Surface Analysis with 3D Analyst

Transcription

1 2013 Esri International User Conference July 8 12, 2013 San Diego, California Technical Workshop Surface Analysis with 3D Analyst Khalid H. Duri Esri UC2013. Technical Workshop.

2 Why use 3D GIS? Because our world is 3D Better communication 3D makes it easier to articulate ideas Improve understanding 3D is easy for everyone to understand Solve problems Some problems are only solved in 3D Esri UC2013. Technical Workshop.

3 What can you do with ArcGIS 3D? 3D Geodesign Multiscale 3D Models ArcGIS for 3D Cities Surface modeling Share 3D scenes Native lidar support 3D Analysis Integrated 3D Esri UC2013. Technical Workshop.

4 Recommended Workshops 3D Experience in ArcGIS 3D Features & Volumetric Analysis Wed 1:30 2:45 Room 9 Publishing Globe Services Wed 2:30 3:00 Room 1 Creating 3D Animations Wed 1:30 2:00 Mapping& Visualization Exhibit Hall B Introduction to ArcGIS for 3D Cities Past Workshop Watch Recorded Video Working with 3D Analyst & CityEngine Past Workshop Watch Recorded Video

5 Understanding the Surface What it is How it is modeled Esri UC2013. Technical Workshop.

6 Defining the Surface Representation of any continuous measurements with one value for a given x-y location. z = ƒ(x, y) Surface Models Elevation Ozone Concentration Rainfall Ground stability Gravity Unlimited possibilities More than just topography!

7 Overview of Surface Data Types Raster Surface Created by interpolation Rectangular matrix of cells arranged in rows & columns Values generalized to cell size Supports math operations Vector Surface Created by triangulation Maintains source measurements Built-in slope, aspect values Supports robust metadata Esri UC2013. Technical Workshop.

8 Choosing the Best Data Type What is the nature of data being modeled? How is the data distributed? How will the data be used?

9 How About True 3D Modeling? Multipatch offers true 3D representation that is well-suited for visualization and can support overlay, proximity & volumetric analysis. Buildings Terrains Volumes

10 Surface Analysis Overview Geoprocessing tools Interactive tools Esri UC2013. Technical Workshop.

11 Geoprocessing Tools ArcGIS Framework for Analyzing & Managing Data Presented through ArcToolbox Enables chaining of operations Supports scripting with Python Can be shared with data or provided as a cloud service Visit the Analysis island & workshops to learn more about geoprocessing.

12 3D Geoprocessing Tools Overview of 3D Toolsets Functional Surface: Analysis operations that support all surfaces. Raster toolsets: Interpolation, mathematic operations, reclassification & surface derivatives from rasters. Triangulated Surface: TIN based surface analysis. Visibility: Sightline, viewshed, & skyline analysis.

13 3D Analyst Toolbar Interactive Tools in ArcMap Steepest Path: Determines steepest path from select point. Interpolate Geometry: Creates 3D features based on surface Z. Target Surface Layer: Surface layer in document that will be processed by interactive tools. Contour: Creates a single isoline at the selected point. Line of Sight: Determines visibility of sight line & identifies possible obstructing point Profile: Creates profile graph of surface or point cloud.

14 LAS Dataset Toolbar Interactive Tools in ArcMap Filters: Shortcuts to popular LAS classification filters. 3D View: Provides 3D view of LAS points within ArcMap. Target Layer: LAS dataset layer in document that will be processed by interactive tools. Symbology: Shortcuts to popular symbology options. Profile View: Provides profile view of LAS points, enables interactive classification editing.

15 TIN Editing Toolbar Interactive Tools in ArcMap TIN Editors: Add, modify, or remove nodes, edges & triangles Grading Tool: Modify surface using line with slope properties.

16 Vector Surface Models TIN Terrain LAS Dataset Esri UC2013. Technical Workshop.

17 Triangulated Irregular Network Surfaces Vector surface models that maintain accuracy of source measurements & support irregular distribution of data. TIN Single resolution Terrain Multi-resolution Supports LAS attributes Suited for large data collections & archival storage Suited for smaller data samples Robust analytical options LAS Dataset Dynamic resolution Optimized for airborne lidar Rapid visualization

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

19 Surface Feature Types 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).

20 Break Lines Vector Surface Concepts Represent linear features (e.g. roads, ridges, shorelines, etc ) Densified to ensure Delaunay triangulation rules Note: Densification of break lines in a TIN can be ignored by specifying constrained Delaunay triangulation to reduce overall size.

21 Hard vs. Soft Surface Feature Type 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.

22 Use a TIN Based Surface if You Need To Calculate planimetric area, surface area, or volumes Have highly irregular data distribution Surface details captured by line & polygon features Source measurements capture adequate range of overall terrain

23 Triangulated Irregular Network (TIN) Overview Single resolution Recommended million node limit Ideal for high-precision modeling of study areas Advantages Interactive editing Rendered in ArcScene Supports constrained Delaunay triangulation at break lines Note: Maximum size of a TIN depends on availability of free, contiguous memory resources. Limiting the size to a few million nodes can ensure an optimal experience.

