Positive Spatial Correlation Research Articles

Excess mortality during the COVID-19 pandemic and its spatial distribution in the state of Pernambuco, Brazil: an ecological study.

To investigate excess mortality during the COVID-19 pandemic and its spatial distribution in Pernambuco, Brazil. This was an ecological, descriptive and analytical study of deaths, by municipality, recorded on the Mortality Information System, in 2020 and 2021. Excess mortality was measured by comparing observed and expected deaths, the latter estimated by calculating standardized mortality ratio (SMR). SMR and respective confidence intervals (95%CI) were calculated. Spatial analysis was performed by calculating the Global and Local Moran Index. Excess mortality was 20.6% and 27.5%, respectively, in 2020 and 2021, with positive spatial correlation (p-value < 0.05). More populous municipalities (2020: SMR = 1.26; 95%CI 1.24;1.27 and 2021: SMR = 1.34; 95%CI 1.32;1.34), more developed municipalities (2020: SMR = 1.43; 95%CI 1.41;1.44 and 2021: SMR = 1.51;95%CI 1.50;1.53) and municipalities in the Sertão region (2020:SMR = 1.31;95%CI 1.30;1.33 and 2021: SMR = 1.44; 95%CI 1.42;1.46) showed greater excess deaths. Excess mortality coincided with peak periods of COVID-19 transmission.

Unfolding the spatial spillover effect of urbanization on composite ecosystem services: A case study in cities of Yellow River Basin

River basins play an important role in national economic development and ecological security and can be well expressed by ecosystem services (ESs) research. Due to rapid population growth and climate change, it has had a significant impact on the ecosystem of the Yellow River Basin (YRB). Although ESs have been assessed in several studies, few studies have used a composite ecosystem service index (CESI) in their assessment. Thus, here, based on the InVEST model, bivariate spatial autocorrelation, and spatial econometric model, we studied the composite ESs in the YRB, with an aim to build a CESI for evaluating the overall ESs in the YRB. We found that the CESI of the YRB from 1990 year–2020 year had an obvious spatiotemporal distribution law at the city level and grid scale, showing a high distribution characteristic in the southeast. The spatial trend also showed a significant difference in regional distribution. There was a positive spatial correlation between the CESI and urbanization indicators that reflected the level of urbanization, and the distribution of the aggregation type among the three was similar. Furthermore, population density had a strong positive spillover effect on the CESI, whereas economic density and land development had a negative spillover effect. Therefore, the YRB should pay attention to transforming the extensive development model and paying attention to the negative spillover effect of economic density when laying out industrial structures. Additionally, it is necessary to control the expansion of built-up land and improve land use efficiency, thereby reducing the negative spillover effect of land development. This study’s findings can serve as reference for policy formulation in major river basins worldwide.

Extended correlation functions for spatial analysis of multiplex imaging data.

Imaging platforms for generating highly multiplexed histological images are being continually developed and improved. Significant improvements have also been made in the accuracy of methods for automated cell segmentation and classification. However, less attention has focused on the quantification and analysis of the resulting point clouds, which describe the spatial coordinates of individual cells. We focus here on a particular spatial statistical method, the cross-pair correlation function (cross-PCF), which can identify positive and negative spatial correlation between cells across a range of length scales. However, limitations of the cross-PCF hinder its widespread application to multiplexed histology. For example, it can only consider relations between pairs of cells, and cells must be classified using discrete categorical labels (rather than labeling continuous labels such as stain intensity). In this paper, we present three extensions to the cross-PCF which address these limitations and permit more detailed analysis of multiplex images: topographical correlation maps can visualize local clustering and exclusion between cells; neighbourhood correlation functions can identify colocalization of two or more cell types; and weighted-PCFs describe spatial correlation between points with continuous (rather than discrete) labels. We apply the extended PCFs to synthetic and biological datasets in order to demonstrate the insight that they can generate.

Spatial and temporal dynamics of urban heat environment at the township scale: A case study in Jinan city, China.

