Bivariate Spatial Autocorrelation Research Articles

Identification of Priority Implementation Areas and Configuration Types for Green Infrastructure Based on Ecosystem Service Demands in Metropolitan City.

During urbanization in developing countries, fragmentation of green infrastructure due to increasing populations and the expansion of construction land leads to an extremely serious imbalance between the supply and demand for urban ecosystem services. In this study, the central city of Zhengzhou, a central city in central China, was selected as the study area and the excessive demand for six ecosystem services, namely, air purification, flood regulation, heat regulation, hydrological regulation, CO2 sequestration and recreational services, was quantitatively evaluated. The entropy method was used to calculate the weights of various ecosystem services, and spatial overlay analysis was performed to obtain the comprehensive ecosystem service excessive demand. Finally, bivariate spatial autocorrelation analysis was used to explore the response of population density to comprehensive excessive demand for ESs. The results of this study indicate that: (1) The most prevalent need is for more CO2 regulation service throughout the study area. (2) Except for hydrological regulation service, the spatial distribution of the remaining highly excessive ecosystem service demands are mostly concentrated in old neighborhoods. (3) Of the six excessively demanded economic services, rainwater regulation obtained the greatest weight, reflecting the poor urban infrastructure configuration for countering the rapidly increasing threat of flooding caused by climate change in the city. (4) The comprehensive ecosystem service excessive demand results show that there are eight priority green infrastructure implementation blocks in the central city of Zhengzhou. (5) There were three agglomeration types between population density and comprehensive excessive demand for ESs: high-high type, low-high type and low-low type. The spatial distribution characteristics of population density and comprehensive ES demand are positively correlated. The results of this study could help to provide information for decision making when delineating the priority areas and types of green infrastructure implementation in developing cities.

A Synthetic Landscape Metric to Evaluate Urban Vegetation Quality: A Case of Fuzhou City in China

Urban vegetation plays a very important role in regulating urban climate and improving the urban environment. There is an urgent need to construct an effective index to quickly detect urban vegetation quality changes. In this study, a synthetic vegetation quality index (VQI) was proposed using a holistic approach based on the quality of vegetation itself and the spatial relationship with its surroundings, composed of four selected variables: normalized difference vegetation index (NDVI), patch aggregation index (AI), patch density (PD), and percentage of landscape (PLAND). Principal component analysis (PCA) was employed to calculate weights for each variable due to its objectivity. Then, taking Fuzhou City, southeast China as the case study, the scale effects of the VQI under different moving window sizes (500 m, 1 km, 2 km, …, 5 km) and the spatiotemporal changes were explored. The results showed that a VQI with a window size of 3 km had the highest correlations with all the selected indicators. Meanwhile, the representativeness and the effectiveness of the VQI were validated by the percentage eigenvalues of PC1, as well as Pearson correlation analysis and bivariate spatial autocorrelation analysis. We also revealed that the proposed VQI had the greatest explanatory power for land surface temperature (LST) among all the factors in both studied years (2000 and 2016), with the VQI’s interpretation of LST being 0–44% better than any individual indicator except for AI in 2000. Additionally, our work revealed that the location of vegetation has a great impact on the urban thermal environment. The VQI can assess urban vegetation quality effectively and quickly.

Degradation or Restoration? The Temporal-Spatial Evolution of Ecosystem Services and Its Determinants in the Yellow River Basin, China

Ecosystem services (ESs) are irreplaceable natural resources, and their value is closely related to global change and to human well-being. Research on ecosystem services value (ESV) and its influencing factors can help rationalize ecological regulatory policies, and is especially relevant in such an ecologically significant region as the Yellow River Basin (YRB). In this study, the ecological contribution model was used to measure the contribution of intrinsic land use change to ESV, the bivariate spatial autocorrelation model was applied to investigate the relationship between land use degree and ESV, and the geographical detector model (GDM) and geographically weighted regression (GWR) were applied to reveal the impact of natural and socio-economic factors on ESV. Results showed that: (1) The total ESV increased slightly, but there were notable changes in spatial patterns of ESV in the YRB. (2) Land use changes can directly lead to ESV restoration or degradation, among which, conversion from grassland to forest land and conversion from unused land to grassland are vital for ESV restoration in the YRB, while degradation of grassland is the key factor for ESV deterioration. (3) According to GDM, NDVI is the most influential factor affecting ESV spatial heterogeneity, and the combined effect of multiple factors can exacerbate ESV spatial heterogeneity. (4) GWR reveals that NDVI is always positively correlated with ESV, GDP is mainly positively correlated with ESV, and population density is mainly negatively correlated with ESV, while positive and negative correlation areas for other factors are roughly equal. The findings can provide theoretical support and scientific guidance for ecological regulation in the YRB.

