Local Autocorrelation Analysis Research Articles

Spatial-temporal distribution characteristics of pulmonary tuberculosis in eastern China from 2011 to 2021.

China is still among the 30 high-burden tuberculosis (TB) countries in the world. Few studies have described the spatial epidemiological characteristics of pulmonary TB (PTB) in Jiangsu Province. The registered incidence data of PTB patients in 95 counties of Jiangsu Province from 2011 to 2021 were collected from the Tuberculosis Management Information System. Three-dimensional spatial trends, spatial autocorrelation, and spatial-temporal scan analysis were conducted to explore the spatial clustering pattern of PTB. From 2011 to 2021, a total of 347,495 newly diagnosed PTB cases were registered. The registered incidence rate of PTB decreased from 49.78/100,000 in 2011 to 26.49/100,000 in 2021, exhibiting a steady downward trend (χ2=414.22, P<0.001). The average annual registered incidence rate of PTB was higher in the central and northern regions. Moran's I indices of the registered incidence of PTB were all >0 (P<0.05) except in 2016, indicating a positive spatial correlation overall. Local autocorrelation analysis showed that 'high-high' clusters were mainly distributed in northern Jiangsu, and 'low-low' clusters were mainly concentrated in southern Jiangsu. The results of this study assist in identifying settings and locations of high TB risk and inform policy-making for PTB control and prevention.

Analysis of Spatial-Temporal Evolution Pattern and Its Influencing Factors of Warehouse Supermarkets in Liaoning Province

Based on the data of existing warehouse supermarkets in Liaoning Province, China, spatial autocorrelation analysis, kernel density analysis, composite correlation coefficient analysis and other methods have been adopted to analyze their spatial-temporal evolution pattern to reflect the general law of the development of China’s existing warehouse supermarkets and fill the gap in this research field. The results show that the spatial distribution of warehouse supermarkets in Liaoning Province is extremely uneven, and areas with high nuclear density are distributed along the “Shenyang-Dalian” line belonging to the aggregation distribution. The Lorentz curve shows a downward trend with a large degree of spatial imbalance, that is, the regional concentration of warehouse supermarkets is high. Through global and local autocorrelation analysis, the regions with similar development levels of warehouse supermarkets in Liaoning Province tend to gather together, and the spatial distribution has a strong correlation. The distribution of warehousing supermarkets in Liaoning Province is affected by traffic location conditions, economic conditions, population quantity and population density, the number of urban functional areas, policy conditions and the role of the government, especially by economic conditions.

Trends in Forest Greening and Its Spatial Correlation with Bioclimatic and Environmental Factors in the Greater Mekong Subregion from 2001 to 2020

Understanding trends of vegetation evolution and its spatial characteristics is critical for sustainable social development in the Greater Mekong Subregion (GMS), which is densely populated and still has uneven economic development. Through Theil–Sen/Mann–Kendall tests, polynomial regression and bivariate local autocorrelation analyses, we investigated vegetation greening trends and their spatial correlation with bioclimatic and environmental variables. The study yielded the following results: (1) Land cover in the GMS has changed significantly over the last 20 years. Conversion between forest and grassland was the main type of change. (2) The upward trend in the forest enhanced vegetation index (EVI) significantly exceeded the downward trend in countries over 20 years. In GMS, the spatial variation in forest trend slope values ranged from −0.0297 a−1 to 0.0152 a−1. (3) Anthropogenic activities have played an important role in forest greening; planted, plantation and oil palm forests exhibit the largest contributions to greening. (4) Changes in forest EVI were most spatially correlated with radiation (12.19% for surface net solar radiation and 12.14% for surface solar radiation downwards) and least spatially correlated with seasonality precipitation (8.33%) and mean annual temperature (8.19%). The results of the analysis of EVI trends in vegetation and their spatial correlation with bioclimatic and environmental variables can provide a reference for strategies aimed for protecting the vegetation ecology.

