1. Basic Spatial Analysis
Spatial Data Analysis: Dealing with GIS functions of storing and querying spatial data
June 13, 2014
Institute of Space Technology, Karachi

2. Spatial Analysis
Involves applications of operations to coordinates and related attribute data
Spatial functions or operations: Manipulation or calculation of coordinates or attribute variables.

3. Chapter 9 of your text book.

4. Input Layer  Spatial Operation Output Layer
Spatial Data Analysis
Input Layer  Spatial Operation Output Layer
Spatial analyses are applied to solve problems related to geographic decisions
Examples:
Identify high crime areas
Generate a list of road segments that need repaving
Select a best location for a new business
100s of spatial operations or functions. E.g.: high crime area, spread of disease etc.
A chain of spatial operation (sequentially) – out of each serving as input to the next operation
Data from 1 or 2 layers to create output

5. Spatial Data Analyses - Operations
Examples:
Selection operations
Sort
Classification
Etc.

6. Sequence of Spatial Operations
Single Spatial Operations
Sequence of Spatial Operations
Single one to one correspondence between input and output layers. : vector to raster conversion.
One to many: Terrain analysis (slope and aspect)
Many to one: layer average.
Spatial operations can be applied sequentially to solve a problem.
Output of each spatial operation serving as input of the next.

7. Challenge!!!!
Selecting appropriate spatial operations and applying them in the appropriate order

8. Spatial Data Analysis Non Spatial Queries (standard Database queries)
Application of operations to coordinates and
related attribute data
Non Spatial Queries (standard Database queries)
How long is River Indus?
Population of Pakistan?
etc.
Spatial Queries
Neighboring countries of Pakistan?
List of provinces through which Indus river flows?
Spatial operations/function to calculate
These are standard Database queries that request to retrieve the value of some attribute.
Spatial operations that applied to both coordinate and associated attribute data?

9. Spatial Data Analysis
Since attribute data is related to spatial objects therefore we can not separate operations on attribute data from operations on coordinate portion of spatial data

10. Spatial Operations
Applied to one or more input layers to produce one or more output data layers
One to One
Conversion of raster data into vector
One input – Many outputs
Slope and aspect produced from raster elevation model
Many inputs – one output
To calculate data averages from different layers
~takes input data, performs analysis on it, and produces output information (may be a layer or non spatial-mean cell value of a raster data layer)
Slope (how steep each cell is) and aspect (direction of slope): Terrain analysis function
Many input: mean temperature over last ten years,

11. Spatial Operations
Spatial function or operations are basic components of spatial data analysis.

12. Spatial Operations Depends on type of data model used
Specific operations available in the GIS software
In many instances it’s more efficient to convert data between data models and apply the desired operations and convert results back to the original data model

13. Spatial Operations Outputs
Non Spatial outputs
Spatial operation produces scalar value, a list, or a table with no explicit geometric data attached
Spatial
New data layer is produced
Non-spatial: in raster data set mean cell value

14. Spatial Scope Local Operations Neighborhood Operations
Spatial operations may be
characterized by their spatial scope
Local Operations
Neighborhood Operations
Global Operations
Scope: to reflect the extent of the source area used to determine the value at a given output location.
Local Operations: data at one input location. Attributes of adjacent locations are not used
Neighborhood Operations: use both an input location + nearby location to determine output value. Value at an output location is influenced by more than just the value of data found at the corresponding input location
Global Operations: uses data values from the entire input layer to determine each output value

15. Spatial Data Analysis Selection Reclassification Dissolving Buffering
Overlay
Set of available spatial operation depends on the data model and type of spatial data used as input.
Data model conversion may also be a choice for ease in spatial operation application.
selection operation from relational algebra

16. Selection Features are identified based on given criteria
Attributes or geometry of features are checked against criteria – those that satisfy the criteria are selected
On-screen or interactive query
Selection by attribute
Selection by location
Selection by graphics
ArcToolbox: Analysis Tools-Extract-select
The set algebra operations < & > not applied on nominal data because there is no implied order in nominal data.

