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Carbon emissions from energy consumption caused by industrial production have become an important factor in global warming, and China now has the highest global carbon emissions, with enormous pressure to reduce emissions. The Mid-Yangtze River urban agglomeration (MYRUA), which is an important region for China, also faces the contradiction of balancing environmental protection and economic production. Currently, there is little discussion on low-carbon pollution research in the MYRUA in China. Therefore, this study takes the MYRUA as the research object, uses a slack-based model (SBM) and exploratory spatial data analysis (ESDA) to explore the spatiotemporal evolution of the industrial carbon emission efficiency (ICEE) of the MYRUA in China from 2006 to 2019, and empirically analyses the factors influencing the ICEE based on a spatial econometric model. The results show that (1) in the period 2006–2019, the ICEE in the MYRUA region generally exhibited a "jagged" trend of decreasing, then increasing until finally decreasing again. Spatially, ICEE generally exhibited a dynamic trend of being low throughout, with high-efficiency areas tending to move to the center and low-efficiency areas being scattered. (2) The global Moran's I coefficient for ICEE ranged between 0.002 and 0.213, with the highest Moran's I value and significant spatial correlation occurring in 2006, after which the value gradually decreased. On the local autocorrelation, the ICEE in 2006 exhibited an agglomeration effect and weakened after 2010. (3) In 2019, the level of industrialization (LI) and the level of external openness (LEO) in the MYRUA changed from nonsignificant to significant positive correlations, and the LEO had the largest impact. The energy consumption structure (ECS) was always significantly negatively correlated. The levels of social development (LSD) and environmental regulation (ER) changed from showing a significant positive correlation to showing a nonsignificant correlation. In conclusion, ICEE is affected by interactions of multiple factors. In the future, the ECS of the MYRUA should be continuously optimized and replaced by clean energy. In addition, foreign investment compensates for the lack of production and technology research funds, which can increase investment and promote the digitalization of manufacturing enterprises. • Spatial-temporal pattern of industrial carbon emission efficiency was investigated. • Spatial regression was employed to identify the factors influencing the efficiency of industrial carbon emissions. • The level of external openness has the largest driving factor. • Differential optimization pattern was established due to the differences within urban agglomerations. [ABSTRACT FROM AUTHOR]

• We found evidence of spatial autocorrelation in seat belt non-use in Tennessee. • Seat belt non-use is not produced solely by the internal structural factors. • We identified two major spatial regimes in Tennessee. • Relationship between demographic variables and seat belt non-use varies across regimes. Roadside observations indicate that seat belt use rates are often spatially correlated with nearby areas. However, very few studies have examined the effects of spatial autocorrelation on seat belt use. This study used exploratory spatial data analysis (ESDA) to explore spatial autocorrelation in Tennessee, which has a lower seat belt use than the United States national average. We geocoded home-addresses of vehicle occupants involved in traffic crashes between 2014 and 16 (n = 1,251,901) and projected them to the census tract corresponding to their home address. This projection reveals information about the spatial distribution of seat belt non-use and socioeconomics of the areas surrounding the crash victim's home. The presence of highly spatially correlated observations (i.e., a significant positive Moran's I) suggests that seat belt non-use is not produced solely by the internal structural factors represented in the non-spatial models. ESDA reveals a distinctive regional imprint for spatial autocorrelation, in which Southern-metropolitan areas' (Southern-MPOs) in Tennessee census tracts have higher than average seat belt non-use compared to Non-Southern-MPOs (16% vs. 9%). The spatial error model was suitable for Non-Southern-MPOs, whereas the spatial lag model was more suitable for Southern MPOs. Comparison of the estimated models indicates that in the Non-Southern MPOs, percentage of the White population, percentage of the population with Bachelor's degree, median household income, vehicle ownership, and population density are significant predictors of seat belt non-use. On the other hand, median household income, vehicle ownership, and percentage of population aged between 16 and 42 years old predict seat belt non-use in Southern MPOs. The study results could be used to identify seat belt non-use clusters at the state level and identify seat belt non-use hot zones. Furthermore, this analysis indicates that the relationship between demographic variables and seat belt non-use varies across regimes. Failing to consider the spatial regimes in the analysis would lead to falsely prioritizing groups prone to seat belt non-use. [ABSTRACT FROM AUTHOR]

