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COVID-19 and Minimizing Micro-spatial Interactions

ACM TRANSACTIONS ON spatial ALGORITHMS AND SYSTEMS 2022年第3期8卷 1–17页

作者： Burtner, Susan Murray, Alan T. Univ Calif Santa Barbara Dept Geog 1832 Ellison Hall Santa Barbara CA 93106 USA

COVID-19, the novel coronavirus that has disrupted lives around the world, continues to challenge how humans interact in public and shared environments. Repopulating the micro-spatial setting of an office building, with virus spread and transmission mitigation measures, is critical for a return to normalcy. Advice from public health experts, such as maintaining physical distancing from others and well-ventilated spaces, are essential, yet there is a lack of sound guidance on configuring office usage that allows for a safe return of workers. This paper highlights the potential for decision-making and planning insights through location analytics, particularly within an office setting. Proposed is a spatial analytic framework addressing the need for physical distancing and limiting worker interaction, supported by geographic information systems, network science, and spatial optimization. The developed modeling approach addresses dispersion of assigned office spaces as well as associated movement within the office environment. This can be used to support the design and utilization of offices in a manner that minimizes the risk of COVID-19 transmission. Our proposed model produces two main findings: (1) that the consideration of minimizing potential interaction as an objective has implications for the safety of work environments, and (2) that current social distancing measures may be inadequate within office settings. Our results show that leveraging exploratory spatial data analyses through the integration of geographic information systems, network science, and spatial optimization, enables the identification of workspace allocation alternatives in support of office repopulation efforts.

关键词： spatial optimization exploratory spatial data analysis network science spatial interaction health informatics

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Is social cohesion decisive for energy cooperatives existence? A quantitative analysis

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ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS 2022年 43卷 173-199页

作者： Lode, Maria Luisa Coosemans, Thierry Camargo, Luis Ramirez Mobil Logist & Automot Technol Res Ctr Pleinlaan 2 B-1050 Brussels Belgium Vrije Univ Brussel Dept Elect Engn & Energy Technol ETEC Elect Vehicle & Energy Res Grp EVERGI Pleinlaan 2 B-1050 Brussels Belgium Univ Nat Resources & Life Sci Inst Sustainable Econ Dev Feistmantelstr 4 A-1180 Vienna Austria

Energy Cooperatives (ECoops), the most prominent example for Energy Communities, are attributed great importance for the energy transition both through the engagement of energy endconsumers and the increase of local renewable energy sources. We conducted an exploratory (spatial) data analysis to study which indicators of the European Social Progress Index and Quality of Life Index co-occure with the presence of ECoops. Results show that these indexes and most of their sub-components present values significantly better at the regions where the ECoops are located compared to all EU regions. While correlation and regression coefficients between the number of ECoops per region and the indexes are relatively small, the individual indicator "Lifelong learning" reaches the highest correlation and explanatory values. Additionally, Global moran statistics show that the concentration of ECoops and their relation to the indexes in space are rather random but a local analysis shows clusters emerging throughout the continent.

关键词： Energy cooperatives Energy transition Social indicators European union exploratory spatial data analysis

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spatial Differences and Influencing Factors of Carbon Emission Intensity in China's Urban Agglomerations toward the Carbon Neutrality Target

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ATMOSPHERE 2024年第6期15卷 641页

作者： Wang, Yilin Hui, Xianke Liu, Kai Shandong Normal Univ Coll Geog & Environm Jinan 250358 Peoples R China Shandong Normal Univ Collaborat Innovat Ctr Human Nat & Green Dev Univ Jinan 250358 Peoples R China

It is of great scientific value to study the spatial differences and influencing factors of carbon emission intensity (CEI) in urban agglomerations (UAs), and it also has reference significance for China in formulating energy-saving and emission-reduction policies to achieve the target of carbon neutrality. Taking 165 prefecture-level cities in 19 UAs in China from 2007 to 2019 as the research object, this study investigated the spatial differences of CEI in UAs using exploratory spatial data analysis and explored the influencing factors of CEI via Geodetector. The results showed the following: (1) The CEI of the UAs showed a downward trend. (2) The CEI of the UAs has typical spatial agglomeration characteristics, where the North comprises mainly high-high and low-high types, whereas the South is primarily high-low and low-low types. (3) The influencing factors of CEI have undergone a transformation from industrial structure to population urbanization.