17. Selection
Thematic map of countries of western Europe (and their population); selection of countries with more than 50M people

18. Selection: More than One Criteria
Features are identified that meet one to several condition or criteria

19. Selection: Set Algebra
Example: in a political map of European countries, select all names and population of countries with more than 50M inhabitants
Above is an example of set algebra
Greater (>), less than (<), equal to (=), & not equal to (<>) selection
Used either alone or in combination
>, <, =, & <>

20. Selection: Set Algebra
Set algebra uses operations > < = <>
> And < can not be applied to nominal data. There is no implied order in nominal data. Green is not greater than Red.
All applied to ordinal and ratio/interval data

21. Selection: Boolean Algebra
Conditions:
AND,
OR,
NOT
Combines set algebra and create compound spatial selection
Boolean expression is valuated by assigning an outcome 1, 0 or True, False
NOT = negation operator
3rd expression above = compound Boolean expression

22. Expression In Boolean Algebra
Try A AND (B OR C)

23. Selection by Location: Adjacency
Identify those features that ‘touch’ other features
States adjacent to Missouri
Adjacency and Containment are 2 commonly used selection operations.
States adjacent to Missouri
Adjacency: Shared line/node required.

24. Selection by Location: Containment
Identifies all features that contain or surround a set of target features
All states containing a portion of Mississippi River or its tributaries
Containment: States containing a portion of Mississippi River or its tributaries are selected

25. Reclassification
Classification of spatial objects based on spatial or non spatial data
From an existing set of classes to a new set of classes
To group objects for display or map production based on a common property (attributes values)
Example: classification of Polygons based on size

26. Manual Classification
Class transitions are specified entirely by the human analyst

27. Binary classification
Simplest form
Two forms: 1, 0; true n false; A and B or other two level classification

28. Automatic Classification
Uses some rules to specify the input class to output class assignment
A mathematical formula or algorithm defines the class boundaries
Examples
Equal Interval
Equal Area
Natural Break
etc.

29. Equal area: Subtracts the lowest value of the classification variable from the highest value and define equal width boundaries to fit the desired number of classes into the range.
In fig low population class shown in white dominates the map.
Problem: the outliers shift the class boundaries to higher values in the above problem (1711 and 3422), resulting in most neighborhoods falling in the small population groups.

30. Source: http://www.slideshare.net/johnjreiser/classification-systems

31. An equal area classification sets class boundaries so that each class covers approximately the same area.

32. Natural Break Default classification method in ArcMap
Features are divided into classes based on big jumps in the data values

33. Natural Breaks Difference I 102 - C 103 1 D 121 18 J 122 A 123 L 129 6
Difference I
102 - C
103 1 D
121 18 J
122 A
123 L
129 6 F
134 5 E
135 K
137 2 H
186 49 G
197 11 B
201 4
Difference I
102 - C
103 1 D
121 18 J
122 A
123 L
129 6 F
134 5 E
135 K
137 2 H
186 49 G
197 11 B
201 4
Source:

34. Dissolve Combines or dissolve similar features within a data layer
Adjacent polygons with identical values are merged into a single polygon
Often used after reclassification

35. Proximity
Modifies existing feature or creates new features that depend on distance
Available water represented by Points and distance function applied to these points to create raster data layer containing the distance to nearest water feature.
What neighborhoods are far from utility stores.
Which homes will be affected by an increase in freeway noise. .

36. Proximity: Distance Calculations
Distance values are calculated using Pythagorean formula
Calculated from cell center to cell center (when applied to raster data)

37. Represents specific distance around a feature
Buffers
Commonly used proximity function
Represents specific distance around a feature
May be determined for point, line, or area features
Also for both types of data models
Most common spatial analysis tool.
Less than or equal to a specified distance from one or more features.

