surface analysis with 3d analyst - amazon s3 · supports rendering of lidar attributes • ideal...

Esri UC2013 . Technical Workshop .

Technical Workshop

2013 Esri International User Conference July 8–12, 2013 | San Diego, California

Surface Analysis with

3D Analyst Khalid H. Duri


Why use 3D GIS?

Improve understanding 3D is easy for everyone to understand

Because our world is 3D

Better communication 3D makes it easier to articulate ideas

Solve problems Some problems are only solved in 3D


What can you do with ArcGIS 3D?

Multiscale 3D Models

Surface modeling

3D Analysis

Native lidar support

Share 3D scenes

Integrated 3D

ArcGIS for 3D Cities

3D Geodesign


Recommended Workshops 3D Experience in ArcGIS

Surface Analysis with 3D Analyst

• 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


Understanding the Surface

§ What it is § How it is modeled


Defining the Surface


Representation of any continuous measurements with one value for a given x-y location. z = ƒ(x, y)

More than just topography!

Surface Models • Elevation

• Ozone Concentration

• Rainfall

• Ground stability

• Gravity

• Unlimited possibilities…


Raster Surface • Created by interpolation

• Rectangular matrix of cells arranged in rows & columns

• Values generalized to cell size

• Supports math operations

Overview of Surface Data Types

Vector Surface • Created by triangulation

• Maintains source measurements

• Built-in slope, aspect values

• Supports robust metadata


Choosing the Best Data Type

• What is the nature of data being modeled?

• How is the data distributed?

• How will the data be used?



How About True 3D Modeling?


Multipatch offers true 3D representation that is well-suited for visualization and can support overlay, proximity & volumetric analysis.

Volumes

Buildings Terrains


Surface Analysis Overview

§ Geoprocessing tools § Interactive tools


Geoprocessing Tools

• Presented through ArcToolbox

• Enables chaining of operations

• Supports scripting with Python

• Can be shared with data or provided as a cloud service

ArcGIS Framework for Analyzing & Managing Data

Visit the Analysis island & workshops to learn more about geoprocessing.



3D Geoprocessing Tools

• 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.

Overview of 3D Toolsets



Steepest Path: Determines steepest path from select point.

3D Analyst Toolbar Interactive Tools in ArcMap


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

Interpolate Geometry: Creates 3D features based on surface Z.

Profile: Creates profile graph of surface or point cloud.


LAS Dataset Toolbar Interactive Tools in ArcMap


Target Layer: LAS dataset layer in document that will be processed by interactive tools.

Symbology: Shortcuts to popular symbology options.

Filters: Shortcuts to popular LAS classification filters.

Profile View: Provides profile view of LAS points, enables interactive classification editing.

3D View: Provides 3D view of LAS points within ArcMap.


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.


Vector Surface Models

§ TIN § Terrain § LAS Dataset


Triangulated Irregular Network Surfaces


TIN • Single resolution

• Suited for smaller data samples

• Robust analytical options

Vector surface models that maintain accuracy of source measurements & support irregular distribution of data.

LAS Dataset • Dynamic resolution

• Optimized for airborne lidar

• Rapid visualization

Terrain • Multi-resolution

• Supports LAS attributes

• Suited for large data collections & archival storage


• Avoids long, thin triangles

• Maximizes smallest interior angle of each triangle

• No vertex lies within circumcircle of another triangle

Delaunay Triangulation Vector Surface Concepts


Esri UC2013 . Technical Workshop . Surface Analysis with 3D Analyst

Surface Feature Types

Also supports:

• Break lines

• Tag fill polygon

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

Vector Surface Concepts


Break Lines


Note: Densification of break lines in a TIN can be ignored by specifying constrained Delaunay triangulation to reduce overall size.

• Represent linear features (e.g. roads, ridges, shorelines, etc…) • Densified to ensure Delaunay triangulation rules

Vector Surface Concepts


Hard vs. Soft Surface Feature Type 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



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



Triangulated Irregular Network (TIN)

• Single resolution • Recommended 15-20 million node limit • Ideal for high-precision modeling of study areas

Overview

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.


