Announcements. Data Sources a list of data files and their sources, an example of what I am looking for:

Transcription

1 Data Announcements Data Sources a list of data files and their sources, an example of what I am looking for: Source Map of Bangor MEGIS NG911 road file for Bangor MEGIS Tax maps for Bangor City Hall, may need to digitize. Addresses of Schools MEGIS Questionaire results Need to conduct interviews School quality rankings? Lecture 11 1 Test 1covering chapters 1-8 and labs 1-4 Test will be ed to all students Tuesday (Oct. 18 th ), on or before 6:00 PM The test is open book, open notes. The test should be ed back to me by noon, Oct. 20 th. No class on the 20 th. Lecture

2 Basic Spatial Analysis Ch. 9 Lecture 11 3 Spatial data analysis Input -> spatial operation -> output Lecture

3 Input Scope The area or extent of the input data. Local point to point Neighborhood adjacent regions have input Global the entire input data layer may influence output Lecture 11 5 Spatial Data Analysis Usually involves manipulations or calculation of coordinates or attribute variables with a various operators (tools), such as: Measurement Queries & Selection Attribute Location Reclassification Dissolve Buffering Overlay Clip Erase Update Intersect Identity Union Symmetrical Difference Merge Network Analysis Lecture

4 Table Operations Statistics count, minimum, maximum, sum, mean, standard deviation and the number of null values, as well as a frequency distribution of the variable. Summarize - summary statistics include the count, average, minimum, and maximum values Join 1:1 or m:1, two tables become one, but it is not permanent. Relate all other relationships, tables remain separate. Append Tables must have the same columns, number and type Lecture 11 7 Measurement: Figure 6.4 Vector GIS measurements: (a) distance and (b) area Lecture

5 Attribute Selection A query is a question to the database. The database response is a table. The ArcGIS database response is selected records. If the table is the feature table it also displays the selection on the map. Selected records can be exported to form a new shapefile/feature class. Lecture 11 9 Theme Name SQL Lecture

6 Spatial Selection (Select by Location) Identifying features based on spatial criteria Adjacency, connectivity, containment, arrangement Lecture Adjacency depends on the algorithm used (the same is true for all spatial operations) Lecture

7 Touch the boundary of Lecture Share a line segment with Lecture

8 Spatial Selection Identifying features based on spatial criteria Adjacency, connectivity, containment, arrangement Allows us to know which roads connect. Analyze transportation networks. Which river or streams flow into another. Analyze electrical networks. Lecture Spatial Selection Identifying features based on spatial criteria Adjacency, connectivity, containment, arrangement Lecture

9 Selection based on spatial and non-spatial attributes Lecture Spatial data analysis: Reclassification An assignment of a class or value based on the attributes or geography of an object Example: Parcels Reclassified By size Lecture

10 Spatial data analysis: Reclassification Lecture Reclassify in ArcGIS Lecture

11 Lecture Natural Breaks (Jenks) Natural Breaks classes are based on natural groupings inherent in the data. Class breaks are identified that best group similar values and that maximize the differences between classes. The features are divided into classes whose boundaries are set where there are relatively big differences in the data values. Natural breaks are data-specific classifications and not useful for comparing multiple maps built from different underlying information. From ArcGIS 10 Help Lecture

12 Natural Breaks Lecture Lecture

13 Equal Interval Equal interval divides the range of attribute values into equal-sized subranges. This allows you to specify the number of intervals, and ArcGIS will automatically determine the class breaks based on the value range. For example, if you specify three classes for a field whose values range from 0 to 300, ArcGIS will create three classes with ranges of 0 100, , and Equal interval is best applied to familiar data ranges, such as percentages and temperature. This method emphasizes the amount of an attribute value relative to other values. For example, it will show that a store is part of the group of stores that make up the top one-third of all sales. From ArcGIS 10 Help Lecture Equal Interval Lecture

14 Lecture Quantile Each class contains an equal number of features. A quantile classification is well suited to linearly distributed data. Quantile assigns the same number of data values to each class. There are no empty classes or classes with too few or too many values. From ArcGIS 10 Help Lecture

15 Quantile Lecture Lecture

16 Standard Deviation The Standard deviation classification method shows you how much a feature's attribute value varies from the mean. ArcMap calculates the mean and standard deviation. Class breaks are created with equal value ranges that are a proportion of the standard deviation usually at intervals of 1,½, ⅓, or ¼ standard deviations using mean values and the standard deviations from the mean. A two-color ramp helps emphasize values above the mean and values below the mean. From ArcGIS 10 Help Lecture Standard Deviation Lecture