关键词： carbon emission intensity spatial differences influencing factors exploratory spatial data analysis Geodetector carbon neutrality

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Cyclical shocks and spatial association of Indonesia's district-level per capita income

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ASIAN ECONOMIC JOURNAL 2022年第3期36卷 261-287页

作者： Kataoka, Mitsuhiko Rikkyo Univ Grad Sch Business Tokyo Japan

Our exploratory spatial data analysis covered Indonesia's district-level per capita incomes for 2004-2018 and found statistical evidence of a weak but monotonically increasing positive spatial association. The spatial income clusters/outliers were scattered nationwide and expanded geographically. Applying the filtering method, we found that regional cyclical shocks significantly influenced spatial association, largely in resource-rich districts, and identified the locations of persistent spatial association that were immune to shocks. We also specified new development targets, showing the adjacent coexistence of low-income agrarian clusters with high-income mining clusters in the undeveloped Papuan provinces. The overall national average is moving toward the narrowing of inter-district income disparities. However, nearly half of all districts have widened the income disparities with their neighbors;shocks increased income gaps rather than narrowing them.

关键词： cyclical shocks exploratory spatial data analysis Geary's c Indonesia Moran's I quantile regression spatial autocorrelation

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analysis of the spatial association network structure of water-intensive utilization efficiency and its driving factors in the Yellow River Basin

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ECOLOGICAL INDICATORS 2024年 158卷

作者： Han, Xinyi Zhang, Xin Lei, Hang Northwest A&F Univ Coll Water Resources & Architectural Engn Yangling 712100 Peoples R China

Achieving the efficient, synergistic and sustainable utilization of water resources is a necessary precondition and an important means through which to protect the ecological environment of the Yellow River Basin (YRB) and promote the high-quality development of the basin's economy. This paper innovatively defines water-intensive utilization efficiency (WIUE) and constructs an appropriate evaluation index system. A superefficiency network slacks-based measure (SBM) model is introduced for measurement. The gravity model is improved, and the spatial clustering and spatial association network characteristics of water use efficiency (WUE) and water conservation and purification efficiency (WCPE) are analysed using exploratory spatial data analysis (ESDA) and social network analysis (SNA). Finally, the formation mechanism of the spatial network of WCPE is explored by using quadratic assignment procedure (QAP) regression. The following conclusions are obtained. (1) The WIUE of the YRB shows a divergent trend over time, with fluctuations in the water conservation and purification stage being the main factors influencing WIUE changes in each province. (2) Currently, the spatial association network structures of WUE and WCPE are sparse. However, with the government's basin-wide water conservation policy, the spatial relationships within the basin have gradually become more closely linked. The local clustering effect of WUE in space and the communication of technical elements in the WCPE stage in the basin are the main reasons for this network formation. Focusing on the WCPE stage, this study not only proposes policy suggestions to improve the efficiency of water resource intensification in the YRB by promoting the exchange of factors but can also be used as a reference for other basins with great regional differences.

关键词： Yellow River Basin Water-intensive utilization efficiency Superefficient network slacks-based measure model exploratory spatial data analysis Social network analysis

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Spatio-temporal evolution and factor explanatory power analysis of urban resilience in the Yangtze River Economic Belt

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Geography and Sustainability 2022年第4期3卷 299-311页

作者： Changsheng Ye Mengshan Hu Lei Lu Qian Dong Moli Gu School of Earth Sciences East China University of TechnologyNanchang 330013China