38. Raster Buffering – Combination of distance and classification

39. Vector Buffers: Point and Line Buffers

41. Variable Distance Buffer

42. Overlay
Combining spatial and attribute data from two or more spatial data layers
Overlapping different themes (multiple layer operation)
Vertical stacking or merging of data
Areas where features in different layers overlap
Data layers should be in a common coordinate system
Overlay creates new data layer
Clip, Intersect and union are special cases of overlay
A new data layer is created

43. Vector Overlay Clip Intersect Union
Only the areas that overlap are contained
Cookie cutter approach
Intersect
Combines data from both layers but only for a given region where both layers contain data
Union
Both overlapping and non-overlapping areas are contained
Order of intersection is important

44. Example: Vector Polygon Overlay

45. Overlay - Examples .

46. Overlay output typically takes the dimension of the lowest order input

47. Raster Overlay Cell by cell combination of 2 or more data layers
Typically applied to nominal or ordinal data
Input raster should have same cell size (or integer multiple) and coordinate systems, same origin of x and y coordinates
Data is converted to most convenient cell size before overlay using resampling.

48. Geoprocessing in ArcGIS
Set of software functions used to manipulate and transform spatial data (single layers or multiple sets of layers), to create new information
Map Overlay functions: combining layers to create single output
Extraction
Intersection
Dissolve
Buffer
Append and Merge

49. Extraction
Clip: cookie cutter function (Layer attributes not combined)
Layers to be clipped: point, line, polygon
Clipping layer:
When the Input Features are polygons, the Clip Features must also be polygons
When the Input Features are lines, the Clip Features can be lines or polygons.
When the Input Features are points, the Clip Features can be points, lines, or polygons.
Erase: Opposite of clip
Clip: Features inside the clip boundary will be preserved, all those outside are removed. A feature is used as a cookie cutter to cut the extent of another feature to the same extent as the cookie cutter feature.
Erase: all information outside of the operational polygon are preserved, and the interior features are erased

50. ArcGIS Desktop –Resource Center

51. ArcGIS Desktop -Resource Center

52. Intersection & Union Intersect Union
Merges attributes between layers within the spatial extent common to both themes - points-lines-polygons
Union
Combines two polygon layers, keeping all areas and merging attributes
Layer Attributes combined
Integrate two spatial data sets while preserving only those features falling within the spatial extent common to both themes

53. Intersection & Union

54. Dissolve Combines and dissolves similar features within a data layer
Aggregates features based on the same attribute value specified by the user

55. Buffers
Creates region at specific distance from one or more features

56. Buffers Undissolved Buffer Dissolved Buffers Separate Polygons
Merged Polygons

57. Append and Merge Combine 2 layers of the same feature type into 1
Merge “edges” of adjoining layers with identically matching polygons and attributes
Append data while maintaining the attributes contained in the selected layer
same feature-type (points, lines, or polygons).
Merge: Combines multiple input datasets of the same data type into a single, new output dataset. This tool can combine point, line, or polygon feature classes or tables.
Use the Append tool to combine input datasets with an existing dataset.

58. ARcGIS Tool for Geoprocessing
To be covered in Lab

59. a. Clip tool
ArcTool Box- Analysis Tools – Extract - Clip
b. Erase tool
ArcTool Box – Analysis Tools – Overlay - Erase
c. Intersect tool
ArcTool Box – Analysis Tools – Overlay – Intersect
d. Union tool
ArcTool Box - Analysis Tools – Overlay - Union
e. Dissolve tool
Arc Tool Box – Data Management Tools – Generalization - Dissolve
f. Buffer tool
ArcTool Box - Analysis Tools – Proximity - Buffer
g. Append tool
Arc Tool Box – Data Management Tools-General – Append
h. Merge tool
Arc Tool Box – Data Management Tools- General – Merge

60. Using Model Builder
Models are built to automate geoprocessing workflow
Will be covered next

61. References webhelp.esri.com/.../spatial_operations.htm
_ArcGIS.pdf
NCRG Training Courses, “Introduction to GIS” Prepared by Training, R&D Division
GIS Fundamental by Paul Bolstad