Global uncertainties brought about by external shocks have surged in recent years, posing huge challenges to achieve the global 2030 Sustainable Development Goals. Urban resilience determines how cities responds, adapts and recovers from external shocks. At present, the theoretical analysis and systematic evaluation of urban resilience in China are still insufficient. Here, we constructed an urban resilience index (URI) system from the perspective of socioeconomic and ecological sustainability to evaluate the urban resilience of prefecture-level cities in China from 2000 to 2020. Then, entropy method and exploratory spatial data analysis (ESDA) were used to investigate the spatiotemporal evolution of urban resilience in China. Finally, the influencing factors that hinder the improvement of urban resilience in China were identified through the obstacle diagnosis model. Results showed that over the past 20 years, China's urban resilience has been greatly improved, as shown in the average URI increased from 0.048 in 2000 to 0.092 in 2010, and further raised to 0.148 in 2020. But the growth rate of China's urban resilience improvement over the past decade (2010−2020) has been slower than in the previous decade (2000−2010). Over the past two decades, China's urban resilience varied across the geographical regions, urban agglomerations and population scales, showing that URI was higher in eastern regions, urban agglomerations and cities with larger population scales than in the mid-west, non-urban agglomerations, and cities with smaller population scales. China's urban resilience has positive spatial auto-correlation, indicating that cities with higher or lower URI tend to have a trend of spatial agglomeration. The dominant factors that hinder the improvement of urban resilience in China have changed over time, manifested as the role of infrastructure gradually weakening, and the role of economic level, industrial structure, and education level gradually strengthening. In view of the heterogeneity of urban resilience in China and the complexity of its influencing factors, differentiated rather than one-size-fits-all countermeasures to improve urban resilience may be more effective. Our findings would provide a beneficial reference for China and other developing countries to optimize urban planning to cope with external shocks and build sustainable and resilient cities. • China's urban resilience has been greatly improved from 2000 to 2020. • China's URI growth rate in the second decade was 1.8% lower than the first. • China's URI varied across the regions, urban agglomerations and population scales. • China's urban resilience has positive spatial auto-correlation. • The dominant factors affecting China's urban resilience have changed over time. [ABSTRACT FROM AUTHOR]

In a regional economy, the central city of a metropolitan area has a radiative effect and an accumulative effect on its surrounding cities. Considering the limitations of traditional data sources (e.g., its subjectivity) and the advantages of nighttime light data, including its objectivity, availability and cyclicity, this paper proposes a likelihood spatial statistical transformation model (LBSSTM) to invert for the gross domestic product (GDP) of the surrounding cities, using time series of Sum of Lights (SOL) data covering the central city and taking advantage of the economic and spatial association between the central city and the surrounding cities within a metropolitan area and the correlation between SOL and GDP. The Wuhan Metropolitan Area is chosen to verify the model using time series analysis and exploratory spatial data analysis (ESDA). The experimental results show the feasibility of the proposed LBSSTM. The prediction accuracy of our model is verified by cross-validation using data from 1998, 2004 and 2011, based on the 3 σ rule. This model can quantitatively express the agglomeration and diffusion effect of the central city and reveal the spatial pattern of this effect. The results of this work are potentially useful in making spatio-temporal economic projections and filling in missing data from some regions, as well as gaining a deeper quantitative and spatio-temporal understanding of the laws underlying regional economic development. [ABSTRACT FROM AUTHOR]

This study assesses the spatial correlation between urban green space and social vulnerability in five Brazilian metropolitan regions (MR), Distrito Federal, Manaus, Porto Alegre, Recife, and São Paulo, containing 20 % of the country's urban population. The spatial correlation method used was exploratory spatial data analysis (ESDA) with the Moran index and local indicator space association (LISA). In the analyzed municipalities, the urban green spaces are not mostly concentrated in areas with better social indices. In four MR, the most representative scenario (in terms of area), was the high social vulnerability accompanied by a high number of urban green spaces. This scenario was observed in peri-urban zones in the analyzed MR. The Distrito Federal (containing the national capital, Brasilia) was the only one case where the concentration of green spaces appeared in the most socially privileged areas. Regarding the most representative scenario, the major problem is not the lack of urban green spaces but the absence of a policy for the implementation of complementary urban facilities in such green spaces. These policies are fundamental for turning urban green spaces into places for social interaction, landscape contemplation, leisure, and culture. Therefore, in the context of land use policies, when green spaces are included among the set of the urban facilities, they become promoters of environmental and spatial justice and can reduce inequality in cities. • Low spatial correlation between Green Spaces and Social Vulnerability Index. • High percentage of green spaces and high social vulnerability had significant correlation. • The Distrito Federal was the only one territory in which green spaces were planned. • Supposition of green spaces favoring higher income people is not confirmed. [ABSTRACT FROM AUTHOR]