Spatiotemporal changes of COVID-19 outbreak in Shanghai

Objective: To clarify the epidemiological characteristics and spatiotemporal clustering dynamics of COVID-19 in Shanghai in 2022. Methods: The COVID-19 data presented on the official websites of Municipal Health Commissions of Shanghai during March 1, 2022 and May 31, 2022 were collected for a spatial autocorrelation analysis by GeoDa software. A logistic growth model was used to fit the epidemic situation and make a comparison with the actual infection situation. Results: Pudong district had the highest number of symptomatic and asymptomatic infectants, accounting for 29.30% and 35.58% of the total infectants. Differences in cumulative attack rates and infection rates among 16 districts (P<0.001) were significant. The rates were significantly higher in Huangpu district than in other districts. The attack rate of COVID-19 from March 1, 2022 to May 31, 2022 had a global spatial positive correlation (P<0.05). Spatial distribution of COVID-19 attack rate was different at different periods. The global autocorrelation coefficient from March 16 to March 29, April 6 to April 12 and May 18 to May 24 had no statistical significance (P>0.05). Our local autocorrelation analysis showed that 22 high-high clustering areas were detected in eight periods.The high-risk hot-spot areas have experienced a "less-more-less" change process. The growth model fitting results were consistent with the actual infection situation. Conclusion: There was a clear spatiotemporal correlation in the distribution of COVID-19 in Shanghai. The comprehensive prevention and control measures of COVID-19 epidemic in Shanghai have effectively prohibited the growth of the epidemic, not only curbing the spatially spread of high-risk epidemic areas, but also reducing the risk of transmission to other cities.

A county-level spatial epidemiological study of hair selenium and Keshan disease.

No spatial analysis of hair selenium and Keshan disease (KD) on a nationwide county-level has been performed. Selenium deficiency is a recognized environmental risk factor for KD. Hair selenium is one of the recognized biomarkers of selenium nutrition. This study aimed to perform a geographically precise and visualized assessment of the achievement of KD prevention and control at the level of selenium nutrition in terms of etiology. A spatial ecological study was conducted. The hair selenium content of the residents was assayed using an atomic fluorescence spectrometer. The spatial analysis was performed using ArcGIS. The median of the hair selenium levels of the 3,028 participants in the 1,174 counties was 0.38 mg/kg, and the content of inhabitants in KD endemic counties was significantly lower than that in KD non-endemic counties (0.34 vs. 0.39 mg/kg, z = -10.03, P < 0.0001). The proportion of Se-deficient and Se-marginal counties in KD endemic counties was significantly higher than that in KD non-endemic counties (59.4 vs. 29.0%, z = -7.45, P < 0.0001). The global autocorrelation analysis was not statistically significant (Moran's I = 0.0005, P = 0.68). Local autocorrelation analysis identified 174 low-low clusters of hair selenium levels, 83 (47.7%) of which are KD endemic counties located in KD endemic provinces of Henan, Gansu, Shaanxi, Inner Mongolia, Jilin, and Heilongjiang. The hair selenium featured a positive correlation with per capita GDP (r s = 0.20, P < 0.0001). The median of the hair selenium levels of inhabitants living in KD endemic counties was significantly lower than that in KD non-endemic counties. All the 83 KD endemic counties with low-low clusters of hair selenium levels should be prioritized in KD precision prevention and control. These findings are geographically precise and visualized evidence of the assessment of the effectiveness of KD prevention and control at the level of selenium nutrition in terms of etiology.

Reconfirmation of the symbiosis on carbon emissions and air pollution: A spatial spillover perspective

Many studies have confirmed the co-emission characteristics of air pollution and carbon emissions. However, studies on the evolution and synergistic factors of the symbiosis of air pollution and carbon emissions over long time scales from a spatial spillover perspective are rare. Here, we identify the spatial evolution and agglomeration characteristics of carbon emissions and air pollution symbiosis by applying local autocorrelation analysis and geographical concentration and by using the dynamic spatial autoregressive model for multiple synergistic factors at city levels during 2006–2019 in China. The results are: (1) The spatial agglomeration and symbiosis of carbon emission and air pollution are similar and show strong spatial locking, as well as path-dependent properties. (2) The spatial imbalance of carbon emission agglomeration and pollution agglomeration gradually improved over time; the concentration centers are all located in Henan province, shifting northward. (3) The symbiosis between both carbon emission agglomeration and pollution agglomeration has significant “spatial and temporal scale effects”, and the economic growth is nonlinear. Additionally, innovation vitality has a negative synergistic driving effect on this relationship. In addition to the results above, rapid industrialization and urbanization are taking place in China. Hence, serious actions against greenhouse gases and air pollutants are imminently needed.

