Spatiotemporal influence analysis model for cultural landscapes based on a virtual geographic environment DOI Creative Commons

Xiangfei She,

Xin Pan,

Jian Zhao

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 10, 2025

A cultural landscape can have a lasting impact on the surrounding region, significantly influencing its culture, customs, and development patterns. It is therefore important to understand spatiotemporal influence range of particular landscape. The scope affected by subjective factors regarding views, hobbies, communication, cognitive abilities all individuals involved in interaction. These are difficult account for using learning process traditional methods. To address this problem, we propose analysis model landscapes based virtual geographic environment (SC-VGE). constructed interactively recognize relationships between landscapes, forming key parameters propagation under various conditions. On basis, construct agents representing different groups people. Based movement space, determine specific or object. In experiments, analyzed two typical examples city Changchun. We conducted comparative our approach against several methods, including Spatial Straight-Line Distance, Accessible Cellular Automata, Multiagent. SC-VGE method surpassed these methods overall prediction accuracy, achieving 89.7 ± 1.3% 87.8 1.5%. This more than 9% higher highest accuracy among Higher enables precisely reflect ranges thereby providing better support management value.

Language: Английский

Spatiotemporal influence analysis model for cultural landscapes based on a virtual geographic environment DOI Creative Commons

Xiangfei She,

Xin Pan,

Jian Zhao

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 10, 2025

A cultural landscape can have a lasting impact on the surrounding region, significantly influencing its culture, customs, and development patterns. It is therefore important to understand spatiotemporal influence range of particular landscape. The scope affected by subjective factors regarding views, hobbies, communication, cognitive abilities all individuals involved in interaction. These are difficult account for using learning process traditional methods. To address this problem, we propose analysis model landscapes based virtual geographic environment (SC-VGE). constructed interactively recognize relationships between landscapes, forming key parameters propagation under various conditions. On basis, construct agents representing different groups people. Based movement space, determine specific or object. In experiments, analyzed two typical examples city Changchun. We conducted comparative our approach against several methods, including Spatial Straight-Line Distance, Accessible Cellular Automata, Multiagent. SC-VGE method surpassed these methods overall prediction accuracy, achieving 89.7 ± 1.3% 87.8 1.5%. This more than 9% higher highest accuracy among Higher enables precisely reflect ranges thereby providing better support management value.

Language: Английский

Citations

0