The smart, sustainable and inclusive growth adopted by Europe 2020 demands new types of information as it is the land use data as an indicator of the land (a primary production factor) - the building block of any economy. Our method is based the article of Salvati & Carlucci (2014) regarding the Urban Growth and Land Use Structure, we develop an Exploratory Spatial Data Analysis ESDA (Method of Choropleth Maps and LISA, Anselin 2003, 2005) for identification of peri-urban areas in Romania at LAU2 level as lattice data (in Arc Gis, GeoDa) and statistical analysis (in SPSS). The main results of this paper consists in suggesting that the indicator land us changes towards covering with buildings could be used as a synthesis monitoring indicator for the divergent growth effects, allowing the identification of the peri-urban areas, as a result of positive agglomeration process formation based on New Economic Geography theory background. The shapes and locations identified offer a quantitative imagine complementary characterized in a qualitative manner by their higher propensity to be with the highest global competitive performance among the national landscape, in the context of free market main driving force expression. [ABSTRACT FROM AUTHOR]

The ability to detect and non-destructively collect biological samples for DNA processing would benefit the forensic community by preserving the physical integrity of evidentiary items for more thorough evaluations by other forensic disciplines. The Electrostatic Detection Apparatus (ESDA ® ) was systemically evaluated for its ability to non-destructively collect DNA from latent fingerprints deposited on various paper substrates for short tandem repeat (STR) DNA profiling. Fingerprints were deposited on a variety of paper substrates that included resume paper, cotton paper, magazine paper, currency, copy paper, and newspaper. Three DNA collection techniques were performed: ESDA collection, dry swabbing, and substrate cutting. Efficacy of each collection technique was evaluated by the quantity of DNA present in each sample and the percent profile generated by each sample. Both the ESDA and dry swabbing non-destructive sampling techniques outperformed the destructive methodology of substrate cutting. A greater number of full profiles were generated from samples collected with the non-destructive dry swabbing collection technique than were generated from samples collected with the ESDA; however, the ESDA also allowed the user to visualize the area of interest while non-destructively collecting the biological material. The ability to visualize the biological material made sampling straightforward and eliminated the need for numerous, random swabbings/cuttings. Based on these results, the evaluated non-destructive ESDA collection technique has great potential for real-world forensic implementation. [ABSTRACT FROM AUTHOR]

Cluster discovery techniques are a fundamental group of exploratory methods designed to identify areas exhibiting elevated levels of disease, risk, danger, etc. Given the intent of cluster detection, spatial structure plays an important role and must be taken into account appropriately if meaningful clusters are to be found. This paper discusses contiguity and the ways in which it is central to local clusters that may be of interest for planners, managers and policy makers. While spatial contiguity is widely considered an important condition of a cluster, most detection approaches employ a priori artificial structure, leading to disingenuous significance and unintended spatial biases that hinders meaningful discovery and interpretation. The basis for significance is reviewed, and methods for maximizing likelihood are detailed. An approach is presented for addressing spatial contiguity explicitly in cluster detection without the use of arbitrarily shaped scan windows. A case study using crime events within a major urban region is presented, with empirical results used to illustrate capabilities for identifying significant and meaningful clusters. [ABSTRACT FROM AUTHOR]

Abstract: To study the development of spatial and social behavior of preschool children, micro-level spatiotemporal data were collected for the first time in both spatial and social context using a novel behavioral coding system. These unique behavioral data enable us to explore the group-level, dynamic, spatial, and social patterns of preschool children's playing behavior from a hybrid geographic and social perspective. In this research, GIS and exploratory spatial data analysis (ESDA) techniques are employed together to study group-level spatial and social behavior emerging from children's everyday activities and interactions. ESDA with social weights is proposed to explore spatial and social patterns of preschool children's behavior at the same time. The results highlight the utility of this approach for studying the relationships between preschool children's playing behavior and preschool's environmental settings and the relationships between preschool children's personal activities and the formation of their social network space. [Copyright &y& Elsevier]