Measuring equality in access to urban parks: A big data analysis from Chengdu.

Spatial equality of parks is a significant issue in environmental justice studies. In cities with high-density development and limited land resources, this study uses a supply-demand adjusted two-step floating catchment area model (2SFCA), paying attention to residents' subjective preferences and psychological accessibility. It assesses equality of access to urban parks from two dimensions: spatial equality and quantitative equality at a fine scale of 100 × 100 m grid resolution. The spatial equality of urban parks in Chengdu is measured under different transportation modes (walking, cycling, and driving) based on multi-source geospatial big data and machine learning approaches. The results show: (1) There were significant differences in the spatial distribution of park accessibility under different modes of transportation. The spatial distribution under walking was significantly influenced by the park itself, while the distribution of rivers significantly influenced the spatial distribution under cycling and driving; (2) Accessibility to urban parks was almost universally equal in terms of driving, relatively equal in terms of cycling, and seriously unequal in terms of walking; (3) Spatial local autocorrelation analysis shows that park accessibility tended to be significantly clustered, with little spatial variation; and (4) The supply and demand of urban parks were relatively equal. The results can help urban planners to formulate effective strategies to alleviate spatial inequality more reasonably and precisely. The applied research methods can further improve the system of scientific evaluation from a new perspective.

Assessment of Sustainable Development of Rural Settlements in Mountainous Areas: A Case Study of the Miaoling Mountains in Southwestern China

As a model based on the harmonious development of society, economy, population, and resources, sustainable development is an essential driving force for a country’s social and economic development. The countryside is an important part of the country, and its sustainable development has been given attention, but existing research lacks a focus on the sustainable development of rural settlements in mountainous areas. In this paper, the rural settlements in the Miaoling Mountains of China are taken as the research object, a geographic detector is used to determine the weight of rural settlement sustainable development factors, a rural settlement sustainable development model is constructed, and a local spatial autocorrelation method is used to quantitatively analyse the level of sustainable development of the rural settlements and the influencing factors related to both the natural environment and socio-economic levels. The results show that (1) 78% of rural settlements in the Miaoling Mountains have a medium to low level of sustainable development and are weak in overall sustainability. (2) The spatial differentiation of the sustainable development levels of rural settlements in the Miaoling Mountains are apparent, and the high sustainable development level settlements are mainly distributed around the urban areas. In contrast, the low sustainable development level settlements are scattered. (3) The level of sustainable development is positively correlated spatially with gross domestic product (GDP), arable land, elevation, normalised difference vegetation index (NDVI), water systems, and roads, and negatively correlated spatially with slope. Of these, GDP, arable land, and elevation have a more substantial influence on the level of sustainability of rural settlements. According to the local autocorrelation analysis, the positively correlated settlement types are mainly clustered in distribution, while the negatively correlated settlement types are sporadic.

The Spatio-Temporal Pattern and Spatial Effect of Installation of Lifts in Old Residential Buildings: Evidence from Hangzhou in China

In recent years, in order to improve the quality of living, China has carried out a series of urban renewal projects, such as adding elevators to old communities. Taking Hangzhou as an example, this paper studies the decision to install elevators in old residential buildings. This study used cold spots and hot spots, local autocorrelation and fishnetting analysis to show the spatial and temporal patterns of lift retrofitting in old communities. Finally, the spatial lag model is used to test whether there is a spatial spillover effect in the behavior of residents installing elevators. The research shows that: (1) Hot spots areas for retrofitting lifts are clustered in the central urban areas of Hangzhou, such as the intersection of Shangcheng District, Xiacheng District, Jianggan District, Gongshu District and Xihu District (scenic area); (2) The trend of retrofitting areas spreading from the center to the periphery; (3) In different communities, the number of elevators added in neighboring communities has a positive effect on the decision of adding elevators in other local communities. Therefore, the neighborhood effect cannot be ignored in the topic of community renovation, in which residents spontaneously participate.