The prolonged dependence on industrial development has accentuated the cumulative effects of pollutants. Simultaneously, influenced by land construction activities and green space depletion, the Urban Heat Island (UHI) effect in cities has intensified year by year, jeopardizing the foundation of sustainable urban development. Prudent urban spatial planning holds the potential to robustly ameliorate the persistent deterioration of the UHI phenomenon. This study selects Jinan City as a case study and employs spatial autocorrelation and spatial regression algorithms to explore the spatiotemporal evolution of urban-rural patterns at the township scale. The aim is to identify key factors driving the spatiotemporal differentiation of Land Surface Temperature (LST) from 2013 to 2022. The research reveals a trend of initially rising and subsequently falling LST in various townships, with low-temperature concentration areas in the southern mountainous region and the northern plain area. The "West-Central-East" main urban axis and the southeast Laiwu District exhibit high-temperature zones. Significant influences on LST are attributed to pollution levels, topographical factors, urbanization levels, and urban greenness. The global Moran's Index for LST exceeds 0.7, indicating a strong positive spatial correlation. Cluster analysis results indicate High-High (HH) clustering in the central Shizhong District and Low-Low (LL) clustering in the northern Shanghe County. Multiscale Geographically Weighted Regression (MGWR) outperforms Geographically Weighted Regression (GWR) and Ordinary Linear Regression (OLR), providing a more accurate reflection of the regression relationships between variables. By investigating the spatiotemporal evolution of LST and its driving factors at the township scale, this study contributes insights for future urban planning and sustainable development.

Assessment of optimal seasonal selection for RSEI construction: a case study of ecological environment quality assessment in the Beijing-Tianjin-Hebei region from 2001 to 2020

Timely and objective assessment of the optimal season for the construction of remote sensing ecological index (RSEI) is of great significance for accurate and effective assessment of ecological environment quality. We manipulated RSEI in to monitor seasonal variations in ecological environment quality (EEQ) in the Beijing-Tianjin-Hebei (JJJ) region from 2001 to 2020. First, we evaluated image quality across all four seasons and filled in missing observations through liner interpolation. Second, Seasonal RSEI was constructed using MODIS and compared across different years. Third, temporal and spatial variations within the same seasons in EEQ. Additionally, Moran’s I was utilized to evaluate spatial autocorrelation of EEQ, and the stability of the correlation between RSEI and four indicators seasonal indicators was compared. The results showed that: 1) the PC1 component concentrates most of the characteristics of the four indicators, especially in summer (over 71%); 2) the Moran’ I in the summer of 2001, 2006, 2011, 2016 and 2020 are 0.909, 0.898, 0.917, 0.921 and 0.892, respectively, which indicated that the EEQ has a strong positive spatial correlation. 3) the correlation between the four indicators and summer RSEI showed high correlation in different years, and the standard deviation of the correlation between the four indicators and RSEI fluctuated most slightly in summer, which the std of NDVI, WET, LST and, NDBSI were 0.005, 0.052, 0.026 and 0.017, respectively. This study theoretically demonstrates that summer is the optimal season for constructing RSEI, filling the research gap in previous studies regarding the rationale for selecting images from periods of vigorous vegetation growth for RSEI construction, which can provide a reference for selecting the optimum season for the ecological quality monitoring of urban in the future.

Identifying driving factors of ecosystem service trade-offs in mountainous region of southwestern China across geomorphic and climatic types

Mountainous areas have obvious spatial differences in topography and climate, which could further cause heterogeneity of ecosystem service (ES) trade-offs. The characteristics of ES trade-offs had been extensively studied, however, the driving mechanism of which is still unclear in mountainous areas. Focusing on the Hengduan Mountain region (HDM) in southwest China, this study quantified the spatial aggregation effects of ESs and their trade-offs using a spatial autocorrelation analysis, and identified the dominant drives for each ES trade-off across various geomorphological and climatic zones. In terms of the spatial distribution, ESs and their trade-offs have a significant positive spatial correlation, which was mainly manifested as high-high (H-H) and low-low (L-L) value aggregations. The dominant factors for some trade-offs differed across geomorphological and climatic zones. Land use type was the main factor in flat areas for paired water yield (WY) with soil conservation (SC) and carbon storage (C). In plateau (PLA) and mid-subtropical (MS) climate zones, the main factors were land use type and soil types for paired WY and C, respectively. Temperature had a higher contribution for paired C and SC in flat and plateau areas. For the other trade-offs, the dominant factor was constant for different zones. The normalized difference vegetation index (NDVI) and soil type were the main factors for paired net primary productivity (NPP) with SC and C respectively. For trade-offs between habitat quality (HQ) and other ESs, and those among multiple ESs, land use type was the dominant drive, and the influence decreased with the increase of topographic relief. Therefore, attention should be paid to the ecological effects of land use change in future urban planning and development. The study will help guide zoning regional spatial planning and achieve mountain sustainable development.