Spatial relationship between landscape ecological risk and ecosystem service value in Fujian Province, China during 1980-2020

Understanding the relationship between landscape ecological risk and ecosystem service value (ESV) is important for building an ecological security pattern and enhancing human well-being. Taking Fujian Province as the research area, based on the remote sensing monitoring data of land use in 1980, 2000, and 2020, we carried out a grid resampling size of 5 km × 5 km in the study area, quantitatively evaluated the landscape ecological risk and ESV, and analyzed the spatio-temporal variations. The spatial correlation between landscape ecological risk and ESV was investigated by using the bivariate spatial autocorrelation analysis and the spatial regression models. The results showed that the landscape ecological risk level in Fujian Province changed from medium level to low level, with the situation being improved. The landscape ecological risk level was generally higher in the east region and lower in the west region. ESV generally declined. The functional structure of each ecosystem was relatively stable. ESV spread from high to low with high value area as the core. There was a significant negative spatial correlation between landscape ecological risk and ESV. Landscape ecological risk had a negative effect on ecosystem total ser-vice value, with the strongest impact on the supply function.

Identifying the Spatial Imbalance in the Supply and Demand of Cultural Ecosystem Services.

Cultural ecosystem services (CESs) are an important part of ecosystem services (ESs). Correctly understanding the supply and demand relationship of CES is the premise of ES sustainable management and helps to improve human well-being. However, the evaluation and mapping of CES supply and demand represents a significant gap in ES research. Using the Shigou Township of Mizhi County in China as an example, in this study, we evaluated CES supply and demand at the village scale. We first considered three aspects of supply potential, accessibility and quality to construct an indicator system of six types of CES supply, including aesthetic (Aest), sense of place (SP), social relations (SR), cultural heritage (Cult), education (Edu) and recreation (Recr) and obtained demand data through a questionnaire. Then, we identified the imbalance in the supply and demand of CES by Z-score standardization based on the quantification of the CES supply and demand. Secondly, bivariate spatial autocorrelation analysis was used to identify tradeoffs/synergies on the CES supply side, and chi-square tests were used to identify CES demand differences between stakeholder groups. The results indicated that the supply–demand patterns of CES presented evident spatial differences. The low-supply–high-demand patterns of Aest, SR and Recr accounted for the largest proportions, with values of 33.33%, 33.33% and 30.95%, respectively. The low-supply–low-demand patterns of SP and Cult accounted for the largest proportions, with values of 30.95% and 38.10%, respectively. The low-supply–low-demand pattern of Edu accounted for the smallest proportion (21.43%) and was mainly located in the south of Shigou Township. The southwest, northeast and central areas of Shigou Township were the key regions of tradeoffs/synergies of CES supply. There were significant differences in CES demand for SR, Cult and Edu among stakeholder groups. The results could contribute to optimizing regional ecosystem management and provide effective information for improving the imbalance between the supply and demand of CES.

Is There Spatial Dependence or Spatial Heterogeneity in the Distribution of Vegetation Greening and Browning in Southeastern China?

