**2. Literature Review**

In addition to a qualitative and conceptual description of urban morphology, recent studies have been performed for the quantitative representation of urban morphology, such as data discretization methods [18]. Researchers utilized various quantification methods for morphology-to-data transmission by selecting and adjusting indicators. Deep learning models were used to automatically learn features and classifiers at once by error backpropagation, adjusting the layers' importance depending on the problem. Then, similarity analysis techniques were used to construct an efficient case retrieval system based on the feeding samples [19].
