3.5. Image Classification Techniques

Try these first

1. 1.

   What is supervised classification?

   Hint

   Think about how the algorithm learns from examples.

2. 2.

   Name one algorithm used in unsupervised classification.

   Hint

   Consider clustering methods.

3. 3.

   What does supervised classification rely on?

   • Unlabeled data
   • Training data
   • Random data

   Hint

   Focus on the concept of training examples.

4. 4.

   True or False: Unsupervised classification requires labeled training data.

   • True
   • False

   Hint

   Think about the nature of data being used.

5. 5.

   Imagine you are tasked with classifying a new satellite image of a forested area. Discuss which classification technique you would choose: supervised or unsupervised. Justify your choice based on the availability of training data.

   Hint

   Consider your resources for classification.

6. 6.

   Provide a detailed explanation of how you would apply Object-Based Image Analysis in urban environments, and the factors that would influence the classification results.

   Hint

   Reflect on urban characteristics that affect image segmentation.