Vegetation is an indispensable component of terrestrial ecosystems and plays an irreplaceable role in mitigation of climate change. Global vegetation changes (i.e., greening and browning) still occur frequently, however, little is known about the spatial relationships between these two processes. Based on the normalized difference vegetation index (NDVI) dataset from 1998 to 2018 in Fujian Province, China. The Theil-Sen and Mann-Kendall tests were used to explore temporal changes in vegetation growing, then the spatial relationships of greening and browning was distinguished with bivariate spatial autocorrelation analysis, and the spatial variation in the relationship between vegetation changes and driving factors was explored by the geographical detector. The results showed that from 1998 to 2018, the average NDVI value increased from 0.75 to 0.83; 89.61% of the study area experienced vegetation greening, while 5.7% experienced significant browning, with active vegetation changes occurred along roads and nearby cities. The spatial autocorrelation results showed that the spatial relationships between vegetation greening and browning were dominated by spatial heterogeneity (i.e., high greening and low browning, H-L clusters accounting for 60% and low greening and high browning, L-H clusters accounting for 14%), but we also revealed that there were still quite a few places (4%) with spatial dependence (i.e., high greening and browning, H-H clusters), occurring around urban areas and along roads. The factor detector indicated that the nighttime light intensity was among the most dominant factor of vegetation changes, followed by elevation and slope. Although the individual effect of the distance to roads was relatively weak on the vegetation changes, its indirect effect was found to be the strongest by the interaction detector, which was obtained from the interactions much larger than its independent impact. Simultaneously, the risk detector revealed that the greening preferred occurring in places with lower nighttime light intensity (<1.1 nW cm−2sr−1), higher elevation (>43.4 m) and slope (>6.3°). Moreover, we found that the vegetation changes primarily occurred within a distance of 1685.4 m from roads. Our findings could deepen the understanding of vegetation change patterns and provide advice for mitigating the impact on the vegetation changes.

Spatiotemporal Evolution and Relationship between Night Time Light and Land Surface Temperature: A Case Study of Beijing, China

Rapid urbanization has triggered significant changes in urban land surface temperature (LST), which in turn affects urban ecosystems and the health of residents. Therefore, exploring the interrelationship between urban development and LST can help optimize the urban thermal environment and promote sustainable development. Based on remote sensing data from 2004–2019 within the sixth ring road of Beijing, this study investigates the spatiotemporal coupling law of night time light (NTL) and LST using an overall coupling model and analyzes the degree of coordination between them using a coordination model. The spatial response law between them was also analyzed using standard deviation ellipses and bivariate spatial autocorrelation. The results show that, from the perspective of spatiotemporal evolution, the spatial distributions of NTL and LST within the sixth ring road of Beijing were closely related from 2004 to 2019, although the overall coupling of NTL and LST was initially decreased and then continuously increased. From the perspective of coordination types, the main types of coordination between NTL and LST deteriorated over time. The increase in LST lagged behind NTL from 2004 to 2009 (heating hysteresis type), while LST increased ahead of NTL from 2014 to 2019 (heating advance type). This suggests that urban development became less efficient, while LST increases became more significant. In terms of correlation, NTL and LST showed significant positive correlation and spatial positive correlation; the correlation coefficient first decreased significantly and then continued to increase. From 2004 to 2009, the temperature increase caused by urbanization was suppressed due to the 2008 Beijing Olympics and related ecological protection policies, resulting in a significant decrease in the correlation coefficient between NTL and LST. From 2009 to 2019, short-term measures taken by Beijing during the Olympic Games were no longer effective, and the opposition between urban development and related policies made the policies increasingly less effective, thereby increasing the correlation coefficient between NTL and LST, and the increase in LST was more significant. This will greatly affect the urban ecological environment and residents’ health and make the previous government investment to suppress the temperature increase all in vain. This study can provide theoretical and practical support for the development of thermal environment optimization schemes and LST mitigation strategies in Beijing and other cities.

Modeling of spatial pattern and influencing factors of cultivated land quality in Henan Province based on spatial big data.

