1. SPATIAL DATA ANALYSIS

2. Spatial analysis Spatial 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.

3. 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

4. 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.

5. Find all houses within a certain area that have tiled roofs and five bedrooms, then list their characteristics.

6. 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.

8. 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.

9. GIS usage in Spatial Analysis
GIS 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
While basic spatial analysis involves some attribute queries and spatial
queries, complicated analysis typically require a series of GIS operations
including multiple attribute and spatial queries, alteration of original data,
and generation of new data sets. The methods for structuring and organizing
such operations are a major concern in spatial analysis. An effective spatial
analysis is one in which the best available methods are appropriately employed
for different types of attribute queries, spatial queries, and data alteration. The
design of the analysis depends on the purpose of study.

10. 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 .

11. 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.

12. 1. Point-in-polygon overlay Map overlay - point in polygon
Topological overlays
1. Point-in-polygon overlay
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

13. Topological overlays (cont.)
2. 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.
Output is line coverage with additional attribute.
No polygon boundaries are copied.
New arc-node topology is created.

14. Topological overlays (cont.)
3. 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.
Polygon-in-polygon overlay:
Output is polygon coverage.
Coverages are overlaid two at a time.
There is no limit on the number of coverages to be combined.
New File Attribute Table is created having information about each newly created feature.

15. 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.

16. 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.
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. A surface may
represent the distribution of a variety of phenomena, such as population, crime,
market potential, and topography, among many others. The perspective
diagram in represents topography of the terrain, generated from
digital elevation model (DEM) through a series of GIS-based operations in
surface analysis.

17. 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.
A fire probability model, which incorporates fire behavior
in response to environmental conditions such as wind and topography,
delineates areas that are most likely to burn in the next two stages. Lighter
shaded cells represent these areas. Fire probability models are especially useful
to fire fighting agencies for developing quick-response, effective suppression
strategies.

18. 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:

19. a) Inverse distance weighting - reduce the variable with decreasing nearness from observed location b) Kriging method -interpolates space according to spatial lag relationship with both systematic & random components c)Thiessen mehod d)Spline method

20. 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.

21. 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.
All cells in a grid have a positive position reference, following the left-to-right and top-to-bottom data scan. Every cell in a grid is an individual unit and must be assigned a value.
Depending on the nature of the grid, the value assigned to a cell can be an integer or a floating point. When data values are not available for particular cells, they are described as NODATA cells. NODATA cells differ from cells containing zero in the sense that zero value is considered to be data.

22. 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

23. 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
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. These data sources have been adopted in many GIS projects and have become the most common sources of major geographic databases.
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

24. Raster Overlay A
Replace all 0’s in B
with data from A B

25. 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.

26. 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.
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. Although, several
compression techniques are available, the advantages of gridded data are
lost whenever the gridded data format is altered through compression. In
most cases, the compressed data cannot be directly processed for analysis.
Instead, the compressed raster data must first be decompressed in order
to take advantage of spatial regularity.
􀁺 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.

27. 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

28. -Altering attribute values without changing geometry.
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

29. THE END…