Advantages • Interactive editing • Rendered in ArcScene • Supports constrained

Delaunay triangulation at break lines


TIN Analysis

Demo #1

§ Delineate TIN Data Area § Surface Grading § Extrude Between


Terrain Dataset

• Multi-resolution • Supports rendering of lidar attributes • Ideal for archival storage & DEM generation

Overview

Note: Terrain resides in a geodatabase and requires contributing features to reside in the same feature dataset.


Advantages • Thinning & display

scale controls • Rendered in ArcScene • Supports anchor

points


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



Terrain Analysis

Demo #2

§ Surface Area & Volume § Interactive Tools


LAS Dataset

• Dynamic resolution • Supports filtering & rendering with lidar attributes • Interactive & automated editing of LAS point

classification

Overview

Note: Calculating statistics for LAS files will optimizes the experience of working with a LAS dataset.


Advantages • Quick to generate • Rendered in ArcScene • Supports anchor

points


Use a LAS Dataset if You Need To…

• 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 “”


General Guidelines for LAS Data


LAS Dataset Analysis

Demo #3

§ Locate Outliers § LAS Point Statistics § Interactive Classification


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


Raster Surface Models

§ Interpolation methods § What to use &

when to use it


Inverse Distance Weighted (IDW)

• Applies weights to source measurements • Weight is a function of inverse distance • Suited for densely sampled

measurements

Raster Interpolation

Note: Interpolated values fall in z-range of source measurements.


Advantages • Fastest interpolator • Rendered in ArcScene • Supports barrier

features


Kriging

• Applies weights based on distance & spatial arrangement

• Requires understanding of data trends

Raster Interpolation

Note: Choosing the most appropriate estimation method requires interactive investigation of the sample measurement’s spatial behavior.


Advantages § Offers multiple

semivariogram models § Provides variance prediction

raster to indicate level of confidence in predicted value

Se

miv

ari

an

ce

Distance

Empirical Semivariogram


• Applies weights to closest subset of source points • Weight based on overlap between Voroni polygons

of measurements & query point

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)

Advantages • Surface passes through the

sample measurements • Smooth except at sample

measurements


• Minimizes curvature between source points • Curve fits specified number of points • Regularized method creates smooth surface,

tensioned method is more constrained

Spline Raster Interpolation

Note: Interpolated values will exceed z-range of source measurements.

Advantages • Surface passes through sample measurements • Supports barriers • Infers trends


• Hydrologically correct elevation models • Ensures connected drainage structure • Captures ridges & streams from contours

Topo To Raster Raster Interpolation

Note: Contours have a stronger effect on at the location of the line.

Advantages • Supports robust feature based

source measurements • Parameters can be saved

and reused


• Fits polynomial function to source measurements • Supports up to 12th order polynomials • Logistic trend option generates prediction model

Trend Raster Interpolation

Note: Resulting surfaces are highly susceptible to outliers.

Advantages • Ideal for surfaces with gradual

variance over space • Useful for examining long-term,

global trends


Trend Raster Interpolation

Note: Resulting surfaces are highly susceptible to outliers.

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

• Fits polynomial function to source measurements

• Supports up to 12th order polynomials

• Logistic trend option generates prediction model for presence/absence of certain phenomena


Raster Analysis

Demo #4

§ Viewshed § Normalized Difference

Vegetation Index (NDVI) with Raster Math

𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 − 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 + 𝐼𝐼𝐼


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

Esri UC2013 . Technical Workshop . Surface Analysis with 3D Analyst

Online • 3D GIS Resource Center

http://resources.arcgis.com/communities/3d

• ArcGIS Desktop Help http://help.arcgis.com

At the UC • ArcGIS Island

main conference hall

• Tech Support follow up assistance


Please fill out the session evaluation

Offering ID: 1228

Online – www.esri.com/ucsessionsurveys Paper – pick up and put in drop box

Thank you…


surface analysis with 3d analyst - amazon s3 · supports rendering of lidar attributes • ideal...

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