The quality of cultivated land determines the production capacity of cultivated land and the level of regional development, and also directly affects the food security and ecological safety of the country. This paper starts from the perspective of spatial pattern of cultivated land quality and uses spatial autocorrelation analysis to study the spatial aggregation characteristics and differences of cultivated land quality in Henan Province at the county level scale, and also uses bivariate spatial autocorrelation to analyze the influence of neighboring influences on the quality of cultivated land in the target area. The spatial autoregressive model was used to further analyze the driving factors affecting the quality of cultivated land, and the influence of cultivated land area index was coupled in the process of rating analysis, which was finally used as a basis to propose more precise measures for the protection of cultivated land zoning. The results show that: (1) The quality of cultivated land in Henan Province has a strong spatial correlation (global Moran’s I≈0.710) and shows an obvious aggregation pattern in spatial distribution; positive correlation types (high-high and low-low) are concentrated in north-central and western mountainous areas of Henan Province, respectively; negative correlation types are discrete. The negative correlation types are distributed in a discrete manner. (2) The bivariate spatial autocorrelation results show that Slope (Moran’s I≈-0.505), Irrigation guarantee rate (IGR, 0.354), Urbanization rate (-0.255), Total agricultural machinery power (TAMP, 0.331) and Pesticide use (0.214) are the main influencing factors. (3) According to the absolute values of the regression coefficients, it can be seen that the magnitude of the influence of different factors on the quality of cultivated land is: Slope (0.089) >IGR (0.025) > Urbanization rate (0.002) > TAMP (0.001) > Pesticide use (1.96e-006). (4) Based on the spatial pattern presented by the spatial autocorrelation results, we proposed corresponding protection zoning measures to provide more scientific reference decisions and technical support for the implementation of refined cultivated land management in Henan Province.

Influence of spatiotemporal changes of impervious surface on the urban thermal environment: A case of Huai'an central urban area

Influence of spatiotemporal changes of impervious surface on the urban thermal environment: A case of Huai'an central urban area

Effects of urban agglomeration and expansion on landscape connectivity in the river valley region, Qinghai-Tibet Plateau

Effects of urban agglomeration and expansion on landscape connectivity in the river valley region, Qinghai-Tibet Plateau

A green infrastructure planning framework–guidance for priority, hubs and types

A green infrastructure planning framework–guidance for priority, hubs and types

Spatial-Temporal Variation and Tradeoffs/Synergies Analysis on Multiple Ecosystem Services: A Case Study in Fujian

The rapid urbanization process has severely affected the ecological security and ecosystem services (ESs) in China’s southern province of Fujian, and threated the sustainable development of the local economy and society in the last two decades. This study mapped the spatial-temporal variation of four types of ESs and evaluated the tradeoffs/synergies among the ESs in Fujian Province from 2000 to 2020 on the three scales of the province, city and county. The results showed that: (1) From 2000 to 2020, the three ESs functions of soil conservation service, carbon storage service, and habitat quality decreased, while the function of food supply service increased. (2) At the provincial scale, soil conservation services, carbon storage services, and habitat quality were in a synergistic relationship, and food supply service was always in tradeoffs relationships with soil conservation services, carbon storage services, and habitat quality. At the prefecture-level scale, the tradeoffs/synergies among ESs vary among prefecture-level cities. At the county scale, the Moran’s I index of bivariate spatial autocorrelation was consistent with the correlation coefficient, and the tradeoffs/synergies between ESs showed significant spatial heterogeneity. (3) Based on the correlation analysis method, the Ecosystem Service Tradeoff-synergy Degree (ESTD) model and bivariate spatial autocorrelation analysis can clearly show the relationship between various ESs, and the research results are relatively consistent. The spatial distribution of four ecosystem services in Fujian province showed a specific aggregation pattern. High—high concentrations and low—low concentrations are strong. Low—high agglomeration and high—low agglomeration are weak.

Analysis of cropping pattern in black soil region of Northeast China based on geo-information Tupu.

Different cropping patterns have their own economic and ecological significance. Developing cropping patterns suitable for local conditions is needed to protect and make good use of black soils. At present, the cropping patterns and their spatial characteristics in the black soil region of Northeast China is poorly understood. Based on the crop classification data in 2017-2019, we used geo-information Tupu methods, distribution index model, and bivariate spatial autocorrelation to examine the cropping patterns. The results showed that: 1) The main cropping patterns in the black soil region of Northeast China were continuous maize cropping, continuous rice cropping, continuous soybean cropping, and maize-soybean rotation, accounting for 38.3%, 18.5%, 10.3% and 26.0%, respectively. The maize-soybean rotation included maize-soybean two-year rotation, maize-maize-soybean three-year rotation, and soybean-soybean-maize three-year rotation, accounting for 44.1%, 34.5% and 21.4% of the rotation area, respectively. 2) Various cropping patterns had obviously horizontal differentiation. For instance, continuous maize cropping had very obvious gradient differentiation characteristics in temperature and humidity, but soybean continuous cropping and maize-soybean rotation showed no gradient differentiation, while continuous rice cropping had gradient differentiation only in humidity. 3) Various cropping patterns had obviously spatial clustering characteristics. They had spatial transition characteristics from soybean continuous cropping, soybean-soybean-maize three-year rotation, maize-soybean two-year rotation, maize-maize-soybean three-year rotation, to continuous maize cropping. The cropping pattern in black soil region of Northeast China was dominated by continuous cropping. Understanding its distribution pattern can provide a basis for future spatial optimization of crop rotation.

