GIS 1 Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University GIS Lecture 10 Extensions.

GIS 1Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

GIS Lecture 10Extensions

GIS 2Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Outline

•Extensions Overview•Free Add On Applications•Network Analyst•Spatial Analyst•3D Analyst•Community Visualization tools•TerraSim•Keyhole•Extensions Review

GIS 3Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

ArcGIS Extensions

•http://www.esri.com/software/arcgis/arcgisxtensions/

The following ArcGIS Extension products add specialized tools and functionality to ArcView, ArcEditor and ArcInfo.

•3D Analyst•Business Analyst•Geostatistical Analyst•Military Analyst•Publisher•Schematics•Spatial Analyst

•StreetMap•Survey Analyst•Tracking Analyst•ArcPress•ArcScan •Job Tracking•MrSID Encoder

GIS 4Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Free ArcGIS Add-Ons

•ArcWeb Toolbar

•Tablet PC Support for ArcGIS

•ArcMap GPS Support

•Districting for ArcGIS

GIS 5Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Network Analyst

Solves a variety of problems based on geographic networks including:

• Most efficient travel routes• Travel directions• Closest emergency vehicle or service facility to an incident

• Service areas or sales territories based on travel time

GIS 6Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Delivery Route - This path represents a delivery truck route.

- With the Network Analyst, the dispatcher can define a route that with stop at each restaurant in the most efficient order and return to the warehouse.

GIS 7Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Shortest and Fastest Path -This path represents the shortest linear distance between the two locations.

- This path represents the fastest path between the same two locations used in the previous example.

- Fastest paths are based on time. You can use any measure of time ( seconds, minutes, hours, etc.)

GIS 8Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Service Areas - Overlapping and nested service areas are individual polygons.

- This allows you to use ArcView's spatial analysis tools to determine which customers or how many customers are in each service area or if any customers are serviced by more than one site.

GIS 9Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Areas within a Distance This example shows which areas are within a 10 minute walking distance of different bus stops (service area and network) and which bus routes (find best route) are serviced by the stops.

GIS 10Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Spatial Analyst Grid based layers

•Geographic data to attempt to describe, simulate or predict a real-world problem or system

•Creates continuous surfaces from scattered point features

• Maps easy to read

GIS 11Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Grid Layers

• Divides geographic space into uniform blocks called cells

-Every cell represents a certain specified portion of the earth, such as a square kilometer or square meter

-Each cell is given a value that describes the site, such as elevation or landuse type

GIS 12Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Wild Fire Predictions

Original wind direction grid.

Using Spatial Analyst, add 90 degrees to each cell value in the first grid to generate a second wind direction grid.

GIS 13Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Wild Fire Predictions

GIS 14Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Soil Information Farmers can determine the soil pH values

GIS 15Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Hydrology Maps Flow direction grid from an elevation grid

Hypothetical spill points, shown by white dots, on the elevation grid. Spatial Analyst uses the flow direction and elevation values to compute the contaminant's probable downhill path.

GIS 16Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

3D Analyst

GIS 17Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

3D Analyst Overview

•3D Analyst Extension-Surfaces-Grids-TINS-3D Shapefiles-3D Scenes-Examples

GIS 18Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Surface Model

A geographic surface, or surface model, represents a spatial quantity or phenomenon that can be measured continuously over some part of the earth

Terrain Elevations DEM - Digital Elevation Model

DTM - Digital Terrain Model

GIS 19Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Other Surface Examples

Geographic phenomena

- Soil type

- Land cover

- Temperature

- Rainfall

- Population density

GIS 20Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Surface Model (Elevations)

Sample elevation points that can be used to generate a surface model.

A set of sample elevation points. Each point has x,y values and a z value, which defines its elevation.

GIS 21Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Surface Model (Elevations) A surface model generated from the points and displayed in 3D perspective.

GIS 22Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Grids

A grid defines geographic space as a matrix of identically-sized square cells.

Each cell holds a numeric value that measures a geographic attribute (like elevation) for that unit of space.

When the grid is drawn as a map, cells are assigned colors according to their numeric values.