Spatial Epidemiological Analysis of Keshan Disease in China.

Objectives:Few researchers have studied the national prevalence of Keshan disease (KD) in China using spatial epidemiological methods. This study aimed to provide geographically precise and visualized evidence for the strategies for KD prevention and control.Methods:We surveyed and analyzed 237,000 people in 280 out of 328 KD-endemic counties (85.4%) in mainland China using a design of key investigation based on case-searching in 2015–2016. ArcGIS version 9.0 was used for spatial autocorrelation analysis, spatial interpolation analysis and spatial regression analysis.Results:Global autocorrelation analysis showed that global clustering of latent Keshan disease (LKD) prevalence was noted (Moran’s I = 0.22, Z = 7.06, and P < 0.0001), no global clustering of chronic Keshan disease (CKD) prevalence (Moran’s I = 0.03, Z = 1.10, and P = 0.27) was observed. Spatial regression analysis showed that LKD prevalence was negatively correlated with per capita disposable income (t = –4.36, P < 0.0001). Local autocorrelation analysis at the county level effectively identified the cluster areas of LKD prevalence in the provinces of Shaanxi, Gansu, Shanxi, Inner Mongolia, and Jilin. The high-high cluster areas should be given priority for precision prevention and control of Keshan disease.Conclusions:This spatial epidemiological study revealed that LKD prevention and control should be strengthened in areas with high values of clustering. Our findings provided spatially, geographically precise and visualized evidence for prioritizing KD prevention and control.

Functional Tradeoffs and Feature Recognition of Rural Production–Living–Ecological Spaces

Recently, the spatial contradiction in rural construction has intensified. Production–living–ecological (PLE) spaces, as important load-bearing spatial patterns of rural revitalization, have become a research focus of territorial space planning. Because of the lack of studies on the scale and accuracy at the township level in rural PLE spaces, the objective of this study is to quantify the subfunctional and functional areas of PLE spaces, weigh the relationship between PLE functions, and conduct feature identification and strategy formulation of the PLE synergistic functional areas. Combined with multitype measurement methods, the study constructed a township-level PLE space evaluation system composed of 12 subfunctional indicators. Taking Guli Street in Nanjing city as an example, Spearman correlation analysis, spatial local autocorrelation analysis, and cold/hot spot identification were used to analyze the synergies and tradeoffs between PLE functions. On this basis, the evaluation model of the PLE synergies area was constructed. The results showed that the production function showed a fragmented distribution pattern. The proportion of high-intensity living function areas was very small. The ecological function area had good patch integrity. In the PLE functions, obvious synergies exist between any two functions, and the tradeoff between the third one and any of the two functions. The seven types of PLE synergistic potential areas were dominated by the dual-function high synergistic zone (DF-H-Z). The zoning scheme and governance strategy proposed in this paper have important practical value for solving the contradiction of sustainable and coordinated development of township-scale spatial resources.

Study on Spatial Distribution Equilibrium of Elderly Care Facilities in Downtown Shanghai.

With the growing challenge of aging populations around the world, the study of the care services for older adults is an essential initiative to accommodate the particular needs of the disadvantaged communities and promote social equity. Based on open-source data and the geographic information system (GIS), this paper quantifies and visualizes the imbalance in the spatial distribution of elderly care facilities in 14,578 neighborhoods in downtown (seven districts) Shanghai, China. Eight types of elderly care facilities were obtained from Shanghai elderly care service platform, divided into two categories according to their service scale. With the introduction of the improved Gaussian 2-step floating catchment area method, the accessibility of two category facilities was calculated. Through the global autocorrelation analysis, it is found that the accessibility of elderly care facilities has the characteristics of spatial agglomeration. Local autocorrelation analysis indicates the cold and hot spots in the accessibility agglomeration state of the two types of facilities, by which we summarized the characteristics of their spatial heterogeneity. It is found that for Category−I, there is a large range of hot spots in Huangpu District. For Category−II, the hot-spot and cold-spot areas show staggered distribution, and the two categories of hot spot distribution show a negative correlation. We conclude that the two categories are not evenly distributed in the urban area, which will lead to the low efficiency of resource allocation of elderly care facilities and have a negative impact on social fairness. This research offers a systematic method to study urban access to care services for older adults as well as a new perspective on improving social fairness.