Spatial-temporal trade-offs of land multi-functionality and function zoning at finer township scale in the middle reaches of the Heihe River

Spatial-temporal trade-offs of land multi-functionality and function zoning at finer township scale in the middle reaches of the Heihe River

Multidimensional Spatial Match of Hierarchical Healthcare Facilities Considering Floating Population: A Case of Beijing, China

Good health and well-being are key to achieving the main goals of the UN Sustainable Development Goals (SDGs), especially after the outbreak of the COVID-19 epidemic. What is a concern for both government and society is how to understand the spatial match of hierarchical healthcare facilities and residential areas in terms of quantity and capacity, to meet the challenges of various diseases and build a healthy life. Using hierarchical healthcare data and cellphone signaling data in Beijing, China, we used the kernel density estimation, a bivariate spatial autocorrelation model, and a coupling index to explore the spatial relationships between hierarchical healthcare facilities and residential areas. We found large numbers of both healthcare facilities and residential areas in the urban center, and small numbers of both at the urban edge. The hospitals and designated retail pharmacies in the densely populated areas do not have enough capacity to meet the need of the population. In addition, the capacity of primary healthcare institutions can meet people’s needs. Our findings would serve as a reference for urban planning, optimization of hierarchical healthcare facilities, and research on similar themes.

Quantitative Assessment for the Spatiotemporal Changes of Ecosystem Services, Tradeoff–Synergy Relationships and Drivers in the Semi-Arid Regions of China

Ecosystem services in arid inland regions are significantly affected by climate change and land use/land cover change associated with agricultural activity. However, the dynamics and relationships of ecosystem services affected by natural and anthropogenic drivers in inland regions are still less understood. In this study, the spatiotemporal patterns of ecosystem services in the Hexi Region were quantified based on multiple high-resolution datasets, the InVEST model and the Revised Wind Erosion Equation (RWEQ) model. In addition, the trade-offs and synergistic relationships among multiple ecosystem services were also explored by Pearson correlation analysis and bivariate spatial autocorrelation, and redundancy analysis (RDA) was also employed to determine the environmental drivers of these services and interactions. The results showed that most ecosystem services had a similar spatial distribution pattern with an increasing trend from northwest to southeast. Over the past 40 years, ecosystem services in the Hexi Region have improved significantly, with the water retention and soil retention increasing by 87.17 × 108 m3 and 287.84 × 108 t, respectively, and the sand fixation decreasing by 369.17 × 104 t. Among these ecosystem services, strong synergistic relationships were detected, while the trade-offs were found to be weak, and showed significant spatial heterogeneity in the Hexi Region. The spatial synergies and trade-offs in the Qilian Mountains were 1.02 and 1.37 times higher than those in the Hexi Corridor, respectively. Human activities were found to exacerbate the trade-offs between ecosystem services by increasing water consumption in the Hexi Corridor, with the exception of carbon storage. In particular, there were significant tradeoffs between food production and water retention, and between soil retention and habitat quality in the oases of the Hexi Corridor, which is affected by rapid population growth and cropland expansion. Additionally, precipitation, temperature and vegetation cover in the Qilian Mountains have increased significantly over the past four decades, and these increases significantly contributed to the enhancements in water retention, carbon storage, habitat quality, soil retention and food production. Nevertheless, the amount of sand fixation significantly decreased, and this was probably associated with the reduction in wind speed over the past four decades. Our results highlighted the importance of climate wetting and water resource management in the enhancement of ecosystem services and the mitigation of food production trade-offs for arid inland regions.

