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Street greening is an important part of urban landscape, and Green view index (GVI) has an important influence on the comfort of street space environment. In this paper, we analyze the GVI of street space based on big data of street view photos and neural network algorithm. By collecting about 25,000 street view photos from Tencent map, we synthesize the panoramic projection photos of equal area. The image segmentation is achieved by training models through DeeplabV3 + network framework, and then the GVI after image recognition is calculated by OpenCV. The spatial distribution of GVI on the street space is analyzed by means of GIS and other means. In this paper, four spatial regression models are applied to analyze the influencing factors of GVI in the context of urbanization development from three perspectives: historical planning, economic and social. A negative correlation between road class and GVI distribution was obtained. When analyzing the influence of different POI distributions on GVI, it was found that the distribution of hospitals and subway stations was significantly correlated with GVI, and the presence of hospitals in neighborhoods would increase the GVI of surrounding streets. The presence of subway stations, on the other hand, decreases the green visibility of the surrounding streets. This study contributes to the development of human-centered planning and design and provides scientific guidance for the construction and renovation of green space in streets by targeting and optimizing the distribution of specific social facilities in the area.

The Green View Index (GVI) is utilized to evaluate urban street value and ecosystem services and to gauge public perceptions of street greening. This study investigates the spatial heterogeneity of the GVI and its influencing factors in Yuzhong District, Chongqing, a mountainous city in China. Deep learning algorithms were employed to calculate the green visibility of street view images, and Geographic Weighted Regression (GWR) and the Optimal Parameter-Based Geodetector (OPGD) were utilized to analyze the relationships between GVI and factors such as road physical attributes, the Normalized Difference Vegetation Index (NDVI), and topographic features. The results indicate that: (1) In Yuzhong District, 58.9% of streets have a GVI within a low to moderate range, suggesting room for improvement. Higher GVI levels are generally associated with elevated Digital Elevation Models (DEM), while slope, aspect, and terrain undulation have relatively minor overall impacts on GVI. (2) The GVI is highest in the western regions and lowest in the eastern regions, with streets along the riversides exhibiting lower GVI levels. (3) GWR analysis reveals that road type and NDVI significantly influence the GVI. Higher DEM values promote increased GVI, whereas high road density suppresses it. (4) The interaction between influencing factors drives the differentiated distribution of GVI within the study area. The interaction effects between Road type, NDVI, and DEM are particularly notable among these.

Background It is true that Chronic obstructive pulmonary disease (COPD) will increase social burden, especially in developing countries. Urban-rural differences in the lagged effects of PM2.5 and PM10 on COPD mortality remain unclear, in Chongqing, China. Methods In this study, a distributed lag non-linear model (DLNMs) was established to describe the urban-rural differences in the lagged effects of PM2.5, PM10 and COPD mortality in Chongqing, using 312,917 deaths between 2015 and 2020. Results According to the DLNMs results, COPD mortality in Chongqing increases with increasing PM2.5 and PM10 concentrations, and the relative risk (RR) of the overall 7-day cumulative effect is higher in rural areas than in urban areas. High values of RR in urban areas occurred at the beginning of exposure (Lag 0 ~ Lag 1). High values of RR in rural areas occur mainly during Lag 1 to Lag 2 and Lag 6 to Lag 7. Conclusion Exposure to PM2.5 and PM10 is associated with an increased risk of COPD mortality in Chongqing, China. COPD mortality in urban areas has a high risk of increase in the initial phase of PM2.5 and PM10 exposure. There is a stronger lagging effect at high concentrations of PM2.5 and PM10 exposure in rural areas, which may further exacerbate inequalities in levels of health and urbanization.