GIS 23Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Grids A grid divides geographic space into cells of equal size. Each cell stores a number that measures a geographic value at that location. In this case, the numbers reflect elevation in meters.

GIS 24Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Grids An elevation grid drawn in a view. The cell values are classified by numeric range and symbolized with different colors.

GIS 25Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Grid Example

Proposed shopping center plan displayed on a graded elevation surface

GIS 26Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

TIN

(Triangulated Irregular Network)

A TIN is a data structure that defines geographic space as a set of contiguous, non-overlapping triangles, which vary in size and angular proportion.

GIS 27Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

TIN Structure•Defined by two elements: a set of input points with x,y, and z values, and a series of edges connecting these points to form triangles.

•Each input point becomes the node of a triangle in the TIN structure, and the output is a continuous faceted surface of triangles.

GIS 28Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

TIN The TIN structure, showing nodes (sample elevation points) and the triangles generated from them.

GIS 29Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

TIN Example

Santa Barbara elevation surface

GIS 30Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

3D Shapefiles

Displays discrete geographic features •Buildings•Rivers•Wells•Roads in 3D

GIS 31Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

3D Shapefiles

Attributes of a 2D shapefile

Attributes of a 3D shapefile

GIS 32Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

3D Contours

•Mt. Saint Helens •Start with a 2D Contour Map

GIS 33Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

3D Contours

Surface layer created

GIS 34Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Dynamic 3D Views

Perspective angle in 3D Scene set at 60°

GIS 35Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Loading Extensions (3D Analyst)

Tools, Extensions…

Choose the 3D Analyst Extension

GIS 36Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

3D Scenes A 3D scene is a three-dimensional viewing environment for spatial data.

GIS 37Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Draping features to a 3D Model•Raster Images•Vector Features

GIS 38Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Extruding Features•Based on 3D field•Buildings extruded from height or number of floors

GIS 39Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Navigating Scenes•Set Observers and Targets

•Flythrough

GIS 40Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

ArcGlobe

Fast Viewing of Large 3D Datasets

GIS 41Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Other 3D ExamplesAnalyzing Visibility•Locations from which observers can see

•Red part of the line is a gap in the line of sight

GIS 42Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Other 3D Examples

Steepest-path analysis•Flow of liquid from a certain point

GIS 43Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Other 3D Examples 3D Representation of Land Value Totals by Tax Map Grid, Concord, North Carolina, USA

GIS 44Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Other 3D Examples North Macadam Development Concept—Floor Area Ratio Massing Study, City of Portland Bureau of Planning • Results of the massing model were

used to generate a series of three-dimensional perspectives from adjacent neighborhoods and scenic points to help illustrate what the district's build-out form could look like. In addition, a regional elevation model was used to assess the impact of development on the visibility of important landscape features. This information was used to help the city, property owners, and the public understand what would be allowed under the proposed plan.

GIS 45Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Advanced Visualization Tools-Helps view, project, analyze, and understand potential alternatives and impacts via visual exploration and alternative scenarios

-Experiments with hypothetical scenarios, challenge assumptions on the fly

-Encourages participation and collaboration by engaging users and public audiences via visualization and interactive participation.

GIS 46Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Community VIZ•Community VIZ http://www.communityviz.com

GIS 47Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Criterion Planners

•INDEX http://www.crit.com

GIS 48Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

TerraSim, Inc.

•CMU Spin-off•TerraTools -3D GIS Visualization Software

•http://www.terrasim.com/

•One Gateway Center, Suite 2050420 Fort Duquesne Blvd.Pittsburgh, PA 15222

• (412) 232-3646(412) 232-3649 FAX

GIS 49Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Schenley Park

GIS 50Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Parametric Bridge Models

GIS 51Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

CMU Campus

GIS 52Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Urban Clutter

GIS 53Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Placement Models

GIS 54Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Keyhole

http://www.keyhole.com

GIS 55Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Keyhole

GIS 56Copyright 2005 – Kristen S. Kurland, Carnegie Mellon University

Extension Review

•Free or paid for add on extensions•3rd Party GIS applications•Reference Manuals Available at

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