1. Surface Creation & Analysis with 3D Analyst
Esri International User Conference
July 23–27 | San Diego Convention Center
Surface Creation & Analysis with 3D Analyst
Khalid Duri

2. Surface Basics
Defining the surface
Representation of any continuous measurement with one value for a given x-y location z = ƒ(x,y)
Elevation
Pollution
Epidemiology
Ground stability
Unlimited possibilities…
More than just topography!

3. Surface Data Types Raster Surface Vector Surface
Overview of Raster & Vector Surfaces
Raster Surface
Created by interpolation
Rectangular matrix of cells arranged in rows & columns
Source measurement precision generalized to cell size
GDB & file based formats
Vector Surface
Created by triangulation
Irregularly spaced data points connected by edges
Source measurement precision maintained
TIN, terrain, & LAS dataset

4. Vector Surface Formats
Supports irregular distribution of nodes, providing higher resolutions where measurements vary greatly and lower resolution in areas w/ less variability.
TIN
Single-resolution
Loaded into memory for display
Suited for smaller collections of high density data
Terrain
Multi-resolution
Supports LAS attributes
Suited for large scale, archival data storage
LAS Dataset
Dynamic resolution
Designed for airborne lidar
Quick to create, references data

5. Delaunay Triangulation
Vector Surface Concepts
Avoids long, thin triangles
Maximizes smallest interior angle of each triangle
No vertex lies within circumcircle of another triangle

6. Surface Feature Types Mass points: Measurements used for triangulation
Vector Surface Concepts
Mass points: Measurements used for triangulation
Erase polygon: Interior areas of no data
Replace polygon: Assigns a constant z value
Clip polygon: Defines the interpolation zone
Also supports:
Break lines
Tag fill polygon
Note: Tag fill polygons provide a means for applying classification attributes (e.g. land use codes).

7. Surface Feature Types: Break Lines
Vector Surface Concepts
Surface measurements that capture linear features (e.g. roads, ridges, shorelines, etc…)
Densified to ensure Delaunay triangulation rules
Impact is visible when exporting raster
Without Break Lines
With Break Lines
Note: Densification of break lines in a TIN can be ignored by specifying constrained Delaunay triangulation. This reduces overall size, while disabling natural neighbor interpolation.

8. Surface Feature Type: Hard vs. Soft
Vector Surface Concepts
Qualifiers for line and polygon based surface feature types
Hard features denote sharp break in slope
Soft features denote gradual change in slope
Soft Break Lines
Hard Break Lines
Note: Impact of soft vs. hard designation is only reflected in the raster exported from the triangulated surface using Natural Neighbor inteprolation.

9. Triangulated Irregular Network (TIN)
Overview
Single resolution
Recommended million node limit
Typically used for high-precision modeling of smaller areas
Advantages
Interactive editing
Rendered in ArcScene
Supports constrained Delaunay triangulation at break lines
Note: Maximum allowable size of a TIN varies relative to free, contiguous memory resources. It’s recommended to cap the size at a few million nodes for usability.

10. TIN Creation & Editing Demo

11. Terrain Dataset

12. Terrain Dataset Multi-resolution TIN
Overview
Multi-resolution TIN
Stored in a geodatabase feature dataset
Commonly used in bathymetric & topographic mapping
Typical data sources include lidar, sonar, & photogrammetry
Advantages
Control over scale display resolution
Grouping options for non-mass point surface features types
Supports anchor points & LAS attributes (class codes, returns, etc…)
Note: Terrain dataset is not supported in ArcScene & can only be rendered in ArcMap.

13. Z-Tolerance vs. Window Size Pyramids
Terrain Concepts
Scale-dependent subsets of source measurements designed for optimizing display and analysis performance.
Window Size
Partitions data into small areas & selects one or two source measurements to contribute to the next pyramid level
Suited for urban landscapes
Quick to build
Z-Tolerance
Determines the minimum number of points to ensure vertical accuracy within the defined z- tolerance from source data points
More accurately depicts data characteristics
Note: Click here for more information on terrain pyramids.

14. Terrain Construction Demo

15. LAS Dataset

16. LAS Dataset Dynamic resolution Designed for airborne lidar
Overview
Dynamic resolution
Designed for airborne lidar
References data from LAS files
Treats LAS measurements as mass points
Advantages
Provides rapid display of LAS
Provides interactive LAS classification editing
Supports anchor points
Can be rendered in ArcScene

17. LAS Dataset Creation & Editing Demo

18. Raster Interpolation

19. Inverse Distance Weighted (IDW)
Raster Interpolation
Cell values are determined using linearly weighted set of sample measurements.
Weight is a function of inverse distance.
Strengths
Suited for densely sampled measurements
Fast processing
Supports barrier features
Note: Interpolated values fall within Z-range of sample measurements.

20. Kriging Raster Interpolation
Predictive geostatistical method that assumes spatial autocorrelation
Multi-step process involving exploratory statistical analysis & variogram modeling
Weight is determined by distance & spatial arrangement
Ordinary Kriging assumes no trend, unversal Kriging assumes overriding trend
Strengths
Offers multiple semivariogram models
Provides variance prediction raster to indicate level of confidence in predicted value
Diverse applications (e.g. health sciences, geochemistry, geology)
Semivariance
Empirical Semivariogram
Distance
Note: Choosing the most appropriate estimation method requires interactive investigation of the sample measurement’s spatial behavior.

21. Natural Neighbor
Raster Interpolation
Applies weights to closest subset of source measurements to a query point
Weight based on proportionate of overlap between Voronia polygons around source measurements & query point
Strengths
Surface passes through the sample measurements
Smooth except at sample measurements
Note: Interpolated values fall within Z-range of sample measurements. Does not infer trends nor capture sharp features that are not found in source measurements (e.g. ridges &valleys)

22. Spline
Raster Interpolation
Estimates values using mathematical function that minimizes curvature between source measurements
Curve must fit a specified number of data points
Regularized method creates smooth surface; tension method is more constrained to source measurement range
Strengths
Surface passes through the sample measurements
Supports barriers
Infers trend
Note: Interpolated values will exceed Z-range of sample measurements.

23. Topo To Raster
Raster Interpolation
Specifically designed for creation of hydrologically correct elevation models
Imposes contraints that ensure connected drainage structure
Produces correct representation of ridges and streams from contours
Strengths
Supports point elevation measurements, contours, streams, sinks, boundary and lake polygons
Parameters can be saved to a file and reused
Note: A minor bias in the interpolation algorithm causes contours to have a stronger effect on the resulting surface at the location of the contour.

24. Trend Fits polynomial function to source measurements
Raster Interpolation
Fits polynomial function to source measurements
Supports up to 12th order polynomials
Logistic trend option generates prediction model for presence/absence of certain phenomena
Strengths
Ideal for fitting sample points when surface varies gradually from region to region (e.g. air pollution)
Useful for examining effects of long- range/global trends
Note: Resulting surfaces are highly susceptible to outliers.

25. Raster Interpolation Demo

26. Surface Analysis

27. Surface Analysis
Overview
Provides wide range of functionality including data management & conversion, to surface analysis.
Interactive Tools
Rapid results on full resolution data
Available via following toolbars:
3D Analyst
TIN Editing
LAS Dataset
Geoprocessing Tools
Can be leveraged for automation
Large collection of functionality
Data management & QA\QC
Surface derivatives & analysis
Visibility

28. Surface Analysis Demo

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