Digital Quest, Inc.

Course at a glance:
This course takes you through the Leica Geosystems Image Analysis software extension for ArcGIS in detail. Remote sensing plays a huge part of image analysis in that it involves gathering data about our environment and analyzing it. Generally, the gathering of this data, or these images, is by satellite or airplane. You will develop skills that will allow you to take images and convert them to data that you will use for different types of analyses. The types of analyses you will be performing in this course will be Using data in Image Analysis, Orthorectification, Feature Extraction, Vegetation Mapping and Change Detection, and Image Enhancement.

Using Data in Image Analysis…: Identify image analysis terminology; View single band and multispectral images; Create a subset of an image; Mosaic two georeferenced images

Orthorectification: Prepare a Digital Elevation Model; Perform image analysis by orthorectifying non-georeferenced digital images to existing map features

Feature Extraction: Use the seed tool to extract land features from imagery data; Explore seed tool properties and their affect on image analysis results

Vegetation Mapping and Change Detection: Categorize land cover types using image analysis tools; Evaluate areas of change in images

Image Enhancement: Enhance an image by adjusting the brightness and contrast; Enhance an image by adjusting the histogram and applying custom histogram stretches; Enhance an image by sharpening and smoothing its appearance; Enhance an image by converting it from color IR to natural color; Enhance an image by performing a resolution merge

During the course you will also learn….

Adding Data
Adding Neatlines to Layouts
Adding Thematic Data to a View
Adjusting Brightness & Contrast of Images
Adjusting the Histogram of an Image
Analyzing Vegetation
Applying an Invert Stretch
Applying Histogram Equalize Stretch
Applying Standard Deviation Stretch
Calculating Thematic Change
Categorizing an Image
Changing Detection in Vegetation Using Image Difference
Changing from Data View to Layout View
Choosing Band Combinations
Computing Image Differences
Converting an Image from Color IR to Natural Color
Creating a Subset Image
Creating Account on GeoCommunity Website
Creating Layouts with Multiple Frames
Creating Links between Image and Shapefiles
Creating Map Layouts
Creating Shapefiles in ArcCatalog
Creating Subsets of Local Aerial Photographs
Displaying Toolbars
Downloading DEM Data from Specified Internet Resources
Editing Symbology of a Layer
Editing the Thematic Change Layer
Extracting Archived Files
Identifying Affected Areas in an Image
Importing Files to Raster
Importing Multispectral Satellite Data
Importing Single Band Satellite Data
Launching ArcMap
Launching Internet Explorer
Loading the Image Analysis Extension
Mosaicking Images
Mosaicking the DEMs
Orthorectifying an Image
Performing Resolution Merge
Placing Fiducials
Preparing a Local DEM
Preparing Digital Elevation Models
Recoding Images
Saving Projects
Selecting by Pixel
Selecting Coordinate System for Images
Selecting Multiple Files
Setting Analysis Extent
Setting Coordinate System for Shapefile
Setting Geocorrection Properties
Setting Seed Tool Properties
Sharpening an Image
Smoothing an Image
Using Image Enhancement Techniques with the Seed Tool
Using Supervised Classification
Using the Layer Stacking Tool
Using the Seed Tool
Using Thematic Change in Change Detection
Using Various Zooming Techniques

Why is this topic important?
Have you ever heard that a picture is worth a thousand words? Then can you imagine how important it is to be able to take a picture, or image and be able to study and analyze it? With Image Analyst you can do just that.

In terms of our geospatial studies, we use the term “remote sensing” as viewing our world from a distance. Usually we do this through the use of airplanes or satellites. In this course you are given the tools necessary to take images from these sources and use them to perform numerous analyses. Examples of actual uses are a forestry team studying the extent of a recent fire without having to send personnel out to survey the land, a farmer being able to detect which parts of his crops need more irrigation or fertilization without physically going there, and a city planner studying the growth of his city over the course of time. This important image data that once served as backdrops for other files can now be used for analysis.

