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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. Surface Basics. Defining the surface. More than just topography!.

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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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