Background Low temperatures are an important risk factor for chronic obstructive pulmonary disease (COPD). However, trends and projections of the global burden of COPD at low temperatures are unclear. Methods Based on data from the 2021 Global Burden of Disease Study (GBD), this study assessed trends in the global and regional burden of death and disability-adjusted life years (DALYs) due to COPD from 1990 to 2021, and identified patterns of change in different regions. A Bayesian Age-Period-cohort (BAPC) model was used to predict the burden of COPD over the next 20 years. Results Although the number of COPD deaths worldwide in 2021 increased from 242,170 in 1990 to 300,849, and the number of DALYs increased from 4,749,734 to 4,981,981, the age-standardized deaths rate decreased from 7.04 to 3.69 per 100,000, and the DALYs rate decreased from 126.69 to 59.22 per 100,000. Up to 2021, men consistently bore a higher burden than women, though their age-standardized deaths rate declined more sharply (54.2% vs. 39.2%). COPD burden increased notably after age 45, with those aged 65 and older contributing most to the total and showing the steepest rise. By SDI level, middle and middle-high SDI regions had the highest burden but saw the fastest declines, while low and low-middle SDI areas carried heavier burdens with slower reductions. High SDI regions maintained low and stable burden levels. BAPC projections suggest a continued but slower decline in COPD mortality linked to low temperature by 2041, with a projected drop of 1.39 per 100,000, less than the 3.35 per 100,000 reduction observed from 1990 to 2021. Conclusion Global age-standardized mortality and DALYs for COPD at risk of low temperatures have declined over the past 30 years, with absolute burden numbers, BAPC predicting a slower rate of decline in the future, and persistent cross-country health inequalities. More precise interventions should be developed to target the resistance to low-temperature risk in older age groups and areas with low SDI.

Based on the PLUS model, research proposed a method to adjust the probability of land use transition to reduce the calculation error of the number of pixels. The refined algorithm is applied to simulate Shenzhen land use situation in 2030 under a progressive scenario using three periods of Shenzhen land use data in 2000, 2010 and 2020. Then, InVEST model was employed to evaluate the distribution situation and future trends of habitat quality in Shenzhen during the study period. Following are the conclusions: 1) The construction land in Shenzhen expanded rapidly and the ecological land gradually shrank during the research period. The proportion of artificial surface area increased by about 45.4% (304.98 km 2 ) within 20 years. 2) By simulating the land use situation of Shenzhen in 2030, the results revealed that the land use change of Shenzhen in the future is mainly concentrated in the central and western regions. 3) The overall average habitat quality of Shenzhen was at a medium level, but the habitat quality showed a continuous degradation trend in each year throughout the study period. Spatially, the habitat quality degradation are mainly concentrated in Shenzhen’s central and western region. 4) Under the natural development scenario, Shenzhen’s habitat quality would experience a sharp decline by 2030. The habitat quality of the conservation area is guaranteed to a certain degree, but the artificial surface expansion outside the area will still affect the habitat quality in the boundary constraint scenario; Only in scenario of ecological priority, the habitat quality of Shenzhen has been restored and improved to a large extent. 5) In order to slow down the degradation trend and improve the regional ecological environment. It is necessary not only to strictly implement various protection boundaries delineated in the context of Territorial Spatial Planning, but also to implement the policy of “Clear waters and green mountains are as good as mountains of gold and silver” in the process of urban development. Government should reasonably control the scale of cities, optimize the ecological compensation mechanism, and implement ecological restoration policies such as returning farmland to forests and returning farmland to grassland.

Background There are regional differences in the effect of green space on mortality of Chronic obstructive pulmonary disease (COPD). We conduct an ecological study, using the administrative divisions of Chongqing townships in China as the basic unit, to investigate the association between COPD mortality and green space based on data of 313,013 COPD deaths in Chongqing from 2012 to 2020. Green space is defined by Fractional vegetation cover (FVC), which is further calculated based on the normalised vegetation index (NDVI) from satellite remote sensing imagery maps. Methods After processing the data, the non-linear relationship between green space and COPD mortality is revealed by generalised additive models; the spatial differences between green space and COPD mortality is described by geographically weighted regression models; and finally, the interpretive power and interaction of each factor on the spatial distribution of COPD mortality is examined by a geographic probe. Results The results show that the FVC local regression coefficients ranged from − 0.0397 to 0.0478, 63.0% of the regions in Chongqing have a positive correlation between green space and COPD mortality while 37.0% of the regions mainly in the northeast and west have a negative correlation. The interpretive power of the FVC factor on the spatial distribution of COPD mortality is 0.08. Conclusions Green space may be a potential risk factor for increased COPD mortality in some regions of Chongqing. This study is the first to reveal the relationship between COPD mortality and green space in Chongqing at the township scale, providing a basis for public health policy formulation in Chongqing.