Table of Contents:

Unit 1: Applications in Remote Sensing

Lesson 1 Using Data in Image Analysis
Lesson Objectives

Identify data terminology dealing with image analysis
View single band and multipsectral images
Create a subset of an image
Mosaic two georeferenced images

Lesson Exercise & Enrichment Exercises: Using Data in Image Analysis

Load the Image Analysis extension program
Display the Image Analysis toolbar
Display a single-band satellite image
Display the background of an image layer as transparent
Display a multi-spectral satellite image
Create a subset image of a larger image data layer
Mosaic two images to create a single image data layer
Create a map layout of analysis results

Lesson 2 Orthorectification
Lesson Objectives

Identify data terminology dealing with image analysis
Prepare a DEM (Digital Elevation Model)
Perform image analysis by orthorectifying non-georeferenced digital images to existing map features

Lesson & Enrichment Exercises: Orthorectification

Explore the concept of orthorectification
Prepare a DEM for use for the orthorectification of an image data layer
Import SDTS files to raster files using conversion tools
Mosaic DEM data layers for use for the orthorectification of an image data layer
Set the coordinate system desired for the orthorectification
Set correction properties for the orthorectification
Place fiducial marks created during imagery collection for the orthorectification
Create links to orthorectify an image data layer to a georeferenced vector data layer
Save the orthorectified image as a new image data layer

Lesson 3 Feature Extraction
Lesson Objectives

Identify data terminology dealing with image analysis
Use the Seed Tool to extract land features from imagery data
Explore Seed Tool Properties and their affect on image analysis results

Lesson & Enrichment Exercises: Feature Extraction

Create a new polygon shapefile in ArcCatalog
Set the coordinate system desired for the analysis
Set Seed Tool Properties
Isolate an area of an image depicting a fire-damaged area using the Seed Tool
Explore pixel selection methods including clicking and clicking/dragging a rectangle to sample pixel values
Explore Seed Radius as a factor in terms of how polygons are drawn using the Seed Tool
Explore the Include Island Polygons option of Seed Tool Properties
Populate a new shapefile with data features using the Seed Tool
Perform a Supervised Classification to find like areas of an image using the Seed Tool

Lesson 4 Vegetation Mapping & Change Detection
Lesson Objectives

Identify data terminology dealing with image analysis
Categorize land cover types using image analysis tools
Evaluate areas of change in images

Lesson & Enrichment Exercises: Vegetation Mapping & Change Detection

Perform a layer stack using Image Analysis tools
Analyze vegetation in imagery using the Vegetative Index tool
Identify areas of change in vegetation using the Image Difference tool with time-lapsed vegetation indices
Perform an Unsupervised Categorization to analyze land cover for a geographic area
Use the Thematic Change tool to identify areas of change in categorized data

Lesson 5 Image Enhancement
Lesson Objectives

Identify data terminology dealing with image analysis
Enhance an image by adjusting the brightness and contrast
Enhance an image by adjusting the histogram and applying custom histogram stretches
Enhance an image by sharpening and smoothing its appearance
Enhance an image by converting it from color IR to natural color
Enhance an image by performing a resolution merge

Lesson & Enrichment Exercises: Image Enhancement

Explore the use of band combinations in satellite imagery to enhance the data
Adjust the brightness of an image data layer
Adjust the contrast of an image data layer
Review the histograms of an image data layer
Apply various histogram stretches to an image data layer to enhance it
Apply an Invert Stretch to a negative image data layer to produce a positive image data layer
Enhance an image data layer using the Sharpen technique
Enhance an image data layer using the Smoothing technique
Convert a color IR image data layer to natural color using Image Analysis tools
Use the Resolution Merge technique to combine the best characteristics of two image data layers a low-resolution color image and a high-resolution monochromatic image.

Who could use this knowledge?

Who are the direct stakeholders?

Skills we assume you have before you take this class:

You must know ArcGIS 9.1, have basic computer skills, including a working knowledge of an office suite (such as PowerPoint, Word Docs, and Spread Sheets) and experience with the Internet.

Software you will need:

an Internet Browser, STARS Custom dataset, ArcGIS Desktop (includes ArcMap and ArcCatalog), and Leica Image Analysis Extension for ArcGIS

Hardware you will need:

A networked computer lab with a 1:1 ratio of students to computers, which meets the following minimum specifications: Pentium-III, Celeron, Pentium 4 or AMD Athlon running at 1ghz or equivalent, at least 1GB of RAM memory, Windows 2000 or Windows XP Professional, a network server providing at least 500MB of storage per student, and appropriate read/write permissions for both the server and workstations. You will also need Internet access and a suitable means of displaying PowerPoint presentations (LCD projector, large monitor, plasma screen, etc.). You will also need a GPS unit.

Teacher Support…

Detailed, thorough student documentation, Full lesson plans including objectives, materials needed, procedures and assessments, PowerPoint presentations with narratives, Customized assessment and answer keys based on local data

What Data will you use…

Filename Type Description
cfcc dbf Census Feature Class Codes

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