Correlations between soil properties and spectral index (healthy vegetation) in soybean crops

Precision agricultural technologies, such as the use of spatial variability of soil properties, have been extensively studied for soybean cultivation. The objective of this study was to analyze the spatial variability of soil properties cultivated with soybean and to correlate the healthy vegetation (HV) spectral index with the bands B8A (classifying vegetation - 865 nm), B11 (measuring the moisture content of soil and vegetation - 1610 nm), B02 blue (useful for soil and vegetation discrimination - 490 nm). A sampling grid was installed for data collection in an area of 2,126.02 ha, with 270 regular points and 98 random points, totaling 368 points. For the soil, the contents of P (resin), K+, Ca2+, Mg2+, H+, Al3+, pH values, sum of bases (SB), cation exchange capacity (CEC), and base saturation were determined at a depth of 0.0 to 0.20 m. Most of the soil properties had exponential and spherical dependence. Clay percentages and Ca, Mg, and P contents had positive spatial correlation with the healthy vegetation spectral index (HV) while no spatial correlation was observed for pH, B, K, silt, sand, S, H+Al, Al, SB, and CEC. The sensor image used in this study in relation to HV showed good application for observing the spatial variability of the soil properties and soybean yield.

Spatio-temporal evolutionary analysis of surface ecological quality in Pingshuo open-cast mine area, China.

The open-pit mining area is highly affected by human activities, which aggravate soil erosion and disturb surface ecology, bringing many problems and challenges to its environmental management and restoration, which has received widespread attention. The establishment of an objective, timely and quantitative remote sensing monitoring, and evaluation system for the spatio-temporal evolution of the surface ecological environment in the open-pit mining area is of great significance for its environmental protection, management decisions, and sustainable social development. Based on the Google Earth Engine (GEE) platform, this paper uses Landsat images to construct and calculate the remote sensing ecological index (RSEI) of the Pingshuo open-cast mine area (POMA) from 1990 to 2020 and monitor and evaluate its surface ecological environment. Combined with the Theil-Sen median, Mann-Kendall test, and Hurst index, the spatio-temporal process was analyzed. The results showed that the ecological environmental quality of the mining area first decreased and then increased from 1990 to 2020. 1990-2000 was a period of serious ecological degradation, followed by improvement. The overall improvement area reached 87.03%, and the degradation was concentrated in the coal mining area. Between 1990 and 2020, the Hurst index of the mining area was 0.452, indicating that the region has a fragile ecological environment and has difficult maintaining its stability. The global Moran's I mean value of the RSEI of the study area is 0.92, which combined with Moran's scatter plot to indicate that there is a strong positive spatial correlation rather than a random distribution of its ecological environment. During the study period, the impact on the climate of the ecological environmental change of POMA was weak, and human factors such as coal mining, land reclamation, and social construction were the main driving forces for the change in ecological quality. The results of this study reveal the changing trend of surface ecology in the mining area over the past 30 years, which is helpful for understanding its impact mechanism on ecological quality and provides support for the management of the region.

Study on the Spatial Correlation Characteristics of Residential Land Prices in Counties of the Urban Agglomeration in the Middle Reaches of the Yangtze River and Their Influencing Factors

