Presentation is loading. Please wait.

Presentation is loading. Please wait.

Review- vector analyses

Similar presentations


Presentation on theme: "Review- vector analyses"— Presentation transcript:

1 Review- vector analyses
Selection Topological Overlays Buffering

2 Selection Selecting points near a line (proximity)
Selecting adjacent features (proximity) Selecting lines within polygons (containment) Selecting polygons that contain lines (overlap) Selecting points within polygons (containment) Selecting polygons that contain points (overlap) Selecting polygons that overlap polygons (overlap)

3 Types of overlays Union Clip Identity Intersect Update Erase

4 Clipping… an example

5 Clipping… an example

6 ArcGIS does NOT automatically update geometry fields for shapefiles

7 Raster Analysis

8 Overview Grid layers Setting grid layer and analysis properties
Grid function types Performing grid analysis Map Algebra More grid analyses

9 Grid layers

10 Grid layers The grid layer is the format ArcInfo uses for raster data.

11 Grid layers A grid layer is a rectangular grid of square cells

12 Grid layers Not all raster datasets are grid layers reflectance values

13 Grid layers Cells have numeric values

14 Grid layers Grid layers are suited for representation of phenomena that vary gradually over space such as elevation, wind speed and direction, or slope

15 Grid types integer (no decimals) floating-point (decimals)

16 Grid types Integer grids can have value attribute tables (VATs), floating point grids do NOT

17 Grid types Integer grids with: a range of values < 100,000
and < 500 unique values will have attribute tables

18 Displaying grid layers
Legends can be altered like other layers

19 Identity tool Individual cell values can be identified

20 Queries Integer grids can be queried in the same way as vector layers (select by attribute)

21 Setting grid layer and analysis properties

22 Setting analysis properties
Working directory Masking Spatial extent of output Cell size Once set, analysis property values stay set until changed Analysis properties determine spatial properties for all newly created output grid layers

23 Analysis extent Analysis extent sets the spatial properties for output of analyses Rectangular area

24 Analysis extent Be careful about setting extent; it may cause poor grid-to-grid registration

25 Cell size Analysis cell size sets the grid cell size for output of analyses Use a consistent cell size for analysis of multiple grid data sets small cells → larger files small cells → longer processing

26 Masking Analysis mask defines spatial extent of output grids
Mask can be any shape (as opposed to the Analysis Extent)

27 Grid function types

28 Grid function types Local Global functions Zonal functions
Focal functions

29 Local functions Local functions apply an independent calculation to all input grid cells local sine e.g. sin(12) =

30 Global functions Global functions apply a calculation based on all cell values e.g. flow accumulation

31 Zonal functions Zonal functions apply one calculation to all input grid cells within each zone Zones are defined as a group of cells having the same value Regions are groups of contiguous cells having the same value

32 Zonal functions Zonal functions apply one calculation to all input grid cells within each zone zonal sum for zone 1: ( ) = 423

33 Focal functions Focal functions apply one calculation to all input grid cells within a focal distance focal mean ( ) / 9  18.7

34 Performing grid analysis

35 Grid analysis: calculations across multiple grids
Multi-grid analyses are possible because of spatial registration multiple grid layers share the same X, Y coordinate space cell values are calculated across multiple grid layers to create a single output grid layer

36 Grid analysis Spatial Analyst toolbar ArcToolbox tools Scripting
Command Line

37 Spatial Analyst toolbar
Raster calculator

38 Spatial Analyst extension

39 Map Algebra

40 Grid analysis: Map algebra
arithmetic expressions output_data_set = input_grid1 operator input_grid slp_dem = slp_grid * dem algebraic functions output_data_set = function (input_data_set[s] {,arguments}) slp_grid = slope (dem, percentrise)

41 Map algebra can be calculated with the Raster Calculator
operator classes operators raster layers expression box

42 Grid analysis: Map algebra
Map Algebra arithmetic: Calculation = (Dem gt 500 and Dem lt 1000 ) Logical (Boolean) criteria

43 Grid analysis: Map algebra
0 = false 1 = true

44 More grid analysis Calculating summary attributes for polygon features using a grid layer (“Zonal Statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources

45 Calculating summary attributes for polygon features using a grid layer
(“Zonal statistics”)

46 Summarizing zones Summarizes groups of cells based on integer cells or polygons with similar value Creates statistical summary of zone Summary table Summary chart

47 Summarizing zones

48 Summarizing zones select polygon field to define zones of cells
select grid layer containing variable to summarize select statistic to graph specify output

49 statistics from input grid based on polygon zones

50 Ecological Applications: Vol. 17, No. 1, pp. 18–33.
INFLUENCE OF ENVIRONMENT, DISTURBANCE, AND OWNERSHIP ON FOREST VEGETATION OF COASTAL OREGON Janet L. Ohmann, Matthew J. Gregory, and Thomas A. Spies

51

52 Cross tabulating areas

53 Cross tabulating areas
Creates a “zonal intersection” of integer grid layers or grids and polygon vectors (similar to vector intersection) Output is a table 1st input layer creates records (1 record for each unique value) 2nd input layer creates fields (1 field for each unique value) Table values are map unit area measurements of combinations of zones

54 Cross tabulating areas
Cross-tabulation setup rows columns

55 Cross tabulating areas
Output table record layer (stands) area measurements in map units row layer (soils)

56 Cross tabulating areas
Identifying fields

57 Cross tabulating areas

58 Cross tabulating areas

59 "Querying" across multiple grid layers (“Map Query”)
Raster Calculator is easy to use and gives rapid results Multiple grids can be simultaneously queried (vector overlay only allows 2) Output represents cells that meet and do not meet query criteria (T or F)

60 "Querying" across multiple grid layers

61 Building Map Queries

62

63 Calculating neighborhood statistics

64 Calculating neighborhood statistics
Minimum Maximum Mean Median Sum Range Standard Deviation Majority Minority Variety “Focal” statistical functions Moving window calculates statistics based on all within the window Output value is written to central cell in output grid Statistical functions:

65 Focal Standard Deviation
locations of greatest variation in elevation

66 Calculating distance surfaces and buffers

67 Calculating distance surfaces and buffers
Similar to buffering with vector data Creates a continuous distance surface rather than a discrete bounded polygonal area Distance measured from input layer features or grid cells

68 Distance from vector features
continuous distance value surface

69 Create a “graded” buffer by setting a max distance

70 Determining proximity

71 Assigning proximity Defining territories based on proximity

72 Assigning proximity output cells have the value of the closest input feature output value is selected from input layer table “Thiessen,” “Voronoi”

73 Converting raster and vector data sources

74 Converting raster and vector data sources
Raster  vector conversions are possible Always a loss or generalization of shape Support for line, polygon  grid in ArcGIS Avoid converting grids that do not have large contiguous zones (e.g., DEMs)

75 homework Read “Raster Analysis 2” & “Data Conversion” & “Model building” Finish assignment 5 Start assignment 6

76 Ecological Applications: Vol. 17, No. 1, pp. 18–33.
INFLUENCE OF ENVIRONMENT, DISTURBANCE, AND OWNERSHIP ON FOREST VEGETATION OF COASTAL OREGON Janet L. Ohmann, Matthew J. Gregory, and Thomas A. Spies

77

78

79

80

81

82

83

84

85


Download ppt "Review- vector analyses"

Similar presentations


Ads by Google