Learning Module 11.1
Image Classification

Introduction

In this module, we will cover image classification techniques. Image Classification is the process of grouping areas of an image into a number of classes or categories that represent similar features. The process produces "thematic maps" based on the original image or data. Unlike image interpretation, which is carried out by a human, the majority of these classification techniques are carried out by a computer. Image classification is used in many regional-scale projects and is often done to generate land cover data sets.

Learning Outcomes

• Understand the difference between pixel based and object classification methods.
• Learn how to conduct supervised and unsupervised classification procedures in ENVI.
• Evaluate different classification methods and select appropriate methods.
• Analyze classification results, including labeling, color coding classes and calculating the area of classes.

Readings

• Read pages 281-299 in Principles of remote sensing: An introductory textbook

Presentations and Content

• Classification Overview
• Unsupervised Classification
• Supervised Classification
• Object-Based Classification
• Land Use/Land Cover Data

Lab 11

• Lab 11: Image Classification

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