A5090753505- Spatial and Panel Data Analysis
- Urban Transport and Accessibility
- Land Use and Ecosystem Services
- Housing Market and Economics
- Urban, Neighborhood, and Segregation Studies
- Regional Economics and Spatial Analysis
- Economic and Environmental Valuation
- Air Quality and Health Impacts
- Regional Economic and Spatial Analysis
- Psychological Well-being and Life Satisfaction
- Remote Sensing in Agriculture
- Energy, Environment, Economic Growth
- Urban Green Space and Health
- Place Attachment and Urban Studies
- Remote Sensing and Land Use
- Tree-ring climate responses
- Impact of Light on Environment and Health
- Environmental Changes in China
- Evaluation Methods in Various Fields
- Environmental Justice and Health Disparities
- Structural Response to Dynamic Loads
- Conservation, Biodiversity, and Resource Management
- Korean Urban and Social Studies
- Health disparities and outcomes
- Soil Geostatistics and Mapping
Henan University
2018-2025
Ministry of Education of the People's Republic of China
2020-2024
Yellow River Institute of Hydraulic Research
2024
Development Research Center
2022
University of Liverpool
2016-2020
University of Sheffield
2014-2017
HBIS (China)
2016
Institute of Geographic Sciences and Natural Resources Research
2016
Chinese Academy of Sciences
2016
University of Bristol
2012-2015
Abstract In order to investigate the response of structures near‐fault seismic excitations, ground motion input should be properly characterized and parameterized in terms simple, yet accurate reliable, mathematical models whose parameters have a clear physical interpretation scale, extent possible, with earthquake magnitude. Such model for representation coherent (long‐period) components has been proposed by authors previous study is being exploited this article investigation elastic...
Geographically Weighted Regression (GWR) is increasingly used in spatial analyses of social and environmental data. It allows heterogeneities processes relationships to be investigated through a series local regression models rather than single global one. Standard GWR assumes that between the response predictor variables operate at same scale, which frequently not case. To address this, several variants have been proposed. This paper describes route map decide whether use model or not, if...
This article discusses how standard spatial autoregressive models and their estimation can be extended to accommodate geographically hierarchical data structures. Whereas econometric normally operate at a single geographical scale, many sets are in nature—for example, information about houses nested into the census tracts which those found. Here we outline four model specifications by combining different formulations of weight matrix W ways modeling regional effects. These (1) groupwise...
This paper develops a methodology for extending multilevel modelling to incorporate spatial interaction effects. The motivation is that classic models are not specifically spatial. Lower level units may be nested into higher ones based on geographical hierarchy (or membership structure—for example, census zones regions) but the actual locations of and distances between them directly considered: what matters groupings how close together any two within those groupings. As consequence, effects...
The trade-offs of ecosystem services (ES) are at the frontier geographical and ecological studies. However, previous studies have focused on either supply-supply trade-off or supply–demand trade-off, while integrated research three types for ES (i.e. demand-demand trade-off) needs to be further studied. This study establish an analytical framework. framework was then applied a sub-watershed Yellow River in China (i.e., Fenghe watershed). Based quantitative assessment both supply demand ES,...
Environmental pollution is a major problem in China, subjecting people to significant health risk. Surprisingly little known, though, about how these risks are distributed spatially or socially. Drawing on large-scale survey conducted Beijing 2013, we examine environmental hazards and health, as perceived by residents, at fine (subdistrict) scale urban investigate the association between hazards, geographical context. A Bayesian spatial multilevel logistic model developed account for...
This article explores how to incorporate a spatial dependence effect into the standard multilevel modeling (MLM). The proposed method is particularly well suited analysis of geographically clustered survey data where individuals are nested in geographical areas. Drawing on multivariate conditional autoregressive models, we develop random slope MLM approach account for within-group among same area and between areas simultaneously. Our improves recent methodological advances integrated...
Abstract G eographically W eighted R egression ( GWR ) is a method of spatial statistical analysis allowing the modeled relationship between response variable and set covariates to vary geographically across study region. Its use geographical weighting arises from expectation that observations close together by distance are likely share similar characteristics. In practice, however, two points can be but socially distant because contexts (or neighborhoods) within which they situated not...
Abstract ‘Social frontiers’ – places of sharp difference in social/ethnic characteristics between neighbouring communities have largely been overlooked quantitative research. Advancing this nascent field first requires a way identifying social frontiers robust way. Such may be ‘open’ an area contrast sharply with neighbourhood one direction, but blend smoothly into adjacent neighbourhoods other directions. This poses some formidable methodological challenges, particularly when computing...
Abstract Millions of Chinese migrants have moved from the countryside to cities seek job opportunities and a better life. Under policy shift “land‐based urbanisation” “people‐oriented urbanisation,” it is important understand what determines migrants' settlement intentions. Although previous studies primarily focused on sociodemographic impacts intention, role city‐level contexts understudied. Drawing upon data, 2015 Migrant Dynamic Monitoring Survey in Yangtze River Delta, this paper...
The Geographical Detector Model (GDM) is a popular statistical toolkit for geographical attribution analysis. Despite the striking resemblance of q-statistic in GDM to R-squared linear regression models, their explicit connection has not yet been established. This study proves that reduces into under framework. Under and moderate-to-strong spatial autocorrelation, Monte Carlo simulation results show tends underestimate importance variables. In addition, an almost perfect power law...
Desertification is a form of land degradation observed in arid, semiarid, and dry subhumid ecosystems. Assessing the global trends drivers desertification arid crucial for developing effective restoration policies mitigating desertification. We aimed to evaluate segmental using Moderate Resolution Imaging Spectroradiometer images from 2000 2022. By constructing robust MSAVI-Albedo Distance Index (DDI), we assessed segmented development characteristics on Google Earth Engine. Additionally,...