24 Demo #1 TIN Analysis Delineate TIN Data Area Surface Grading Extrude Between Esri UC2013. Technical Workshop.

25 Terrain Dataset Overview Multi-resolution Supports rendering of lidar attributes Ideal for archival storage & DEM generation Advantages Thinning & display scale controls Rendered in ArcScene Supports anchor points Note: Terrain resides in a geodatabase and requires contributing features to reside in the same feature dataset.

26 Use a Terrain Dataset if You Need To Manage an expansive, editable surface data model Store large sets of surface measurements with variable data density Create a repository for DEM production with break line enforcement Maintain robust metadata along with Z values Leverage enterprise database versioning

27 Demo #2 Terrain Analysis Surface Area & Volume Interactive Tools Esri UC2013. Technical Workshop.

28 LAS Dataset Overview Dynamic resolution Supports filtering & rendering with lidar attributes Interactive & automated editing of LAS point classification Advantages Quick to generate Rendered in ArcScene Supports anchor points Note: Calculating statistics for LAS files will optimizes the experience of working with a LAS dataset.

29 Use a LAS Dataset if You Need To General Guidelines for LAS Data Rapidly visualize lidar Edit LAS point classifications Review LAS point statistics Assess data coverage & perform QA/QC Produce digital elevation models from lidar Visit the

30 Demo #3 LAS Dataset Analysis Locate Outliers LAS Point Statistics Interactive Classification Esri UC2013. Technical Workshop.

31 Recommended Workshops TIN Based Surfaces Working with Terrain Datasets Wed 8:30 9:00 Hall F Room 1 Working with Lidar & Terrain Datasets Wed 12:30 1:00 Mapping& Visualization Exhibit Hall B Working with Lidar Datasets Wed 3:15 4:35 Room 9

32 Raster Surface Models Interpolation methods What to use & when to use it Esri UC2013. Technical Workshop.

33 Inverse Distance Weighted (IDW) Raster Interpolation Applies weights to source measurements Weight is a function of inverse distance Suited for densely sampled measurements Advantages Fastest interpolator Rendered in ArcScene Supports barrier features Note: Interpolated values fall in z-range of source measurements.

34 Kriging Raster Interpolation Applies weights based on distance & spatial arrangement Requires understanding of data trends Advantages Offers multiple semivariogram models Provides variance prediction raster to indicate level of confidence in predicted value Semivariance Empirical Semivariogram Distance Note: Choosing the most appropriate estimation method requires interactive investigation of the sample measurement s spatial behavior.

35 Natural Neighbor Raster Interpolation Applies weights to closest subset of source points Weight based on overlap between Voroni polygons of measurements & query point Advantages 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) Esri UC2013. Technical Workshop.

36 Spline Raster Interpolation Minimizes curvature between source points Curve fits specified number of points Regularized method creates smooth surface, tensioned method is more constrained Advantages Surface passes through sample measurements Supports barriers Infers trends Note: Interpolated values will exceed z-range of source measurements. Esri UC2013. Technical Workshop.

37 Topo To Raster Raster Interpolation Hydrologically correct elevation models Ensures connected drainage structure Captures ridges & streams from contours Advantages Supports robust feature based source measurements Parameters can be saved and reused Note: Contours have a stronger effect on at the location of the line. Esri UC2013. Technical Workshop.

38 Trend Raster Interpolation Fits polynomial function to source measurements Supports up to 12 th order polynomials Logistic trend option generates prediction model Advantages Ideal for surfaces with gradual variance over space Useful for examining long-term, global trends Note: Resulting surfaces are highly susceptible to outliers. Esri UC2013. Technical Workshop.

39 Trend Raster Interpolation Fits polynomial function to source measurements Supports up to 12 th 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 longrange/global trends Note: Resulting surfaces are highly susceptible to outliers. Esri UC2013. Technical Workshop.

40 Demo #4 Raster Analysis Viewshed Normalized Difference Vegetation Index (NDVI) with Raster Math IIIIIIII RRR IIIIIIII + RRR Esri UC2013. Technical Workshop.

41 Recommended Workshops Raster Surfaces Creating Surfaces with Spatial Analyst Wed 8:30 9:00 Room 3 Perform Regression Analysis Using Raster Data Wed 10:30 11:00 Hall G Room 2 An introduction to Geostatistical Analyst Wed 1:30 2:45 Room 5A An Introduction to Spatial Analyst Wed 1:30 2:45 Room 3 Concepts & Applications of Kriging Wed 3:15 4:35 Room 4 Raster Surface Interpolation in ArcGIS Wed 4:30 5:30 Analysis & Geoprocessing Exhibit Hall B

42 Online 3D GIS Resource Center ArcGIS Desktop Help At the UC ArcGIS Island main conference hall Tech Support follow up assistance

43 Thank you Please fill out the session evaluation Offering ID: 1228 Online Paper pick up and put in drop box