Factors affecting land dissection density in geomorphological regions of China

Land dissection density(LDD)provides morphological evidence regarding prior intense soil erosion and quantifies the distribution of land dissections.A comprehensive understanding of the potential factors influencing the spatial pattern and value of the LDD is vital in geological disasters,soil erosion,and other related domains.Land dissection phenomena in China affects large areas with different morphological,pedological,and climatic characteristics.Prior studies have focused on the potential factors influencing the LDD at a watershed scale.However,these results are insufficient to reflect the status quo of dissection development and its primary influencing factors on a national scale.LDD’s spatial patterns and the dominant factors at a regional scale in millions of square kilometers remain to be ascertained.This study used the geomorphon-based method and the geographical detector model to quantify the spatial pattern of LDD over China and identify the dominant factors affecting this pattern in China’s six first-order geomorphological regions(GR1~GR6).The results yield the following findings:(1)LDD in China ranges from 0~4.55 km/km^(2),which is larger in central and eastern regions than in other regions of China;(2)dominant factors and their dominant risk subcategories vary with each geomorphological region’s primary internal and external forces;(3)the influence of natural factors is more significant on the large regional scale in millions of square kilometers compared to anthropogenic factors;relief degree of land surface(RDLS)is dominant in GR1,GR2,and GR5;the slope is dominant in GR6,soil type is dominant in GR3 and GR4,and lithology plays a critical role in the dominant interactions of GR3,GR4,and GR6;(4)the interactions between factors on LDD’s spatial pattern have a more significant effect than individual factors.

Driving forces and their interactions of soil erosion in soil and water conservation regionalization at the county scale with a high cultivation rate

Soil erosion control based on county scale Soil and Water Conservation Regionalization(SWCR)is an essential component of China's ecological civilization construction.In SWCR,the quantitative analysis of the spatial heterogeneity and driving factors of soil erosion among different regions is still lacking.It is of great significance for soil erosion control to deeply examine the factors contributing to soil erosion(natural,land use,and socioeconomic factors)and their interaction at the county and regional levels.This study focused on a highly cultivated area,Hechuan District of Chongqing in the Sichuan Basin.The district(with 30 townships)was divided into four soil and water conservation regions(Ⅰ-Ⅳ)using principal component and hierarchical cluster analysis.The driving factors of soil erosion were identified using the geographical detector model.The results showed thatⅰ)the high cultivation rate was a prominent factor of soil erosion,and the sloping farmland accounted for 78.4%of the soil erosion in the study area;ⅱ)land use factors demonstrated the highest explanatory power in soil erosion,and the average interaction of land use factors explained 60.1%of soil erosion in the study area;ⅲ)the interaction between natural factors,socioeconomic factors,and land use factors greatly contributes to regional soil erosion through nonlinear-enhancement of double-factor enhancement.This study highlights the importance of giving special attention to the effects of land use factors on soil erosion at the county scale,particularly in mountainous and hilly areas with extensive sloping farmland and a high cultivation rate.

Factors driving surface deformations in plain area of eastern Zhengzhou City,China

With the rapid socio-economic development and urban expansion,land subsidence has emerged as a major environmental issue,impeding the high-quality development of the plain area in eastern Zhengzhou City,Henan Province,China.However,effective prevention and control of land subsidence in this region have been challenging due to the lack of comprehensive surface deformations monitoring and the quantitative analysis of the factors driving these deformations.In order to accurately identify the dominant factor driving surface deformations in the study area,this study utilized the Persistent Scattered Interferometric Synthetic Aperture Radar(PS-InSAR)technique to acquire the spatio-temporal distribution of surface deformations from January 2018 to March 2020.The acquired data was verified using leveling data.Subsequently,GIS spatial analysis was employed to investigate the responses of surface deformations to the driving factors.The findings are as follows:Finally,the geographical detector model was utilized to quantify the contributions of the driving factors and reveal the mechanisms of their interactions.The findings are as follows:(1)Surface deformations in the study area are dominated by land subsidence,concentrated mainly in Zhongmu County,with a deformation rate of−12.5–−37.1 mm/a.In contrast,areas experiencing surface uplift are primarily located downtown,with deformation rates ranging from 0 mm to 8 mm;(2)Groundwater level,lithology,and urban construction exhibit strong spatial correlations with cumulative deformation amplitude;(3)Groundwater level of the second aquifer group is the primary driver of spatially stratified heterogeneity in surface deformations,with a contributive degree of 0.5328.The contributive degrees of driving factors are significantly enhanced through interactions.Groundwater level and the cohesive soil thickness in the second aquifer group show the strongest interactions in the study area.Their total contributive degree increases to 0.5722 after interactions,establishing them as the primary factors influencing surface deformation patterns in the study area.The results of this study can provide a theoretical basis and scientific support for precise prevention and control measures against land subsidence in the study area,as well as contributing to research on the underlying mechanisms.

