
1 SPATIAL DATA ANALYSIS
Large tables of spatial data obtained from censuses and surveys.
Simplifying the huge amount of detailed information in order to extract the main trends.
Multi-variate analysis is followed- it considers more than one variable at a time.
2 SPATIAL AUTOCORRELATION
Measures and analyses the degree of dependency among observations in a geographic space.
Eg- In a neighbourhood, the distances between neighbours, or whether they fall into a specified directional class.
Rainfall and the water table.
3 SPATIAL INTERPOLATION
Estimates the variables at unobserved locations in geographic space based on the values at observed locations.
Eg- Traffic prediction down the road.
4 SPATIAL REGRESSION
Captures spatial dependency, avoiding statistical problems such as unstable parameters and unreliable significance tests.
Generating predictions from partial data sets.
Eg- Archaeological survey and conservation
5 SPATIAL INTERACTION
Spatial interaction or "gravity models" estimate the flow of people, material or information between locations in geographic space.
Eg- Destination attractiveness variables such as the amount of office space in employment areas
Proximity relationships between the locations measured in terms such as driving distance or travel time.
6 SIMULATION AND MODELLING
Study the emergence of complex patterns and relationships from behaviour and interactions at the individual level.
Eg- One could model traffic flow and dynamics using agents representing individual vehicles that try to minimise travel time between
specified origins and destinations.
7 MULTIPLE-POINT GEOSTATISTICS
Spatial analysis of a conceptual geological model is the main purpose of any MPS algorithm.
Conceptual model is called training image.
The method analyzes the spatial statistics and generates realizations of the phenomena that honor those input multiple-point statistics.
To learn and simulate specific structural patterns.
WHAT IS MAP ALGEBRA ?
Dana Tomlin, 1980
Band collectionCombining and calculating
The statistics of raster bandsMore like extracting .xls from a layer
Create SignatureCreates an ASCII signature file defined by
input sample data and a set of raster bandsCreating a simple source
Iso Clusterclustering algorithm to determine
characteristics of the natural groupingsjust Grouping !
FUZZY OVERLAY
Sum Transforms the input raster into a 0 to 1 scale, indicating the strength of a membership in a set, based on a specified fuzzification algorithmic value x its importance
AND | OR | PRODUCT | SUM | GAMMA(0.9)
Creates a raster of a constant value within the extent and cell size
Constant
rasterNormal raster
Random
rasterCreates a raster of a Normal value within the extent and cell size
Creates a raster of a Random value within 0 to 1.
ALSO TOO MUCH !
Block Statistics
Filter Statistics Focal Statistics
Line Statistics
Point Statistics
including profile and plan curvature
Curvature Contour Cut and fill
line feature class of contours (isolines) from a raster surface
Calculates a volume change between two surfaces
shaded relief from a surface raster by considering the illumination source angle and shadows
Hill shade Slope Observer pt.
rate of maximum change in z-value) from each cell of a raster surface
Identifies which observer points are visible from each raster surface location