Spatial-Temporal Analysis of Factors Influencing the Median Urine Iodine Concentration of 8-10-year-old Children in Xinjiang, China 25 Years after Implementation of the Salt Iodization Policy.

The iodine status of children has improved and stabilized since China implemented salt iodization measures 25years ago, but routine monitoring of iodine cannot reflect regional factors that influence the iodine level in children. Therefore, we conducted a regional spatial-temporal analysis of children's median urinary iodine concentration (MUIC) and searched for possible factors that might affect children's iodine levels by mining monitoring data. We analyzed data from Xinjiang collected as part of the "Iodine Deficiency Disease National Monitoring Program" from 2017 to 2020. The study population consisted of 76,268 children who participated in the study. We used global autocorrelation analysis to determine whether the MUIC of children was spatially clustered, local autocorrelation analysis to identify specific clustering areas, local cold and hot spot analysis to verify the reliability of the local autocorrelation results, and a spatial lag model to identify factors affecting the children's MUIC. The MUIC values were 217.70, 227.00, 230.67, and 230.67µg/L in 2017, 2018, 2019, and 2020, respectively. Global autocorrelation analysis showed that the MUIC of all children in the study was significantly related to region (Z scores all > 1.96, P values all < 0.05) from 2017 to 2020. Partial auto-correlation analysis showed that counties with clusters of high values were mostly concentrated in the southwestern region of Xinjiang, whereas counties with clusters of low values were located in the northern part of Xinjiang. Partial cold spot and hot spot analysis showed the same trend, and there are more overlapping districts and counties in 4years. Three-dimensional trend analysis indicated that children from the western part of Xinjiang had high levels of urinary iodine. According to spatial lag model, urine iodine concentration level is positively correlated with thyroid volume, average salary, and urbanization rate classification. The MUIC of 8-10-year-old children in Xinjiang was spatially clustered and related to geographic region. Our results show that spatial analysis of survey data combined with geographic technology and public health data can accurately identify areas with abnormal iodine concentrations in children. Additionally, understanding the factors that influence iodine levels in the human population is conducive to improving monitoring methods.

A County-Level Spatial Study of Serum Selenoprotein P and Keshan Disease.

BackgroundKeshan disease (KD) is strongly associated with selenium deficiency. Selenoprotein P (SELENOP) is a recognized molecular biomarker of selenoproteins and an important indicator of selenium nutrition. This study was aimed at providing geographically precisely visualized evidence of selenium nutrition at molecular level for assessing KD prevention, control, and elimination on the etiological perspective.MethodsWe used spatial ecological design for this study. The serum SELENOP levels of the residents were measured by ELISA. ArcGIS version 9.0 was used for spatial description, spatial autocorrelation analysis of SELENOP levels and spatial regression with per capita disposable income.ResultsThe mean serum SELENOP levels of the 6,382 residents in 1,688 counties were 4.62 ± 1.82 μg/mL. The mean serum SELENOP levels of the residents living in the townships and rural areas of KD endemic counties were not statistically significantly lower than those of the KD non-endemic counties. The mean serum SELENOP levels were globally clustered (Moran's I = 0.03, z = 6.37, and P < 0.0001), and 99.3% (553/557) of the cold spots, identified by local autocorrelation analysis (Getis-Ord-Gi* analysis), were located in the KD endemic provinces of Shaanxi, Shanxi, Henan, Hebei, Shandong, Inner Mongolia, Gansu, Hubei, Chongqing, Yunnan, and Sichuan. The serum SELENOP level was positively correlated with per capita disposable income (t = 3.52, P = 0.0004).ConclusionsThe results of this study were the geographically precisely visualized evidence of selenium nutrition at molecular level for assessing KD elimination on the etiological perspective. The cold spot counties found by Getis-Ord-Gi* analysis in the KD endemic provinces should be the high priority of KD precision prevention and control.

