Determining Urban Emotion using a Supervised Learning Approach: A Case Study around Majitar, East

Abstract

Perception and expectation of citizens is an important factor in urban settlement, planning and management. Hence, there is a need of a participatory citizen centric planning of urban settlement based on spatial data. These perception and expectation may be represented in terms of emotions. Determining Urban Emotions is an approach which can be used to map different types of emotions associated with urbanization. In the recent years, some new methods have been presented for the area of urban and spatial planning, which resulted in a fundamental change of the issues and understanding of urban planning. Geographical information system acts as a key factor for analyzing urban emotions from various types of data. This paper presents the supervised learning approach for determining urban emotions using K-Nearest Neighbor algorithm.