交通通达度对生态系统健康的影响——以长江中游城市群为例

PDF HTML阅读 XML下载 导出引用 引用提醒 交通通达度对生态系统健康的影响——以长江中游城市群为例 DOI: 10.5846/stxb202101230245 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（42001187，42001231，41701629）；地表过程与资源生态国家重点实验室开放基金项目（2021-KF-03） Impact of traffic accessibility on ecosystem health: A case study of the middle reaches of the Yangtze River Urban Agglomerations Author: Affiliation: Fund Project: National Natural Science Foundation of China, No.42001187 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:完善的交通基础设施网络是形成高度同城化和高度一体化城市群的前提和基础，科学探测城市群地区交通通达度对生态系统健康状况的影响机理对城市群地区生态系统保护以及区域可持续发展具有重要实践意义和价值。基于多源数据分别测度了1995-2015年长江中游城市群交通通达度以及生态系统健康水平，并借助双变量空间自相关与空间回归模型从全局和局部的角度揭示了交通通达度对生态系统健康的影响机理。研究结果显示：（1）研究期间长江中游城市群生态系统健康状况总体呈现降低态势，山区生态系统健康水平显著高于平原地区；（2）双变量空间自相关分析结果显示交通通达度和生态系统健康水平之间存在显著的空间依赖性，二者之间主要的关系类型包括低交通通达度水平-低生态系统健康水平、高交通通达度水平-低生态系统健康水平和低交通通达度水平-高生态系统健康水平三种类型；（3）空间回归结果显示交通通达度的增加会导致生态系统健康状况的恶化，而且交通通达度对生态系统健康的影响具有显著的空间异质性。研究发现可以为长江中游城市群地区生态系统健康保护宏观调控政策制定以及差异化管控政策制定提供科学依据。 Abstract:The gradual improvement of traffic network in urban agglomeration plays an important role in the construction of national land development environment, construction of national land development structure, and optimization of functional space system. At the same time, it also causes serious disturbance to the structure and function of ecosystem and the health status of ecosystem, and seriously threatens the sustainable development of urban agglomeration. How to promote the high-quality development of urban agglomerations and alleviate the disturbance and damage of urban agglomerations to ecosystem health has become an urgent problem to be answered and solved in the current development process of urban agglomerations. To scientifically reveal the spatial relationship between traffic accessibility and ecosystem health in urban agglomerations, and to clarify the impact mechanism of traffic accessibility on ecosystem health is an effective way to solve this issue. Based on multi-source data, this study measured the traffic accessibility and ecosystem health level in the middle reaches of the Yangtze River Urban Agglomerations (MRYRUA) from 1995 to 2015, and estimated the influence mechanism of traffic accessibility on ecosystem health with bivariate spatial autocorrelation and an integrated spatial regression models from the global and local perspectives. The results showed that:(1) the overall ecosystem health in the MRYRUA exhibited a decreasing trend, and the ecosystem health level in the mountainous areas were significantly higher than those of the plain areas during the study period. (2) The bivariate spatial autocorrelation results showed that there was a significantly spatial dependence between traffic accessibility and ecosystem health. The spatial relationships between them mainly included low traffic accessibility-low ecosystem health level, high traffic accessibility-low ecosystem health level, and low traffic accessibility-high ecosystem health level. (3) The spatial regression results showed that traffic accessibility development would lead to the deterioration of ecosystem health. The impact of traffic accessibility on ecosystem health had significantly spatial heterogeneity. The results show that the ecosystem health is not only affected by the ecosystem elements of the local unit, but also by the health status of the surrounding units or distant units and other factors. Therefore, the trans-regional joint governance is particularly important in urban agglomeration. Secondly, the results show that the impact of traffic accessibility on ecosystem health has significant spatial heterogeneity, and local differentiated management and control measures for regional future traffic construction and ecosystem health protection are necessary for the sustainable development of urban agglomerations. The findings can provide a scientific basis for the formulation of macro-control policies for ecosystem health protection and differentiated control policies for urban agglomerations in the MRYRUA. 参考文献 相似文献 引证文献

The Influence of Green Space Patterns on Land Surface Temperature in Different Seasons: A Case Study of Fuzhou City, China

