Assessing Spatiotemporal Built-up Dynamics in Chiang Mai City, Thailand using Entropy approach

Abstract

The rates of urban dynamics affecting by industrialization, urban agglomeration, and large-scale migration turn its behaviour from monocentric to polycentric metropolitan resulting in unprecedented urban growth. Therefore, the present study incorporated an entropy-based approach to measure the degree of compactness and dispersiveness of urban development in Chiang Mai City. The Object-based machine learning was deployed for the image classifications with an overall accuracy above the minimum requirements (i.e., 90%) and kappa statistic of agreement above 0.85. The study reveals that Chiang Mai city has undergone urban development outskirts from the urban centre (CBD) and north and south-west direction from the CBD. A considerable increase in urban demographic and physical urban patches was observed in last 1998 to 2018. The research emphasized the significant role of Shannon Entropy to analyze the built-up growth supplemented by Remote Sensing and Geographic Information System (GIS) in respective zones and geographical directions.

Cartography and analysis of the urban growth, case study: Inter-communal grouping of Batna, Algeria

“…Different studies using Shannon entropy such as the study of Bhattacharjee (2019) employed Shannon entropy estimation to determine the rate of urban growth in the city of Silchar. Gyeltshen et al (2022) have done a study that uses entropy to measure the degree of compactness and dispersion of urban development in the city of Chiang Mai. Serdaroğlu Sağ (2021) assessed the urban development pattern and sprawl using Shannon's entropy: a case study of Konya (Turkey), and Aprillia and Pigawati (2018) used the Shannon entropy to analyse and determine the location of the sprawl in the city of Semarang.…”