<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In the conservation of the historical landscape within the Guangfu Ancient City Core Protection Area, traditional descriptions via drawings and textual narratives often exhibit subjective biases. To address this, a theoretical model for the historical architectural landscape has been developed to objectively measure and characterize the spatial patterns and morphologies of the landscape. This study introduces Exploratory Spatial Data Analysis (ESDA) techniques, utilizing spatial weights and spatial correlation measures as primary analytical tools. Additionally, meta-cellular automata are employed to simulate the spatial and temporal evolution of the historical landscape. Geographical Information Systems (GIS) and Remote Sensing (RS) technologies have been leveraged to establish a spatial database and facilitate the visualization of the historical landscape’s evolutionary processes. This integrated model and technological approach enable a detailed analysis of the architectural landscape characteristics and the spatial structure’s evolution within the study area. The findings reveal distinct spatial distribution characteristics, with an undulation index ranging from 5 to 20 and a predominant index over 7, accounting for 15.67% of the land. Based on these insights, the study proposes strategic interventions to safeguard the historical integrity of Guangfu Ancient City’s core conservation area.</p>
</abstract>

In the conservation of the historical landscape within the Guangfu Ancient City Core Protection Area, traditional descriptions via drawings and textual narratives often exhibit subjective biases. To address this, a theoretical model for the historical architectural landscape has been developed to objectively measure and characterize the spatial patterns and morphologies of the landscape. This study introduces Exploratory Spatial Data Analysis (ESDA) techniques, utilizing spatial weights and spatial correlation measures as primary analytical tools. Additionally, meta-cellular automata are employed to simulate the spatial and temporal evolution of the historical landscape. Geographical Information Systems (GIS) and Remote Sensing (RS) technologies have been leveraged to establish a spatial database and facilitate the visualization of the historical landscape’s evolutionary processes. This integrated model and technological approach enable a detailed analysis of the architectural landscape characteristics and the spatial structure’s evolution within the study area. The findings reveal distinct spatial distribution characteristics, with an undulation index ranging from 5 to 20 and a predominant index over 7, accounting for 15.67% of the land. Based on these insights, the study proposes strategic interventions to safeguard the historical integrity of Guangfu Ancient City’s core conservation area.

Study on the historical landscape evolution of the core reserve of Guangfu Ancient City based on computer simulation

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In the conservation of the historical landscape within the Guangfu Ancient City Core Protection Area, traditional descriptions via drawings and textual...

Study on the historical landscape evolution of the core reserve of Guangfu Ancient City based on computer simulation

Pubblicato online: 07 giu 2024

Pagine: -

Ricevuto: 20 feb 2024

Accettato: 01 mag 2024

DOI: https://doi.org/10.2478/amns-2024-1413

Parole chiave
ESDA technology, Spatial correlation measurement, Meta cellular automata, GIS, Spatial database

© 2024 Qinghong Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Study on the historical landscape evolution of the core reserve of Guangfu Ancient City based on computer simulation

Pubblicato online: 07 giu 2024

Pagine: -

Ricevuto: 20 feb 2024

Accettato: 01 mag 2024

DOI: https://doi.org/10.2478/amns-2024-1413

Parole chiaveESDA technology, Spatial correlation measurement, Meta cellular automata, GIS, Spatial database

© 2024 Qinghong Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
ESDA technology, Spatial correlation measurement, Meta cellular automata, GIS, Spatial database