Urban resilience assesses a city’s ability to withstand unknown *** are not comprehensive in assessing urban resilience,and they lack consideration of population *** study investigated 110 prefecturelevel cities in the Yangtze River Economic Belt(YREB)as study *** calculated the YREB’s level of urban resilience based on the aspects of“economy-society-population-ecology-infrastructure”,which ensured that the comprehensive evaluation of urban resilience is complete and *** spatio-temporal evolution of urban resilience was analyzed using exploratory spatial *** were used to investigate the impact of several indicators,focusing on economic,social,population,ecological,and infrastructure factors,on urban *** results showed that the urban resilience of the YREB has maintained a slow upward trend from 2005 to 2018,and the average urban resilience of the YREB has risen from 0.2442 to *** resilience gap between cities in the study region increased initially and then *** dominant factor in the spatial differentiation of urban resilience was the economic factors,followed by the population *** resilience has been clarified and an evaluation index system is constructed,which can provide an effective reference for the evaluation of urban resilience among countries around the *** on this,factors that optimize urban resilience are configured,and the regional and national sustainable development can be promoted.

关键词： Urban resilience spatial-temporal differentiation Geographical detector exploratory spatial data analysis The Yangtze River Economic Belt

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spatial effects of carbon emission intensity and regional development in China

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2021年第11期28卷 14131-14143页

作者： Wang, Yingdong Zheng, Yueming Wuhan Univ Sci & Technol Coll Literature Law & Econ Wuhan 430065 Hubei Peoples R China

Due to the imbalance of technological level and industrial structure in regional economic development, the same carbon source can bring differentiated carbon emission levels in different regions, thus making the carbon emission show significant regional differences. In order to explore the regional differences in China's provincial carbon emission intensity and the effect of relevant influencing factors, this paper combines EKC model and STIRPAT model to conduct research. Using carbon emission intensity and other influencing factors of China's 30 provinces ranging from 2005 to 2017 to construct a panel data, the authors use exploratory spatial data analysis and spatial Durbin Model to study the spatial effect of carbon emission intensity in China's provincial regions and the impact of different development factors on carbon emission intensity. The results show that from 2005 to 2017, China's carbon emission intensity gradually declined from east to west and from south to north. The inter-provincial carbon emission intensity of China presents an agglomeration effect in space, and the agglomeration effect gradually weakens with time. In addition, reducing energy intensity can reduce carbon emission intensity to a large extent. By optimizing industrial structure, increasing the degree of foreign trade and promoting financial development, carbon emission intensity can also be inhibited. Therefore, reducing the energy intensity of various industries and establishing inter-regional carbon emission cooperation mechanism will be effective to control the carbon emission intensity.

关键词： Carbon emission intensity Energy intensity Economic development Environmental Kuznets curve exploratory spatial data analysis spatial Durbin Model

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Geographical distribution of the COVID-19 pandemic and key determinants: Evolution across waves in Spain

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GEOGRAPHICAL RESEARCH 2024年第4期62卷 486-502页

作者： Moreno, Rosina Vaya, Esther Univ Barcelona AQR IREA Barcelona Spain

Amidst the COVID-19 pandemic, most research has examined specific temporal snapshots. This study diverges by offering a comprehensive analysis of COVID-19 incidence across the Spanish provinces throughout six distinct waves of the pandemic. Using spatial exploratory techniques, we find no single pandemic;rather, there have been waves. Significant differences in the spatial distribution of cases and deaths across six waves show that each has unique characteristics. Homogeneous conclusions cannot be drawn at the national level. Notable regional differences in the pandemic's spatial distribution suggest a need for subnational responses, reflecting variations in climate, economic dynamism, sectoral specialisation, and socio-health resources. spatial regression models show that the main determinants of COVID-19 incidence depend on stage. Traditional factors commonly associated with epidemiological studies, such as temperature, exerted significant influence during the pandemic's onset. However, as mobility restrictions were enforced and vaccination campaigns were rolled out, economic conditions, and especially levels of economic activity, emerged as increasingly significant determinants.

