Practice Unsupervised Classification (5.17.3.B) - Texture

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9 questions

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6 questions · about 4 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is the main focus of unsupervised classification?
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Think about what kind of data this classification relies on.
Question 2.
Name one algorithm used in unsupervised classification.
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Consider popular clustering methods.
3Question 3.
What does unsupervised classification rely on?
- Training samples
- Spectral properties
- Ground truth data
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Consider the absence of training in this method.
4Question 4.
True or False: ISODATA is a clustering algorithm that requires training samples.
- True
- False
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What type of classification is ISODATA associated with?
Question 5.
Suppose you have satellite imagery of a forest area with varying tree types. Describe how you would apply unsupervised classification and what considerations you would account for.
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Think about how diversity in the forest might impact classification.
Question 6.
What strategies could you use if your unsupervised classification resulted in ambiguous clusters?
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What might you look for to clarify your clusters?

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