Study on epidemic trend of hemorrhagic fever with renal syndrome in Zhejiang province, 2005-2020

Objective: To analyze the epidemiological characteristics and spatiotemporal distribution of hemorrhagic fever with renal syndrome (HFRS) in Zhejiang province from 2005 to 2020, and provide scientific information for the precise prevention and control of HFRS. Methods: Data on HFRS cases in Zhejiang province during 2005-2020 were collected from the China National Notifiable Infectious Disease Reporting Information System (NNDS) for a descriptive analysis, and software ArcGIS 10.2 was used for global autocorrelation and local autocorrelation analyses. Spatiotemporal clusters were scanned with SaTScan 9.4.4 and visualized with ArcGIS 10.2. Results: A total of 7 724 HFRS cases were reported in Zhejiang province from 2005 to 2020, including 25 deaths. There were two incidence peaks each year, in late spring and early summer (May-June) and in winter (November-January). The top three areas with high cumulative cases were Ningbo (1 875, 24.27%), Taizhou (1 642, 21.25%), and Shaoxing (1 123, 14.54%). Among the reported cases, with a male to female ratio of 2.73∶1(5 656∶2 068). The majority of HFRS cases were middle-aged and elderly people, with cases aged 41-70 years accounting for 60.95%. Most HFRS cases were farmers, accounting for 69.89% (5 398/7 724). The spatial distribution of HFRS in most years was correlated. SaTScan was used for retrospective spatiotemporal scanning and three clusters were detected: the first type clusters were in 21 counties in eastern Zhejiang province and central Zhejiang province, among which 4 were in Ningbo, Shaoxing and Jinhua, 8 were in Taizhou, and 1 was in Lishui (RR=13.69, LLR=5 522.60, P<0.001); the second type clusters were in Longquan and Qingyuan counties (RR=31.20, LLR=1 232.46, P<0.001); the third types of clusters were in Changxing and Anji counties of Huzhou in northern Zhejiang province (RR=3.42, LLR=23.93, P<0.001). Conclusions: HFRS mainly occurred in middle-aged,elderly and male farmers in Zhejiang province. The incidence was high in late spring, early summer and winter in eastern Zhejiang province. Precise prevention and control measures are needed for populations at high risk before the epidemic season.

Analysis of the trend and spatial clustering of gastric cancer deaths in Shandong Province from 1970 to 2013

Objective: To investigate the distribution characteristics and trends of mortality and spatial aggregation of gastric cancer in Shandong Province from 1970 to 2013. Methods: The mortality data of gastric cancer from 1970 to 1974, 1990 to 1992 and 2004 to 2005 were collected from the first, second and third retrospective sampling survey of causes of death in Shandong Province, respectively. The mortality data of gastric cancer from 2011 to 2013 were collected from the all-cause surveillance data of Shandong Province. The crude mortality rate and age-standardized mortality rate were used to describe the death level of gastric cancer. The age-standardized mortality rate of Shandong Province was calculated based on Segi's world standard population, and the age-standardized mortality rate of counties (cities and districts) was calculated based on the Chinese population in 1964.The factors influencing the difference of gastric cancer mortality in different periods were decomposed by using the method of differential decomposition of mortality, and the contributions of population and non-population factors in different periods were estimated.Using ArcGIS 10.2 software, the death level of gastric cancer in different counties (cities and districts) in Shandong province from 1970 to 1974 and 2011 to 2013 were visualized. DeoDa 1.12 software was used for global and local spatial autocorrelation analysis. Results: The crude death rate and age-standardized death rate of gastric cancer in Shandong province increased firstly and then decreased during 1970-2013, and the crude death rate of gastric cancer increased from 18.33/100 000 in 1970-1974 to 28.51/100 000 in 2011-2013. Segi's age-standardized mortality rate for gastric cancer decreased from 20.94 per 100 000 in 1970-1974 to 18.17 per 100 000 in 2011-2013.From 1990 to 1992, from 2004 to 2005 and from 2011 to 2013, the contribution value of non-population factors to the increase of crude gc mortality was 95.59%, 48.45% and -20.57%, respectively, showing a continuous downward trend. The Moran's I index of crude mortality of gastric cancer in Shandong province from 1970 to 1974 and from 2011 to 2013 were 0.77 and 0.57, respectively, and the Moran's I index of age-normalized mortality was 0.75 and 0.44, respectively. Local autocorrelation analysis showed that there were 31 and 19 high aged-mortality areas of gastric cancer in 1970-1974 and 2011-2013 respectively, and 7 overlapping counties (cities and districts), 6 of which were located in Jiaodong area. Conclusion: The crude mortality and age-standardized mortality of gastric cancer in Shandong province increased first and then decreased from 1970 to 2013, and the distribution of gastric cancer mortality had obvious spatial aggregation and changed with time.