关键词： climate COVID-19 pandemic exploratory spatial data analysis pandemic's diffusion Spanish provinces spatial regressions

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A Study on spatial Differentiation of Urban Land Prices Based on Geographically Weighted Regression Models

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International Journal for Housing Science and Its Applications 2024年第4期45卷 1-15页

作者： Liu, Qiuyu Zhang, Lina Wang, Hui Lv, Huangzhen He, Yakai Wang, Yan School of Business The Chinese University of Hong Kong Hong Kong999077 Hong Kong Chinese Academy of Agricultural Mechanization Sciences Group Co. Ltd. Beijing100083 China China National Packaging and Food Machinery Corporation Beijing100083 China

Urban residential land price is related to the basic life of residents as well as the healthy and stable development of society. In this paper, the residential land price in QZ city was selected as the research object, and the residential land price data of 107 sample points in the built-up area were collected for the 10 years from 2013 to 2022, and the exploratory spatial data analysis (ESDA) method and Geostatistical Kriging spatial Interpolation (GSI) method were combined to investigate the law of spatial heterogeneity of urban land price. Finally, general linear regression model and geographically weighted regression model are constructed to investigate the influencing factors of urban land price spatial differentiation by selecting suitable influencing factors. The sample data of residential land price in the study area basically conforms to normal distribution, and the land price shows a U-shape in the latitudinal direction, and in the horizontal direction, the land price shows a trend of decreasing from the city center to the periphery, and a "mono-core" spatial structure of decreasing from the center to the periphery. There are large regional differences in the contribution of plot ratio, distance from main roads, distance from hospitals and distance from schools to residential land price, among which the marginal effect of plot ratio on residential land price reaches 122.5385yuan/m2 which reflects the importance of plot ratio to residential land price. The study provides a decision-making basis for government targeted land planning, urban infrastructure investment and real estate development. © 2024 International Association for Housing Science. All rights reserved.

关键词： exploratory spatial data analysis geographic weighting land price urban residential volume ratio

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spatial-temporal evaluation of total-factor energy efficiency in Chinese construction industry based on three-stage super-efficiency SBM-DEA model

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ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT 2024年

作者： Shi, Qianqian Wang, Ziyu Nanjing Univ Aeronaut & Astronaut Coll Econ & Management Nanjing Peoples R China

Purpose- The study aims to enhance energy efficiency within the high-energy consuming construction industry. It explores the spatial-temporal dynamics and distribution patterns of total factor energy efficiency (TFEE) across China's construction industry, aiming to inform targeted emission reduction policies at provincial and city levels. Design/methodology/approach- Utilizing a three-stage super-efficiency SBM-DEA model that integrates carbon emissions, the TFEE in 30 Chinese provinces and cities from 2004 to 2019 is assessed. Through kernel density estimation and exploratory spatial data analysis, the dynamic evolution and spatial patterns of TFEE are examined. Findings- analysis reveals that environmental investments positively impact TFEE, whereas Gross Regional Product (GRP) exerts a negative influence. R&D expenditure intensity and marketization show mixed effects. Excluding environmental and random factors, TFEE averages declined, aligning more closely with actual development trends, showing a gradual decrease from east to west. TFEE exhibited fluctuating growth with a trend moving from inefficient clusters to a more even distribution. spatially, TFEE demonstrated aggregation effects and characteristics of space-time transition. Originality/value- This research employs the three-stage super-efficiency SBM-DEA model to measure the total factor energy efficiency of the construction industry, taking into account external environment, random disturbances, and multiple effective decision-making units. It also evaluates energy efficiency changes before and after removing disturbances and comprehensively examines regional and temporal differences from static and dynamic, overall and phased perspectives. Additionally, Moran scatter plots and LISA cluster maps are used to objectively analyze the spatial agglomeration and factors influencing energy efficiency.

关键词： Total-factor energy efficiency spatial and temporal distribution Construction industry Three-stage super-efficiency SBM-DEA exploratory spatial data analysis spatial agglomeration effect

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