The role of residential land price in regulating local economic development and optimizing urban land spatial layout is becoming more and more prominent. This paper takes the residential land price of 229 counties (districts, cities) of urban agglomeration in the middle reaches of the Yangtze River in 2017 as the research object, and establishes a theoretical model of the influencing factors of county residential land price based on equilibrium price and regional economic theory; and uses methods of spatial autocorrelation analysis and spatial lag model to explore the spatial distribution characteristics and influencing factors of residential land price in the research area and the influencing factors. The research results indicate that: (1) There are significant overall differences in residential land price among different counties within the urban agglomeration in the middle reaches of the Yangtze River, and the overall distribution of residential land price shows a "pyramid" pattern from low to high. (2) The spatial distribution pattern of residential land price in counties within urban agglomerations is greatly influenced by the location conditions and the administrative level of higher-level cities. The residential land price shows an inverted "U" distribution in the east-west direction, with the eastern part being higher than the western part as a whole; There is a gradual downward trend from north to south in the north-south direction. (3) The Global Moran’s I of residential land prices in the research area is 0. 603, with a significant spatial positive correlation and agglomeration phenomenon. and the obvious local spatial agglomeration characteristics. (4) There is a significant positive spillover effect between county-level residential land price in the urban agglomeration of the middle reaches of the Yangtze River. The residential land price in the study area is strongly influenced by both land supply and demand factors, policy systems, and government regulatory capabilities. The relevant conclusions can provide reference for urban agglomeration to optimize urban resource allocation through land price regulation, narrow regional development gaps, and promote the integrated development of the region.

Epidemiological characteristics and spatio-temporal aggregation of severe fever with thrombocytopenia syndrome in Jinan City, China, 2018-2022.

Severe fever with thrombocytopenia syndrome (SFTS) has become a significant public health issue in Jinan City. However, the analysis of epidemiological characteristics and spatio-temporal clustering of SFTS in Jinan has not been studied yet. SFTS data from 2018-2022 in Jinan City were obtained from the China Information System for Disease Control and Prevention. Global spatial autocorrelation and local spatial autocorrelation analyses were performed using ArcGIS 10.2 software, and spatiotemporal hotspot area detection was carried out using SatScan 9.6 software. Between 2018 and 2022, 680 SFTS cases were reported in Jinan City, resulting in 53 deaths and an average case fatality rate of 7.8%. 99.0% of cases occurred between April and October, 91.9% individuals were over 50 years old, and 87.79% were primarily farmers. A positive spatial correlation of SFTS in Jinan was observed (Moran's I value between 0.135-0.197, P<0.001), indicating spatial aggregation, primarily in Licheng, Zhangqiu, Laiwu, and Gangcheng districts in southeastern Jinan. Spatiotemporal scanning detected one class I and two class II aggregation areas, with the class I aggregation area (RR = 5.66, LLR = 192.547, P<0.001) locating in southeastern Jinan City, comprising 31 towns/streets, and an aggregation time from 13 May 2020 to 13 October 2022. Spatial and temporal aggregation of SFTS is evident in Jinan. Based on the spatial and temporal distribution and epidemiological characteristics, prevention and control measures such as public education, monitoring, and training should target key populations in high-incidence epidemic areas.

The spatiotemporal distribution and prognostic factors of Japanese encephalitis in Shanxi Province, China, 2005-2022.

Japanese encephalitis (JE) is a naturally occurring localized disease caused by the Japanese encephalitis virus, which is spread by the Culex tritaeniorhynchus. China has a high rate of JE. Shanxi, located in North China, has a high prevalence of adult JE. Adult JE has more severe complications, mortality, and a higher disease burden, making it a public health issue. This retrospective study examined the dynamic epidemic changes, high-risk areas of JE, and clinical characteristics and prognostic factors of adult JE in Shanxi Province. The findings revealed that July to September was the primary epidemic season of JE and that JE cases were mainly in individuals over the age of 40. The incidence of JE from 2005 to 2022 demonstrated a positive spatial correlation with significant clustering characteristics, with high-incidence clusters in the south and southeast. Multivariate logistic regression analysis revealed that higher cerebrospinal fluid pressure, higher white blood cell counts, higher neutrophil percentage, deep coma, and lower albumin were independent factors for poor prognosis of adult JE. The developed risk prediction model holds great promise in early prognosis assessment of patients, providing a basis for clinical decision-making and early clinical intervention.