Background: Urban green space (UGS) has been shown to play an important role in mitigating urban heat island (UHI) effects. In the context of accelerating urbanization, a better understanding of the landscape pattern mechanisms affecting the thermal environment is important for the improvement of the urban ecological environment. Methods: In this study, the relationship between land surface temperature (LST) and the spatial patterns of green space was analyzed using a bivariate spatial autocorrelation and spatial autoregression model in three seasons (summer, transition season (spring), and winter) with different grid scales in Fuzhou city. Results: Our results indicated that the LST in Fuzhou City has a significant spatial autocorrelation. The percentage of landscape and patch density area were negatively correlated with surface temperature. The results of our indicators differed according to the season, with population density and distance to the water indicators not being significant in the winter. The coefficient of determination was higher at the 510 m grid scale on this study’s scale. Conclusion: This study extends our understanding on the influence of UHI effects after accounting for different seasonal and spatial scale factors. It also provides a reference for urban planners to mitigate heat islands in the future.

Response of Spatio-Temporal Differentiation Characteristics of Habitat Quality to Land Surface Temperature in a Fast Urbanized City

The degradation and loss of global urban habitat and biodiversity have been extensively studied as a global issue. Urban heat islands caused by abnormal land surface temperature (LST) have been shown to be the main reason for this problem. With the accelerated urbanization process and the increasing possibility of abnormal temperatures in Zhengzhou, China, more and more creatures cannot adapt and survive in urban habitats, including humans; therefore, Zhengzhou was selected as the study area. The purpose of this study is to explore the response of urban habitat quality to LST, which provides a basis for the scientific protection of urban habitat and biodiversity in Zhengzhou from the perspective of alleviating heat island effect. We used the InVEST-Habitat Quality model to calculate the urban habitat quality, combined with GIS spatial statistics and bivariate spatial autocorrelation analysis, to explore the response of habitat quality to LST. The results show the following: (1) From 2000 to 2015, the mean value of urban habitat quality gradually decreased from 0.361 to 0.304, showing a downward trend as a whole. (2) There was an obvious gradient effect between habitat quality and LST. Habitat quality’s high values were distributed in the central and northern built-up area and low values were distributed in the high-altitude western forest habitat and northern water habitat. However, the distribution of LST gradient values were opposite to the habitat quality to a great extent. (3) There were four agglomeration types between LST and habitat quality at specific spatial locations: the high-high type was scattered mainly in the western part of the study area and in the northern region; the high-low type was mainly distributed in the densely populated and actively constructed central areas; the low-low type was mainly distributed in the urban-rural intersections and small and medium-sized rural settlements; and the low-high type was mainly distributed in the western mountainous hills and the northern waters.

Impacts of Human Activities on Ecosystem Service Value in Arid and Semi-Arid Ecological Regions of China.

The quantitative and spatial–temporal variations in the characteristics of ecosystem value can be helpful to improve environmental protection and climate adaptation measures and adjust the balance between economic development and the ecological environment. The arid and semi-arid regions of China are undergoing the effects of climate change across the entire northern hemisphere. Their ecological environments are fragile and in conflict with anthropogenic activities, which significantly altered more ecosystems services in these regions. Therefore, estimating the effects of anthropogenic activities on ecosystem services is important for formulating ecological policy and regional environmental mitigation plans of these regions. This study employed the model of ecosystem service value (ESV) assessment and the bivariate spatial autocorrelation method to reveal the spatiotemporal variations in the characteristics of ecosystem value in the arid and semi-arid ecological regions of China and its interaction with human activities. Results showed that (1) the total value of ES of the study area increased from USD 487,807 billion in 2000 to USD 67,831,150 billion 2020; (2) the ES value provided by forest land first increased by 5.60% from 2000 to 2020; (3) the ESV provided by grassland showed an overall decline over the 20 years. Food and raw material production showed the lowest ES value, and climate regulation and soil conservation decreased from 2000 to 2020; (4) the index of human footprint patches decreased from 45.80% in 2000 to 17.63% in 2020, while the high and very high human footprint index areas increased significantly, mainly due to the rapid urbanization and improvement of railway networks in these areas. Spatially, the regions with high human footprint were mostly dispersed in the northeastern of China such as Shanxi and Gansu, whereas the regions with a low human footprint remained mainly located in the central and southwestern parts of China; (5) significant spatial dependencies between changes in ESV and the human footprint index were recorded. Our study could provide a scientific basis for ecosystem functions regulation and land development security in arid and semi-arid ecological regions.