As an important spatial carrier of Hong Kong’s economic development, construction land provides a critical site for Hong Kong’s economic and social activities. The development of construction land directly affects the sustainable development of the city. Therefore, analysing the spatial and temporal evolution and driving mechanism of construction land in Hong Kong is of great significance in promoting sustainable urban development. This study aimed to evaluate the evolutionary characteristics and driving mechanism of construction land of Hong Kong in the period 1972–2020. Here, we extract construction land data from 1972 based on the historical map of Hong Kong. Then, we apply ArcGIS Pro and Fragstats software to calculate the rate of land expansion, land intensity, change in the centre of gravity, and landscape pattern index of construction land in Hong Kong from 1972–2020. Analysis shows the following: (1) The expansion of construction land in Hong Kong generally showed the characteristics of “rapid at first and then slowing down”, with 2010 as the peak of the 1970–2020 timeframe. (2) The sources of construction land transfer mainly came from cultivated land, sea areas, and forest land, which were mainly distributed in the New Territories. (3) The centre of gravity of construction land in Hong Kong showed the spatial characteristics of “slowly shifting to the northwest” during the study period, indicating that Hong Kong’s polycentric urban structure has been continuously strengthened. (4) The Spiltting index showed a tortuous upward trend, and the index of Mean Euclidean nearest neighbour distance showed a steady downward trend, which indicated that the landscape connectivity of city construction land steadily increased while the degree of fragmentation gradually increased. (5) The driving factors behind the expansion of Hong Kong construction land comes from population, economic, and traffic factors; the support factors come from location and policy factors; the elasticity factors mainly come from reclamation projects; the resistance factors mainly come from the restrictions of environmental protection departments, NGOs, and relevant laws on land reclamation.

Soil is the foundation of agricultural sustainable development. After nearly 40 years of rapid economic development and highly intensive agricultural production, our country’s farmland soil is facing severe soil heavy metal pollution. The situation of heavy metal pollution in farmland soil in China is not optimistic and poses a threat to the safe production of agricultural products and food safety. Therefore, the treatment and restoration of soil heavy metal pollution has received extensive attention. According to the actual situation of soil pollution in our country, the prevention, control and remediation of soil heavy metal pollution has become a major national demand. This article discusses the current status of soil heavy metal pollution control in our country and the main remediation technologies. Aiming at the characteristics and shortcomings of various remediation technologies, it proposes the improvement and development direction of heavy metal contaminated soil remediation technology to provide reference for soil remediation technology research.

As an old community, Luoliu community is representative in Shanghai. Traditional infrastructure is not combined with public space and green space layout, which makes the climate resilience of the old residential area urgently need to be improved. Through questionnaire survey, field measurement, combined with Envi-met to simulate microclimate changes and formulated green space resilience transformation strategies. Microclimate factors such as temperature, humidity, wind speed and wind direction change with the spatial distribution and vegetation structure. First, the walls of buildings are most vulnerable to the shadow of buildings. The microclimate of the building enclosed green space is stable, but its toughness is poor. Parallel green space can restrain the temperature rise to a certain extent, it has strong space toughness. Green enclosure space is also closed, usually covered with green plants. Although it can reduce the impact of solar radiation, overgrown and untrimmed trees will become an obstacle to air ducts. Ventilation should be the priority. Second, the canopy and vertical structure of green plants should be reasonable. Third, the combination layout of the dominant wind direction and the residential complex shall be considered comprehensively to plan the public facilities and sidewalks.