Investigating the spatio-temporal interactive relationship between land use structure and ecosystem services in urbanizing China

The negative impacts of urbanization-triggered land use changes on ecosystem services have attracted worldwide attention. However, the interactive relationships between land use structure and ecosystem services remain unclear, which is not conducive to sustainable regional ecological management. This study employed the information entropy and ecosystem services value assessment method to measure the land use structure and ecosystem services at the county level in China between 2000 and 2020, respectively. Then the spatial correlation analysis and decoupling model were used to explore the spatial and temporal interactive relationships between them, respectively. The results indicated that the average information entropy of land use structure (IELUS) and total ecosystem services value (ESV) in China both showed a continuous growth trend during the study period. ESV and IELUS were found to have a significant positive spatial correlation and were dominated by low-value agglomeration. The dominant types of the interactive relationship between IELUS and ESV were strong decoupling and expansion negative decoupling, and the number of counties with expansion negative decoupling decreased rapidly during the study period. These results suggest that differentiated land-use structure management policies ought to be adopted to protect regional ecosystem services.

Spatio-temporal linkage variations between NDVI and tree rings on the leeward side of the northern Patagonian Andes

The Normalized Difference Vegetation Index (NDVI) and tree rings provide different approaches that allow evaluating the productivity of ecosystems. Following this premise, we evaluated the relationship between NDVI and tree-ring widths of Austrocedrus chilensis forests at sectors of the Argentinian northwestern foothills of the Patagonian Andes. To proceed with this study, wood core samples were taken from 153 trees at 6 sites located at different latitudes and along a strong west-east precipitation gradient. The NDVI presented a significant and positive spatial correlation with precipitation, the Standardized Precipitation-Evapotranspiration Index (SPEI-3), soil moisture, and a negative correlation with air temperature at large geographical coverages. Stand location in the latitudinal and meridian coordinates showed a species-specific effect, with greater sensitivity to NDVI in sites located at higher latitudes and under drier conditions. We found stronger associations between stem biomass (tree rings) and canopy biomass (NDVI) in drier sites, assuming a closer link to stressful water conditions. This behavior was accentuated since 1988, which coincides with the increase in air temperature as a result of regional warming processes. These results suggest that site environmental conditions influence how NDVI and ring width are linked, showing the complex dynamics between climate and growth. The results indicate that ring widths of A. chilensis trees have the potential to assess current NDVI variations in the study area, allowing reconstructions of past productivity and potential predictive models of future changes.

Regional Heterogeneity Analysis of Residential Electricity Consumption in Chinese Cities: Based on Spatial Measurement Models

The share of electricity consumption by urban and rural residents in China’s overall electricity consumption is very close to that of the tertiary sector, which has become an important driver of China’s electricity consumption growth. At the same time, due to the mismatch between China’s regional resource endowments and the level of regional development, the regional supply and demand situation for electricity varies. Therefore, it is urgent to clarify the regional differences in residential electricity consumption and the factors affecting it, and accordingly adopt targeted and feasible measures to regulate residential electricity consumption. This article includes data from 285 Chinese prefecture-level cities from 2006 to 2019, and adopts a “three lines” method of region-partitioning (Qinling–Huaihe line, Huhuanyong line, and Shanhaiguan line) to divide four regions. We used spatial econometric models to examine residential electricity consumption and its influencing factors in China from the standpoint of regional heterogeneity. The results show that there is significant regional heterogeneity in residential electricity consumption in China, and the difference between the north of the Shanhaiguan line and other areas is significant. Moreover, there is a positive spatial correlation in the per capita domestic electricity consumption of urban residents, and each influencing factor has obvious regional heterogeneity, among which household appliances are the significant influencing factor. Based on the regional heterogeneity of residential electricity consumption, management measures should be formulated according to local conditions, and the supply of electricity should be ensured by strengthening multidimensional initiatives.

