Understanding the historical evolution of spatial layout and architectural styles in a historic area is imperative for its preservation and rejuvenation.However,conventional methods such as document collation and feld...Understanding the historical evolution of spatial layout and architectural styles in a historic area is imperative for its preservation and rejuvenation.However,conventional methods such as document collation and feld surveys are time-and resource-intensive.This research focuses on the historic area of Dujiangyan city(Dujiangyan Old Town)and uses computer vision techniques to increase the efciency and accuracy of architectural information capture.Semantic segmentation techniques are employed to derive building footprints from remote sensing satellite images captured from three points in time over a period of nearly fve decades,facilitating the comparison of spatial patterns and the identifcation of diferent architectural styles in panoramic street views.The distribution of architectural styles is analysed from urban planning and architectural perspectives.The experimental fndings illustrate well-preserved spatial patterns and discernible development strategies across various periods.Image-processing methods have emerged as efective tools for analysing urban spatial dynamics and identifying architectural styles,thereby yielding quantifable data essential for obtaining a nuanced understanding of historic areas.These insights can contribute to planning,management,and preservation eforts aimed at historic areas.展开更多
基金supported by JST SPRING,Grant Number JPMJSP2136.
文摘Understanding the historical evolution of spatial layout and architectural styles in a historic area is imperative for its preservation and rejuvenation.However,conventional methods such as document collation and feld surveys are time-and resource-intensive.This research focuses on the historic area of Dujiangyan city(Dujiangyan Old Town)and uses computer vision techniques to increase the efciency and accuracy of architectural information capture.Semantic segmentation techniques are employed to derive building footprints from remote sensing satellite images captured from three points in time over a period of nearly fve decades,facilitating the comparison of spatial patterns and the identifcation of diferent architectural styles in panoramic street views.The distribution of architectural styles is analysed from urban planning and architectural perspectives.The experimental fndings illustrate well-preserved spatial patterns and discernible development strategies across various periods.Image-processing methods have emerged as efective tools for analysing urban spatial dynamics and identifying architectural styles,thereby yielding quantifable data essential for obtaining a nuanced understanding of historic areas.These insights can contribute to planning,management,and preservation eforts aimed at historic areas.
