Evidence map›Paper›PMID 40210667›Full record

ArticleScientific reports2025

Spatiotemporal influence analysis model for cultural landscapes based on a virtual geographic environment.

Xiangfei She, Xin Pan, Jian Zhao

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Xiangfei SheSchool of Computer Technology and Engineering, Changchun Institute of Technology, Changchun, 130012, China.
Xin PanSchool of Computer Technology and Engineering, Changchun Institute of Technology, Changchun, 130012, China. panxin@neigae.ac.cn.
Jian ZhaoSchool of Computer Technology and Engineering, Changchun Institute of Technology, Changchun, 130012, China.

Funding

Foundation of Jilin Provincial Science & Technology Department YDZJ202401340ZYTS
6 · The paper itself

Abstract

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

Indexed as

Cultural landscapesMultiagentSpatiotemporal influenceVGEVR

Identifiers

PMID40210667
PMCPMC11986163

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.