Spatiotemporal Trends and Ecological Determinants in Population by Elevation in China Since 1990

It is very important to understand the ecological and socio-economic factors in population distribution and their changes over time for the compilation of regional development planning and the guidance of rational population flow.Using surface-based population data for China from 1990 to 2015,the national distribution and dynamics of the human population by elevation are quantified based on 1-km cell-size gridded distribution datasets and 1-km cell-size DEM(digital elevation model).A geographical detector model is used to quantitatively analyze the dominant role of natural geographical factors,such as topography and climate,on the spatial distribution of population.Results show that:1)the population size and density decrease rapidly with elevation below 1000 m above the sea level,and the gap in population density between low-altitude areas and high-altitude areas increases with time because of the continuous growth of population density in low-altitude areas;2)the distribution of the population can be divided into five steps according to integrated population density(IPD),in proportions of 43∶35∶21∶1∶0,and that these proportions have remained stable over the last 25 yr;3)the basic pattern of population spatial distribution is determined by natural geographical environment factors,such as topography,climate,geomorphology,and their interactions;and 4)the development of society and the economy are the driving forces for the dynamic change in the population distribution during the study period,with the distribution pattern and dynamics of population by altitude in China providing a comprehensive reflection of various geographical elements on different spatial scales.

Spatio-temporal Distribution Characteristics and Environmental Impact Factors of Lung Cancer Mortality: A Case Study of Yuhui District in Bengbu City, China

Among cancers, lung cancer is the most common cause of death in China. For the prevention and control of lung cancer, it is necessary to investigate the spatial and temporal distribution of lung cancer mortality, as well as the changes in the trend and the affecting mechanism. Based on statistics and auto-correlation analysis, this paper studied the spatial and temporal distribution of lung cancer mortality in Yuhui District, Bengbu, Huaihe River Basin, from 2017 to 2020. In addition, Spearman’s Rank Correlation Assessment Model and Geographic Detector Model were used to examine the relationship between environmental factors and lung cancer mortality to identify impact factors and their mechanisms. The findings indicated that: 1) from the characteristics of temporal distribution, the number of lung cancer deaths exhibited a linear growth tendency, with the highest mortality in winter;2) from the characteristics of spatial distribution, lung cancer mortality showed a strong spatial agglomeration form, concentrating on two clustering areas, located in the old city and the central city of Bengbu, near the Huaihe River;3) from the point of view of the whole research area, there were 15 impact factors with significant correlation in the built and natural environment factors. The significant impacting factors in the built environment included land use, road traffic, spatial form and blue-green space, which could indirectly affect lung cancer mortality, while air pollution and temperature constituted the significant impacting factors in the natural environment;4) the influence of screened environmental factors on lung cancer mortality was different. Spatial stratified heterogeneity assessment, the interaction among environmental factors demonstrated statistical significance, it was found that the interaction between environmental factors in pairs had a significant enhancement effect on lung cancer mortality. To some extent, urban planning and policies could reduce lung cancer mortality.

Coordinated development efficiency between cultivated land spatial morphology and agricultural economy in underdeveloped areas in China:Evidence from western Hubei province

Suitable spatial morphology of cultivated land is a basic requirement for sustaining agricultural economic development in mountainous areas.Coordinated development efficiency of cultivated land spatial morphology and agricultural economy(CECA)is of great practical significance to measure the efficiency of cultivated land use,and thereby promote regional rural revitalization.However,few studies to date have focused on coordinated development efficiency between cultivated land use and agricultural economy in mountainous areas from the perspective of cultivated land spatial morphology.Thus,the present study explores CECA with this focus using the data envelopment analysis method,and analyzes the key influencing factors via a geographical detector model in 16 counties in western Hubei province.The results show the following:(1)CECA exhibits significant spatial heterogeneity that is high in the south of the study area and low in the north;(2)scale efficiency is the primary limiting factor for CECA;(3)the insufficient output of cultivated land use mainly restricts CECA in the south of the study area,while individual county in the north suffered from input redundancy and insufficient output;and(4)population density in the southern region has the most significant effect on CECA,and gross domestic product has the greatest impact in the northern region.The results contribute to the derivation of specific measures by which to promote cultivated land use efficiency and sustainable development of the social economy.

Sandwich mapping of rodent density in Jilin Province, China

Rodents are the main host animals that spread plague, and Spermophilus dauricus（S. dauricus） is the most common rodent in North China. In this study, a rodent density survey was carried out in China＇s Jilin Province from April to August 2005. Moran＇s I and semivariogram curves were used to investigate the spatial distribution characteristics of the sampling data. We found that the spatial auto-correlation index was low and failed to generate a meaningful semivariogram curve. In this case, commonly used interpolators, such as kriging, were not suitable for mapping density over the study area. However, the Sandwich model, which is based on spatial stratified heterogeneity, could be applied to our data. Our results showed that the type of soil and land use significantly influenced the distribution of rodent density, and the interactive effect of these variables was much stronger than that of each variable alone. The Sandwich-estimated rodent density map showed that rodent density increased from the southeast to the northwest in Jilin Province. Finally, a framework of a rodent density survey using the Sandwich model was introduced.