Analysis and Prediction of Spatial and Temporal Evolution of Ecosystem Service Value on the Northern Slopes of the Kunlun Mountains Based on Land Use

The ecological environment in the mountainous areas of southern Xinjiang is very sensitive and fragile, and identifying the ecological asset retention within the mountainous areas is a top priority at the current stage in the context of comprehensive environmental management in arid zones. This study examines the conversion and ecosystem service values between different land types within the mountainous areas based on a time series of land-use data from 1990 to 2020, and the results show that: (1) The value of ecosystem services on the northern slopes of the Kunlun Mountains shows an overall increasing trend. It increased from CNY 308.645 billion in 1990 to CNY 326.550 billion in 2020. Among them, the value of ecosystem services increased significantly between 2000 and 2010, with an increase of CNY 39.857 billion. Regulatory services accounted for more than 66% of the value of each ecosystem service. (2) Land use on the northern slopes of the Kunlun Mountains has changed significantly since 1990. The areas of cropland, forest land, grassland, watershed, and construction land have all shown an upward trend, with the greatest increase in construction land. The area of unutilized land, on the other hand, has slightly decreased. (3) The value of ecosystem services within the northern slopes of the Kunlun Mountains was spatially high in the south, low in the north, and higher in the west than in the east. The study also found a significant positive spatial correlation between ecosystem service values. In the spatial distribution, the increasing areas were mainly distributed in the southeast, and the decreasing areas were in the north. Changes in land types are expected to include an increase in the area of grassland and woodland, a decrease in unutilized land and cropland, and an overall improvement in the ecological environment of the northern slopes of the Kunlun Mountains in the next decade. This study also provides lessons and references for sustainable development and ecological protection in ecologically fragile regions.

Landscape Fragmentation and Spatial Autocorrelation of a Typical Watershed in the Wenchuan Earthquake-Affected Area—A Case Study in the Longxi River Basin

The 2008 8.0 Ms Wenchuan earthquake caused serious ecological degradation in the northwest of China’s Sichuan Province. Elucidating landscape fragmentation and spatial pattern of post-earthquake landscape is of great interest in order to improve ecological restoration and predict the spatial distribution of damaged ecosystems in earthquake-affected areas. We used four real-time remote sensing images to analyze the landscape pattern characteristics and spatial autocorrelation of the Longxi River Basin before and after the Wenchuan earthquake during the period from 2005 to 2015. In the study period, the degree of landscape fragmentation increased 1 year after the earthquake in 2009 but decreased in 2011 and 2015. The spatial distribution of forest, farmland, and shrub-grassland had significantly positive spatial correlation and the characteristics of spatial aggregation from 2005 to 2015. Construction land had no significant spatial correlation before the earthquake in 2005, but significantly positive spatial correlation after the earthquake, while traffic land had no significant spatial correlation across the study period. Unlike the other landscape types, geological disasters changed from a significantly negative spatial correlation before the earthquake to a significantly positive spatial correlation after the earthquake. However, the positive autocorrelation of all landscape types decreased with the increase of space distance, but in different distance-decay rates. The High-high spatial aggregation areas of geological disasters and construction land clustered gradually upstream of the basin and distributed in Longchi town, respectively; those of farmland distributed in the southeast of the basin increased in 2009 but then decreased, while those of forests had the opposite pattern as the dominant landscape type after the earthquake. Our results elucidated the spatial structure and distribution features of the Longxi River Basin to give a theoretical foundation for assessing the effects of ecological restoration and reconstruction management in earthquake-affected areas.

Driving factors to agriculture total factor productivity and its contribution to just energy transition

This study explores the intricate relationship between agricultural productivity and the pursuit of a just energy transition in China. As the world's largest emitter of greenhouse gases and a nation grappling with environmental degradation and socio-economic disparities, China faces the imperative to transition toward a more sustainable and equitable energy system. This paper investigates the role of agriculture in this transition, recognizing its pivotal position as a significant emitter of greenhouse gases while also being vulnerable to the impacts of climate change. By examining the potential synergies and conflicts between agricultural productivity enhancement and the goals of reducing emissions and promoting social justice, this study aims to shed light on strategies that can effectively align agricultural development with the objectives of a just energy transition. The result indicates substantial internal disparities and strong agglomeration effects (referring to areas with similar agricultural total factor productivity) within China's agricultural total factor productivity distribution. Over the past 17 years (2005–2021), the average agricultural productivity has shown a commendable upward trend, marking a 2.8% growth rate. This increase signifies ongoing efforts and advancements in the agricultural sector, leading to improved productivity levels. Our results also show a significant positive spatial correlation in agricultural total factor productivity, suggesting a tendency for spatial agglomeration. The years 2005 and 2021 stand out as periods marked by significant adverse effects resulting from the interplay of diverse factors on agricultural productivity. By integrating findings from various sectors, this study provides insights into the complex interplay between agriculture and energy transition, emphasizing the need for integrated, holistic approaches that prioritize sustainability, fairness, and resilience in China's pursuit of a just energy future.

