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

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

Chapter 9 of your text book.

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

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

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.

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

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?

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

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,

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

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

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

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

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

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.

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

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

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 >, <, =, & <>

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

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

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

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.

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

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

Manual Classification Class transitions are specified entirely by the human analyst

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

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.

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.

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

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

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

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: http://web.viu.ca/corrin/GIS/New_Folder/Classification.htm

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

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. .

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

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.

Raster Buffering – Combination of distance and classification

Vector Buffers: Point and Line Buffers

Variable Distance Buffer

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

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

Example: Vector Polygon Overlay

Overlay - Examples .

Overlay output typically takes the dimension of the lowest order input

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.

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

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

ArcGIS Desktop –Resource Center

ArcGIS Desktop -Resource Center

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

Intersection & Union

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

Buffers Creates region at specific distance from one or more features

Buffers Undissolved Buffer Dissolved Buffers Separate Polygons Merged Polygons

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.

ARcGIS Tool for Geoprocessing To be covered in Lab

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

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

References webhelp.esri.com/.../spatial_operations.htm http://www.wou.edu/las/physci/taylor/es341/geoprocessing _ArcGIS.pdf www.ianko.com/.../images2/buffer_dissolve.jpg NCRG Training Courses, “Introduction to GIS” Prepared by Training, R&D Division GIS Fundamental by Paul Bolstad