Abstract: This paper studies the relationship between homicide rate and socioeconomic factors at community area level in Chicago from 1960 to 1995. Most of prior studies of social disorganization theory are based on cross-sectional spatial regression or longitudinal studies. This research integrates space and time in testing social disorganization theory. First, exploratory spatial data analysis (ESDA) is used to examine dynamic spatial patterns of these indicators. This investigation justifies the estimation of homicide rates across community areas through panel-data models that extend to include spatial lag and spatial error autocorrelation. [Copyright &y& Elsevier]

Abstract: Latent fingermarks were deposited onto white office paper samples containing writing or printing from several media (for example, ballpoint pens and laser printers). Fingermarks were deposited both before and after writing/printing. The marks were then treated with appropriate latent fingermark development techniques. Once treated, they were examined with standard techniques applied in document examination (filtered light analysis, electrostatic detection device and Raman spectroscopy) to determine the sequence of application. The results suggested that the sequence of laser printing and latent marks could be determined via electrostatic detection device examination of undeveloped and Ninhydrin developed samples. [Copyright &y& Elsevier]

Abstract: Questioned document casework can occasionally involve the sequencing of impressions. Although some conclusions can be drawn from looking at ESDA traces of intersections there is currently no way of assessing the strength of the observations made in any given case. Using a range of paper and pen types this work examines points of intersection and evaluates the results statistically in order judge the value of the results obtained. [Copyright &y& Elsevier]

Abstract: The Electrostatic Detection Apparatus (ESDA) is a technique most commonly used for the visualisation of indented impressions on questioned documents. This work investigates some of the variables which are known to affect the results of ESDA and some variables which have, as yet, not been addressed. The investigation of variables included: examining the effects of different levels of indentation on different qualities of paper, chronological aging of cascade developer and the effects of repeated use of cascade developer on both the quality of results and the glass beads themselves, the effects of storage of cascade developer in a humidified environment and finally the effects of variation on the image development time. Results indicate that chronological aging of cascade developer does not have a negative effect on the quality of results and a 200g portion of cascade developer will give good quality results for up to 30 traces before the quality will begin to deteriorate. Humidification of the cascade developer appears to have no advantages over storage in a normal environment and, in fact, the toner is lost sooner with humidification. The surface of the glass beads are affected through repeated use of cascade developer and appear to become visually smoother which may lead to a loss of attraction between them and the toner particles. [Copyright &y& Elsevier]

Abstract: The electrostatic process for imaging indentations on documents using the ESDA device is investigated under controlled experimental settings. An in-house modified commercial xerographic developer housing is used to control the uniformity and volume of toner deposition, allowing for reproducible image development. Along with this novel development tool, an electrostatic voltmeter and fixed environmental conditions facilitate an optimization process. Sample documents are preconditioned in a humidity cabinet with microprocessor control, and the significant benefit of humidification above 70% RH on image quality is verified. Improving on the subjective methods of previous studies, image quality analysis is carried out in an objective and reproducible manner using the PIAS-II. For the seven commercial paper types tested, the optimum ESDA operating point is found to be at an electric potential near −400V at the Mylar surface; however, for most paper types, the optimum operating regime is found to be quite broad, spanning relatively small electric potentials between −200 and −550V. At −400V, the film right above an indented area generally carries a voltage which is 30–50V less negative than the non-indented background. In contrast with Seward''s findings [G.H. Seward, Model for electrostatic imaging of forensic evidence via discharge through Mylar–paper path, J. Appl. Phys. 83 (3) (1998) 1450–1456; G.H. Seward, Practical implications of the charge transport model for electrostatic detection apparatus (ESDA), J. Forensic Sci. 44 (4) (1999) 832–836], a period of charge decay before image development is not required when operating in this optimal regime. A brief investigation of the role played by paper-to-paper friction during the indentation process is conducted using our optimized development method. [Copyright &y& Elsevier]

