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Surface Creation & Analysis with 3D Analyst

Unlock the power of surface data types for elevation, pollution, epidemiology, and more. Learn about raster, vector surfaces, TIN, terrain, LAS datasets, and advanced concepts. Discover terrain construction, LAS dataset editing, raster interpolation, and terrain pyramids. Join us at the Esri International User Conference from July 23-27 at San Diego Convention Center.

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Surface Creation & Analysis with 3D Analyst

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  1. 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 More than just topography! 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…

  3. Surface Data Types 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 Vector Surface Concepts Note: Tag fill polygons provide a means for applying classification attributes (e.g. land use codes). • 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

  7. Surface Feature Types: Break Lines Vector Surface Concepts 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. • 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

  8. Surface Feature Type: Hard vs. Soft Vector Surface Concepts Note: Impact of soft vs. hard designation is only reflected in the raster exported from the triangulated surface using Natural Neighbor inteprolation. • 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

  9. Triangulated Irregular Network (TIN) Overview 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. • Single resolution • Recommended 15-20 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

  10. TIN Creation & Editing Demo

  11. Terrain Dataset

  12. Terrain Dataset Overview Note: Terrain dataset is not supported in ArcScene & can only be rendered in ArcMap. • 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…)

  13. Z-Tolerance vs. Window Size Pyramids Terrain Concepts Note: Click here for more information on terrain pyramids. 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

  14. Terrain Construction Demo

  15. LAS Dataset

  16. LAS Dataset 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 Note: Interpolated values fall within Z-range of sample measurements. • 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

  20. Kriging Raster Interpolation Note: Choosing the most appropriate estimation method requires interactive investigation of the sample measurement’s spatial behavior. • 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

  21. Natural Neighbor Raster Interpolation 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) • 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

  22. Spline Raster Interpolation Note: Interpolated values will exceed Z-range of sample measurements. • 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

  23. Topo To Raster Raster Interpolation 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. • 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

  24. Trend Raster Interpolation Note: Resulting surfaces are highly susceptible to outliers. • 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

  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 AnalysisDemo

  29. Steps to evaluate UC sessions • My UC Homepage > “Evaluate Sessions” • Choose session from planner OR • Search for session www.esri.com/ucsurveysessions

  30. Thank you for attending • Have fun at UC2012 • Open for Questions • Please fill out the evaluation: • www.esri.com/ucsessionsurveys

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