Spatial-temporal characteristics and influencing factors of wildfire occurrence and correlation with WUI presence in Beijing-Tianjin-Hebei region, China

Wildfires not only directly affect ecology but also have a huge impact on social and economic stability. Enhancing the understanding of wildfire influences can guide the design of targeted strategies in mitigation plans and adaptation strategies. Here, we explored the spatial-temporal characteristics of wildfires in the Beijing-Tianjin-Hebei region of China and the mechanisms of the effect of potential influencing factors on wildfire occurrence based on 2014–2020 wildfire data. The results show that wildfires mainly occur in spring and winter and decrease yearly. Among all the considered influencing factors, the occurrence of wildfire is most significantly affected by the temperature vegetation dry index (TVDI) and is also greatly affected by population and economy. Through interaction detection, it was found that the normalized difference vegetation index (NDVI) greatly interfered with wildfires. The high occurrence risk of wildfire was distributed in a blocky pattern in the middle and east of the study area. In addition, we also found a positive spatial correlation between the high wildland-urban interface (WUI) presence and high wildfire occurrence. These findings have improved our understanding of the impact of multiple influencing factors on wildfires and are supposed to facilitate the development of wildfire management strategies.

Spatiotemporal Dynamics of the Suitability for Ecological Livability of Green Spaces in the Central Yunnan Urban Agglomeration

Green spaces are an essential aspect of building an eco-livable city and play an important role in building for eco-livability in the central Yunnan urban agglomeration. However, there are relatively few studies evaluating the eco-livability of green spaces. The establishment of a green-space eco-livability assessment system may help researchers to analyze the eco-livability of urban green spaces more effectively. To address this research gap, we constructed an ecological livability-evaluation index system for green spaces that incorporates three determinants—economic development, social life, and the ecological environment—using the green spaces of the urban agglomeration in central Yunnan as a case study. We used the entropy method to calculate the suitability for ecological livability of the green spaces in each district and county in the central Yunnan urban agglomeration for 2010, 2015 and 2020. We used the spatial autocorrelation analysis function of ArcGIS 10.8 software to explore the spatial clustering characteristics of the suitability for ecological livability of green spaces in the central Yunnan urban agglomeration. The results showed that, from 2010 to 2020, the suitability for ecological livability of green spaces of the 49 districts and counties in the central Yunnan urban agglomeration increased in some districts and decreased in others. The spatial characteristics were high in the central districts and counties and low in the peripheral districts and counties. The spatial characteristics of the suitability of the target layers for economic development and ecological-environment target were consistent with the overall suitability. Through a spatial autocorrelation analysis, we observed that the suitability of green spaces for ecological livability had a positive spatial correlation and demonstrated significant spatial clustering. In this study, we propose recommendations to improve the suitability for ecological livability of green spaces from two dimensions of government policy and urban development, using a combination of the three target layers. The results of the study provide a reference for decision-making in the construction of eco-livable cities in the central Yunnan urban agglomeration.

Analysis of the spatial effect of clean energy development on green economic growth: evidence from China.

Clean energy development has played a pivotal role in economic transformation. Based on the panel data of 30 provinces in China from 2006 to 2021, the spatial Dubin model was used to empirically investigate the impact of clean energy development on green economic growth. Furthermore, this research selected industrial structure optimization as the mediating variable to analyze the mediating effect between clean energy development and green economic growth. The results are as follows. Firstly, there is a positive spatial correlation for green economic development, in which the level of green economic development in a region can be influenced by neighboring regions. Secondly, there is a significant positive relationship between clean energy development and green economic growth, in which the clean energy development has a positive impact on green economic growth. Thirdly, the mediating effect analysis demonstrates that the clean energy development can influence green economic growth through industrial structure optimization. Based on the findings in this paper, several suggestions are proposed. China should formulate a unified national strategy for green economy by coordinating and balancing regional differences, develop the clean energy industry to promote green economic growth, and pay attention to the intermediary effect of industrial structure to promote green economic growth.