The Spatial Distribution Characteristics of Carbon Emissions at County Level in the Harbin–Changchun Urban Agglomeration

China has clearly put forward the strategic goals of reaching the “Carbon Emission Peak” by 2030, and achieving “Carbon Neutrality” by 2060. To achieve these goals, it is necessary to precisely understand the spatial distribution characteristics of historical carbon emissions in different regions. This paper has selected a representative national-level urban agglomeration in China, the Harbin–Changchun urban agglomeration, to study the temporal and spatial distribution characteristics of carbon emissions in its counties. This paper has constructed global and local Moran’s I indexes for the 103 counties in this urban agglomeration by using the carbon emission values reflected by night light data from 1997 to 2017 to perform global and local autocorrelation analysis on a spatial level. The results show that: (1) the main characteristic of carbon emission clustering in the Harbin–Changchun urban agglomeration is similar clustering; (2) the changes in carbon emissions of the Harbin–Changchun urban agglomeration have a strong correlation with relevant policies. For example, due to the impact of the “Twelfth Five-Year Plan” policies, in 2013, the global county-level Moran’s I index of the carbon emissions in the Harbin–Changchun urban agglomeration decreased by 0.0598; (3) the areas where high carbon emission values cluster together (“High–High Cluster”) and low carbon emission values cluster together (“Low–Low Cluster”) in the Harbin–Changchun urban agglomeration are highly concentrated, and the clusters are closely related to the development level of different regions.

Precipitation and urban expansion caused jointly the spatiotemporal dislocation between supply and demand of water provision service

A clear quantification and spatial mapping between supply and demand of water provision service in relation to climate change and urban expansion can provide some guidance to water resources management. Nevertheless, so far, most researches ignored the dynamic changes and influences of supply-demand coupling correlations. In this study, water yield and water demand were quantified and mapped in the Xiangjiang River Basin (XRB) from 2000 to 2018 by using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and water-demand models, then the spatial distribution characteristics and their matching relationship were identified by using the univariate local autocorrelation analysis and the common logarithm of water supply-demand ratio (WSDR). With that, the contributions of climate and socio-economic factors to the above-mentioned changes were explored by using geographic detector. Results showed that the annual water yield increased by 20.20% in 2000–2015 and decreased by 33.92% in 2015–2018 affected by precipitation and land use changes; Changsha-Zhuzhou- Xiangtan urban agglomeration (CZX) and Southwest of Yongzhou were the high value areas of water yield (>338 m3/hm2). Due to the urban expansion, the water demand increased by 40.50% from 2000 to 2005 and decreased by 36.39% after 2005; From 2000 to 2018, high value areas of water demand (>53566 m3/hm2) mainly appeared in midstream and downstream with high urbanization level, dense population and developed industry. Under the joint action of precipitation (prep) and urban expansion, the overall state of supply and demand in the upper reaches was surplus, and more than 90% of the regions in midstream and downstream were at the middle and high level of supply shortage, especially in Hengyang and Chenzhou. Consequently, the increasing needs of human beings should be emphasized from the overall perspective of the basin, the growth rate of construction land and the necessary green infrastructure should be controlled reasonably and configured for achieving win-win goals of coordinating environmental protection and urban development.