17 Lecture Geometric Interval The geometrical interval classification scheme creates class breaks based on class intervals that have a geometrical series. The geometrical coefficient in this classifier can change once (to its inverse) to optimize the class ranges. The algorithm creates geometrical intervals by minimizing the square sum of elements per class. This ensures that each class range has approximately the same number of values with each class and that the change between intervals is fairly consistent. This algorithm was specifically designed to accommodate continuous data. It produces a result that is visually appealing and cartographically comprehensive. It minimizes variance within classes and can even work reasonably well on data that is not normally distributed. From ArcGIS 10 Help Lecture

18 Geometric Interval Lecture Lecture

19 The Modifiable Areal Unit Problem (MAUP) The results of data analysis are influenced by the number and sizes of the zones used to organize the data. The Modifiable Area Unit Problem has at least three aspects: 1. The number of ways in which fine-scale zones can be aggregated into larger units is often great. 2. The number, sizes, and shapes of zones affect the results of analysis. 3. There are usually no Lecture objective 11 criteria for choosing one zoning scheme over another. 37 MAUP Example Lecture

20 Dissolve Lecture Vector Buffers Lecture

21 Mechanics of Point and Line Buffering Lecture Buffering Variants: point buffer examples Lecture

22 Lecture Regions in Buffering inside, outside, enclosed Lecture

23 Overlay Analysis Combination of different data layers Both spatial and attribute data is combined Requires that data layers use a common coordinate system A new data layer is created Lecture Lecture

24 Lecture Vector Overlay Topology is likely to be different Vector overlays often identify line intersection points automatically. Intersecting lines are split and a node placed at the intersection point Topology must be recreated for later processing Any type of vector may be overlain with any other type Output typically takes the lowest dimension of the inputs For example: Point on Polygon results in a point Lecture

25 Ambiguous result Unambiguous result Lecture Vector Overlay - Most common ways applied, but there are other methods. CLIP INTERSECTION UNION Lecture

26 CLIP Cookie cutter approach Bounding polygon defines the clipped second layer Neither the bounding polygon attributes nor geographic (spatial data) are included in the output layer Lecture Lecture

27 Lecture INTERSECTION Combines data from both layers but only for the bounding area (Bounding polygon also defines the output layer Data from both layers are combined Data outside the bounding layer (1 st layer) is discarded) Lecture

28 Lecture Lecture

29 UNION Includes all data from both the bounding and data layers New polygons are formed by the combinations of the coordinate data from each layer Lecture Lecture

30 Lecture Lecture

31 Identity Analysis Computes a geometric intersection of the Input Features and Identity Features. The Input Features or portions thereof that overlap Identity Features will get the attributes of those Identity Features. Lecture Identity Analysis The Input Features must be point, multipoint, line, or polygon. The Identity Features must be polygons. Output may be multipart. If multipart features are not desired, use the Multipart to Singlepart tool on the output. Lecture

32 Symmetrical Difference Computes a geometric intersection of the input and update features. Features or portions of features in the input and update features which do not overlap will be written to the Output Feature Class. The input and difference feature class and feature layer must have polygon geometry. Output may be multipart. Lecture Update Computes a geometric intersection of the Input Features and Update Features. The attributes and geometry of the input features are updated by the update features in the output feature class. The input must be a polygon. ArcGIS Desktop Help Lecture

33 Why do buffering and vector overlay often take so long? Because a time consuming line intersection test must be performed for all lines in the data layers Then, inside vs. outside regions must be identified for all new polygons Lecture Finding the interior: Interior: Is a point inside a polygon? (shaded)? n= 2, out Potential point n= 4, out n= 3, in n= 1, in Algorithm: Pick a Algorithm: direction (East (right) count in the line example) crossings to Count outside line crossings of convex to thehull, outside if of they convex is an hull odd (shaded number polygon) the point is inside, if If odd even number number, then the point is inside outside If even, the point is outside Lecture

34 Vector Overlay Common features in Vector overlays create Slivers or Sliver polygons A common feature in both layers. The problem is that each definition is very subtly different (different time, source, materials) so the polygons don t line up. They can only be seen a very large display scale but can represent over half the output polygons. They take very little space but affect analytical results. Lecture Lecture

35 Methods to reduce/remove slivers: Redefine the common boundaries with highest coordinate accuracy and replace them in all layers before overlay Manually identify and remove Use snap distance during overlay Lecture Merge New parcels can be created by merging existing parcels in the parcel fabric. Adjacent parcels can be merged to create a single parcel, and disjoint parcels can be merged to create multipart parcels. Parcels being merged can be saved as historic parcels, kept current, or deleted. ArcGIS Desktop Help Lecture