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Spatial differentiation (standardized) of the cases aggregation with different spatial scales: (a)Beijing (XFD), (b)Dalian (KSF), (c)Tonghua (YQL).
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From the onset of the COVID-19 pandemic in 2020, studies on the microgeographies of epidemics have surged. However, studies have neglected the significant impact of multiple spatiotemporal units, such as report timestamps and spatial scales. This study examines three cities with localized COVID-19 resurgence after the first wave of the pandemic in...
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... understand the importance of spatial scale selection in epidemiological research, the standardized spatial patterns of localized outbreaks with three spatial scales were demonstrated (Fig. 2). The standardized spatial pattern reports the strong spatial heterogeneity of epidemic statistics results when adopting these three spatial scales. It is worth noting that this spatial differentiation is smaller in areas far from the epidemic source, and larger in areas close to the epidemic source, which are also the high incidence ...
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... Urban residential networks provide the basis for studying urban social relationships and disease transmission. The transmission of social relationships, opinions, and even epidemics through contact between urban residents has driven research on group decision games, the expression of social will [72], and the prediction of epidemic transmission pathways [73]. It provides new ideas for revealing the spatial structure of such invisible networks of relationships and for intervening through spatial means. ...
Residential areas are primary functional spaces of urban built-up areas, representing urban social structure externally and influencing urban spatial fabric (SF). Chinese cities have increasingly experienced urban renewal following significant population growth and urban expansion in the last four decades. We selected built-up urban areas of Shanghai as the research scope, considering 6731 residential quarters as research objects, which were identified and classified into six types. Based on complex network theory and analysis methods, an urban residential spatial network (URSN) was constructed in central Shanghai implementing through code. The degree of distribution and network robustness of the URSN was examined, and network “communities” were identified. The findings indicate that URSN stability, like robustness, implies harmonious and smooth social interactions and information transfer, consistent with the SDG 11, where the large-degree node residential quarters play an important role and must be prioritized in urban renewal. Meanwhile, the identification results of the URSN “communities” help us understand territory identity in built-up urban areas. This research provides new concepts and methods for examining SF in urban residential areas that integrate “physical” and “social” spaces, compares this approach to the traditional point-axis structure, and pioneers the study of urban SF from the perspective of complex networks by providing a new way of visualizing the spatial relationship between residential quarters as a network-like structure.
... Assessing the impact of climate variation on vegetation change not only helps to elucidate the mechanisms involved in ecosystem processes, but also has important theoretical and practical implications for assessing the impact of environmental change on ecosystem quality (Zhang et al., 2022). With increasing global warming and inter-annual variation in precipitation, numerous studies have revealed a strong relationship between climate and vegetation (Huang et al., 2020;Huete, 2016). ...
Despite numerous studies on the response of vegetation change to climate variation, they have mainly been based on annual mean temperature and annual mean precipitation, and have failed to reveal the impact of climate on the inter-annual variation of vegetation in different geomorphic zones based on non-linear methods and considering daily low and high temperature. In this study, the effect of climate variation on the inter-annual variation of vegetation in different geomorphic zones along the area of t the Yangtze River Basin, China from 1982 to 2015 is revealed using Ensemble Empirical Mode Decomposition method. The results show that the inter-annual variation of vegetation is frequently fluctuating, mainly on a short time scale (3-year time scale), and its contribution gradually increases from 62.35% to 73.57% with increasing relief (from plain to high undulating mountain). The vegetation change of more than 75% of the areas is dominated by inter-annual variations, moreover, the vegetation change of the low relief areas is dominated by the 3-year timescale along with the long-term trend, while that of the other geomorphic zones is dominated by the 3-year timescale only. Inter-annual vegetation variation is positively related to precipitation and maximum temperature, but negatively related to mean temperature and minimum temperature in most areas, with area percentages of 67.20%, 86.55%, 65.38% and 75.02%. Inter-annual variation is mainly controlled by maximum temperature in most areas (54.77%). These results will deepen our understanding of the vegetation-climate relationship, suggesting that the responses of inter-annual variation in vegetation to climate vary not only on different time scales, but also in indifferent geomorphic zones.
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Flooding is a natural hazard that touches nearly all facets of the globe and is expected to become more frequent
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about using such indicators, given the real-life consequences that can occur due to the MAUP. The results of this
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... In this paper, we start from the previous works on the negative impact of Covid-19 epidemic on FDI, and extend our discussion to the spatial spillover effects of the epidemic. Since previous studies mainly narrow down focus on the geographic spillover effects of the epidemic on global FDI (Florida & Mellander, 2022), we propose that the spillover effects of Covid-19 shock, both spatially and temporally (Zhang et al., 2022), can be inherently different in an economic network formed by global OFDI linkages. The above-mentioned spillover mechanisms are shown in Fig. 1 below. ...
The outbreak of Covid-19 epidemic has a prolonged impact on global economic activities. In recent years, many scholars have been motivated to estimate the effects of Covid-19 shock on global foreign direct investment (FDI). However, existing studies have not paid enough attention to the spillover effects caused by the epidemic. Although few academic works have explored the geographic-neighboring spillover effects of epidemic shock on global investment, we further extent the understanding of the spillover effects in an economic network. On the basis of country-month greenfield FDI panels, we construct a spatial Durbin model, and figure out that Covid-19 shock may have positive FDI spillover effects in an economic network via global FDI transfers. Furthermore, we find that such spillovers are greatly conditioned by country-level network position and institutional ties among nations. Our research suggests that global FDI transfers may partly offset economic-adverse effects of the Covid-19 shock. While global countries, especially those in the Global South, should be more closely embedded in the global investment network in such an uncertain environment.