Trade-Off and Projecting Effects of Land Use Change on Ecosystem Services under Different Policies Scenarios: A Case Study in Central China

Predicting the spatio-temporal evolution characteristics and trade-off/synergy relationships of ecosystem service value (ESV) under different policy scenarios is of great significance for realizing regional sustainable development. This study established a framework and used the geographical simulation and optimization systems-future land use simulation (GeoSOS-FLUS) model and bivariate local autocorrelation analysis to stimulate and predict the impact of land use change on the ESV of Anyang City from 1995 to 2025. We also explored the trade-offs and synergy among ecosystem services under three policy scenarios (natural evolution, cultivated land protection, and ecological protection) in 2025. Results show that (1) the land use change in Anyang from 1995 to 2025 was significant, and the degree of land use change under the cultivated land and ecological protection scenarios was more moderate than that under the natural evolution scenario; (2) The total ESV decreased between 1995 and 2015, amounting to losses of 1126 million yuan, and the decline from 2015 to 2025 under the natural evolution scenario was more significant than those under the cultivated land protection and ecological protection scenarios; and (3) an obvious synergy was observed between various ecosystem services in Anyang City under different scenarios in 2025, and the most significant synergy was observed under the natural evolution scenario. In terms of spatial distribution, the agglomeration of “high–high” synergy in the west and “low–low” synergy in the central region was significant. Local areas showed “high–low” and “low–high” trade-off relationships scattered between their built land and woodland or cultivated land. The proposed framework can provide certain scientific support for regulating land use and ecosystem services in rapidly urbanized areas.

Influence of COVID-19 prevention and control measures on the temporal and spatial evolution of epidemic situation

Objective To understand the spatiotemporal distribution and spatial clustering of coronavirus disease 2019 (COVID-19), and to evaluate the impact of comprehensive prevention and control measures on the COVID-19 epidemic. Methods Three periods was divided according to the measures of first level emergency response and the resumption of work and production. Data of diagnosed number in all provinces and municipalities was collected, and the diagnosed number per week in each time period was calculated. The spatial autocorrelation method was used to analyze the temporal and spatial evolution of COVID-19 epidemic. Results In the first stage, a significant positive spatial correlation was observed rounding Hubei province (Morans'I=0.144, Z =2.517, P =0.016). Local spatial autocorrelation analysis showed a high-high clustering between Hubei and its adjacent provinces, and a low-low clustering in these provinces far away from Hubei. After the measures of first level emergency response being taken(the second stage), the COVID-19 epidemic presented a random distribution (Morans'I=-0.017, Z =0.597, P =0.251). A high-low clustering between Hubei and its adjacent provinces, and a low-low clustering in these provinces far away from Hubei was observed. Since the time of work and production was resumed (the third stage), the COVID-19 epidemic remained a random distribution (Morans ' I=-0.055, Z =-0.857, P =0.131). A high-low clustering between Guangdong and Jiangxi, and a low-low clustering in Sichuan was observed. Conclusion The comprehensive prevention and control measures adopted in China have effectively controlled the spread of COVID-19 epidemic throughout the country. At present, the epidemic posed a sporadic state. A closely monitoring and comprehensive prevention and control measures should be maintained to prevent the rebound of COVID-19 epidemic. 摘要：目的 分析新型冠状病毒肺炎(COVID-19)在不同时期的地理空间分布、空间聚集性特征, 评价综合防控措 施对疫情发展的影响。 方法 根据我国各地区采取I级响应措施及复工复产时间将疫情流行分为三个时间段。收集 我国内地各省、直辖市COVID-19动态确诊数据, 计算每个时间段的周确诊病例数;运用空间自相关法对COVID-19确 诊情况进行统计分析。 结果 在第一阶段, 疫情呈现以湖北为中心的典型空间正相关(Morans’I=0.144, Z=2.517, P =0.016);局部聚集表现为湖北与周边省份的髙-髙型和与湖北相距较远省份的低-低型分布。自各地区启动I级响应措 施以后, 疫情在第二阶段呈现随机分布(Morans’I=-0.017, Z =0.597, P =0.251), 局部聚集表现为湖北与周边省份的髙-低 型和与湖北相距较远省份的低-低型分布。自各地区复工复产后, 疫情在第三阶段仍呈现随机分布(Morans’ I=-0.055, Z =-0.857, P =0.131);局部聚集表现为广东与江西的髙-低型及四川地区的低-低型分布。 结论 我国采取的综合防控 措施有效地控制了全国疫情蔓延, 目前疫情总体处于散发流行状态 , 应防止疫情反弹