Content

Introduction
Readings
Fundamental Concepts
Self Check
Activities & Assignments
Summary
Self Review

Topic Introduction

For this topic we will focus on raster data, which is the common data type for imagery analysis in remote sensing. Understanding basic image enhancement and spatial filters is an important step in analyzing raster data. Classification is a common technique used to efficiently categorize land-cover, however being able to explain error and understand accuracy assessments is vital to justifying your classification.

Topic Readings

Required & Optional Readings

There are no readings for this topic.

Fundamental Concepts

Lecture Video and Powerpoint

Imagery Analysis

FODE009_4.1 Basic Image Processing.pdf

Self Check (For certificate learning only)

Self-check Quiz 4.1

Quiz Questions:

Are computer screens additive or subtractive color systems?
What is a false color composite?
What is the relationship between the number of classes you create for classification and the accuracy of your result?
What is the difference between training and testing data?
How do you calculate users accuracy from an error matrix?

Check Answers:

Instructions: Take the quiz by clicking Self-check Quiz 4.1 and compare your answer with the Model Answer after your attempt.

Activities & Assignments (For certificate learning only)

Class Forum Topic 4.1

Follow detailed requirements in FODE009_Forum Post 4.1.docx to prepare your forum post for this week. For general participation and grading criteria, please see detailed description on under Modules > Graded Assignments > Class Forum Discussions.

Assignment/Lab 6: Classification and Accuracy Assessment

Start doing Assignment/Lab 6 for this week. For detailed instructions and grading criteria, please see detailed descriptions under Modules > Graded Assignments > Assignment 6. You may use FODE009_Assignment 6 Answer Sheet.docx to put together your answers to the questions in the lab.

Topic Summary

Choosing which spectral channels or bands to be represented on your colour guns provides a variety of strategies that can allow you to meaningfully interpret your image. The enhancements and filters we have gone over is not an exhaustive list, there are countless other ways to filter images, but we have introduced the basic ones to get you started. Classification is a very important tool that can be applied to a variety of different fields, how might you apply classification to improve sustainable forest management? Lastly, accuracy assessments need to be conducted to validate classifications for yourself, but also for your colleagues or potential employers.

Topic Self-review (For self learning)

Please use the reflection questions below as study guide to conduct self-review for the topic.

List and describe several different kinds of image enhancements and filters.
Explain why we would want to classify images.
Describe the procedures, pros and cons associated with supervised and unsupervised classification.
What causes classification error?
How do you conduct an accuracy assessment?

FODE009