Jia Wan

Mrs. Jia Wan


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 October 2020 in Sustainability
Verified
Journal Article
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JWJia Wan
Jia Wan
LZLiwei Zhang
Liwei Zhang
JYJunping Yan
Junping Yan
XWXiaomeng Wang
Xiaomeng Wang
TWTing Wang
Ting Wang
Urban agglomeration is the core area of not only regional economic development and urbanization but also human–land contradiction. Based on the population–economy–society–spatial model and the pressure–state–response model, this study develops an evaluation index system for the urbanization and eco-environment of 13 urban agglomerations in China. The urbanization index and eco-environment index are determined using the coefficient of variation method. The coupled coordination of the two indices is measured with the coupled coordination model, and the influence of the indicator factors is calculated with a geographical detector. The results reveal the following: (1) The urbanization indices of the 13 urban agglomerations in China increase year by year, and the spatial distribution pattern is high in the east and low in the west. (2) The eco-environment index shows an “S-shaped” variation trend, and the spatial difference between urban agglomerations gradually decreases. (3) The coupled coordination is mainly characterized as a mild imbalance, and the spatial distribution pattern is “balance in the east and imbalance in the west”. (4) The coupled coordination degree between urbanization and eco-environment is affected by many factors. Among such factors, economic urbanization, social urbanization, spatial urbanization, and eco-environment response are the main controlling factors. The impact of population urbanization, eco-environment pressure, and eco-environment state presents a gradual increase.

12 July 2024 in Sustainability
Verified
Journal Article
Open access
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JWJia Wan
Jia Wan
RDRuiyin Dou
Ruiyin Dou
TMTao Ma
Tao Ma
Investigating the distribution characteristics of earthquake disaster risks in the Sichuan–Yunnan region is of great importance for enhancing government emergency response capabilities and achieving sustainable regional development. This study, based on disaster systems theory, constructs a seismic risk evaluation index system for the Sichuan–Yunnan region and employs the entropy method to determine the comprehensive risk index for earthquake disasters across 37 prefecture-level cities. The findings reveal the following: (1) High-risk areas for disaster-causing factors are located in the Hengduan Mountain region and the North–South Mountain Range Valley Region; medium-risk areas are distributed along the northwestern edge of the Sichuan Basin; low-risk areas are situated in the eastern part of the Sichuan Basin and the Yunnan Plateau. (2) High-risk disaster-prone environments are found in the Hengduan Mountain region; medium-risk areas are present on the Yunnan Plateau and the western part of the North–South Mountain Range Valley Region; low-risk areas are in the Sichuan Basin. (3) High-vulnerability areas include the central Sichuan Basin and Kunming on the Yunnan Plateau; medium-vulnerability areas are located in the eastern and western parts of the Sichuan Basin; low-vulnerability areas are in the less developed parts of the Yunnan Plateau, the North–South Mountain Range Valley Region, and the Hengduan Mountain region. (4) High-risk seismic disaster areas are concentrated in the developed regions of the Sichuan Basin and the Yunnan Plateau; medium-risk areas are concentrated in the western part of the North–South Mountain Range Valley Region; low-risk areas are sporadically distributed in the eastern parts of the Sichuan–Yunnan region. (5) The vulnerability of the population, economy, and lifeline systems significantly explain the variation in seismic risk levels, all exceeding 0.70; the synergistic effects of disaster-causing factor danger, disaster-prone environment stability, and disaster-prone environment sensitivity are the most pronounced, with explanatory power exceeding 0.85 after factor interaction.

1 September 2021 in Applied Geophysics
Verified
Journal Article
Closed access
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JWJia Wan
Jia Wan
JYJunping Yan
Junping Yan
ZLZi-Qiang Liu
Zi-Qiang Liu
XWXiao-Meng Wang
Xiao-Meng Wang
YZYu-Feng Zhang
Yu-Feng Zhang
CWCheng-Bo Wang
Cheng-Bo Wang

11 November 2020 in E3S Web of Conferences
Verified
Conference Paper
Open access
PDF file
JWJia Wan
Jia Wan
JYJunping Yan
Junping Yan
XYXiaomeng Yan
Xiaomeng Yan
Commensurability information, a butterfly diagram and a commensurability structure system were used to analyse the spatiotemporal symmetry and to assess the trends of Ms≥7.0 earthquakes in the Sichuan-Yunnan region of China. The results show that the next earthquake may occur in 2020 or 2021, as seismic signals are strong. Analysing the characteristics of epicentre spatial migration, there is a significant synchrony and symmetry between the latitudinal and longitudinal epicentre migrations. The symmetry axis is 30°N in latitude and 101.5°E in longitude. There is a northeast–southwest strike symmetry axis, and the next epicentre may migrate toward the southwest (i.e., south of 30°N and west of 101.5°E); the calculated strike symmetry axis is Y=3.5X-329. By grouping earthquake disaster events, the spatial migration pathways of the epicentres regularly exhibit jump-migration and sequential-migration. The migration distributions over the symmetry axis quadrants are ‘uniform-discrete’ and ‘concentrated-dispersion’.