[Display omitted] • The relation between urbanization and water environment in Hanjiang Basin was studied. • Coupling coordination degree model between UAWE of Hanjiang Basin was established. • The positive interaction effect of UAWE is mainly focused on the middle and lower reaches of the Hanjiang River. • Put forward feasible measures to realize the sustainable development of UAWE. The urbanization process of the Hanjiang Basin is speeding up and facing many challenges. It is necessary to take active actions to realize the balance between urbanization development and water environment protection. This paper aims to establish a comprehensive evaluation model of urbanization and water environment (UAWE) and explore the development of UAWE in the Hanjiang Basin in China from 2010 to 2018. In terms of methodology, these evaluation models are combined with the Coupling coordination degree model (CCDM), Exploratory Spatial Data Analysis (ESDA), and Geographically and Temporally Weighted Regression (GTWR) to measure and analyze the coupling degree (CD) and spatiotemporal heterogeneity of UAWE. Our findings include the following: (1) From 2010 to 2018, in all regions of the Hanjiang Basin, urbanization showed a gradual upward trend. Among Them, the comprehensive urbanization index (CUI) of Xiangyang increased by 25.37%. (2) The comprehensive water environment index (CWEI) presents a fluctuating growth, with the rate of increase in Jingmen's reaching 17.44%. (3) There is heterogeneity in time and space between cities in the Hanjiang Basin, and the positive interaction effect of UAWE is mainly focused on the middle and lower reaches of the Hanjiang River. (4) Coupling coordination degree (CCD) in the basin shows an increasing trend, and the areas with high CCD are mainly concentrated in Xiangyang and Xiantao. (5) ESDA shows that the CCD among cities in the basin has spatial correlation and heterogeneity, and the regions with similar CCD tend to be distributed centrally in space. [ABSTRACT FROM AUTHOR]

Coal mining play a fundamental role in promoting economic and social progress. However, intensive mining operations have brought enormous ecological risks, such as landform destruction, vegetation degradation and biodiversity loss. Based on the "source-sink" landscape and ecological risk assessment theories, this study proposes a new methodology to comprehensively analyze the mechanism of ecological risk and makes quantitative evaluation taking Pingshuo coal mine area as an example from 2000 to 2017. The results prove that the "source-sink" landscape theory is more consistent with the nature of ecological process to distinguish the ecological risk in mining area. Within the study period, the main risk source of mining areas is the environmental disturbance brought by mining production with a spreading trend, while the pollution risk caused by residents' life is relatively low but the scope is large. The ecological niche of risk sink (a place where ecological risks disappear) in the study area improved as a whole, the ecological vulnerability and exposure coefficient of risk sink shows a decreasing trend from core mine area to outside, and the trend was not obvious at the end stage, testifying the protective effect of environmental governance. The striking increase areas of comprehensive ecological risk are mostly concentrated in the surroundings of mining production expansion, testifying mining practice has a significant adverse impact on the contiguous natural ecosystem. Any kind of pressure from coal mine operation, residents' production and natural erosion in mining area should not be ignored, and the high risk areas are markedly clustered around the risk sources. [ABSTRACT FROM AUTHOR]

Understanding the spatial-temporal dynamics of grain production and the influencing factors at the county level in China may promote the knowledge of land-use management and local policymaking, which are conducive to food security and the sustainable development of society. This study aims to evaluate China's grain yield (GY) from 2000 to 2014 and investigate the potential driving factors (PDFs) that affect the spatial-temporal dynamics of GY, including land, labor force, capital, and macro-background. Specifically, the locational Gini coefficient and exploratory spatial data analysis (ESDA) were used to characterize the spatial patterns of GY and its correlations with PDFs. Spatial regression models (SRMs) were employed to investigate the spatial dependence of GY on each PDF in 2000, 2005, 2010 and 2014. Results reveal that China's grain production has been on the rise with high-yield regions distributed mainly within the northeastern agricultural regions. Moreover, the proportion of counties in the northeastern agricultural regions with high grain yield has increased, while the number of low-yielding counties has increased in other agricultural regions. This finding highlights the increasing trend of spatial polarization in grain production. The significant bivariate Moran's I (p < 0.05) further revealed a global spatial spillover effect in the spatial correlation of GY and four PDFs. The spatial correlations could be categorized into four types: high GY and high PDFs, high GY and low PDFs, low GY and high PDFs, and low GY and low PDFs. SRMs were capable of quantifying the spatial dependence of GY on various PDFs, thereby revealing that land factors had a substantial effect on the grain production dynamics nationwide. The exploration of the spatial relationships between GY and PDFs provide a reference for formulating scientific and reasonable agricultural policies. • A new insight to understand food security and sustainable agriculture of China. • Spatial polarization and spillover effect existed in grain production in China. • Multiple cropping index was extracted from MODIS NDVI time series. • Exploratory spatial data analysis and spatial regression models were used. • The research was performed at the county level. [ABSTRACT FROM AUTHOR]