Urban Landscape Pattern Research Articles

The Effects of Urban Landscape Pattern Evolution on Habitat Quality Based on InVEST Model

With the acceleration of urbanization, urban landscape patterns have been rapidly adjusted and reorganized, which has resulted in drastic changes in the quality of urban habitats. To achieve the objective of a new type of eco-conservative urbanization, it is urgent that we strengthen the research on the relationship between the habitat quality and landscape patterns. Based on the InVEST model and FRAGSTATS landscape pattern index, in this study, we evaluated the habitat quality evolution and landscape pattern change trend of Harbin based on remote sensing images from 2000, 2010, and 2020, and we explored the correlation between them using Pearson’s correlation coefficient. The results showed that: (1) From 2000 to 2020, the habitat quality in Harbin decreased from 0.68 to 0.65, with an overall downward trend. The low-quality habitat increased by 1.25%, while the high-quality habitat decreased by 6.43%. The spatial heterogeneity was substantial, and the distribution pattern was high in the middle, middle in the east, and low in the west; (2) The landscape pattern index of Harbin obviously changed, and the overall landscape pattern had a trend of further fragmentation and gradual irregularity, decreases in the diversity and evenness, and spatial heterogeneity; (3) For most of the land types, there were substantial correlations between the habitat quality and landscape pattern indices. The PD, COHESION, and LSI had the most substantial correlations with the habitat quality. The research results provide a theoretical basis for the ecological protection and sustainable development in Harbin.

County-Based PM2.5 Concentrations’ Prediction and Its Relationship with Urban Landscape Pattern

Satellite top-of-atmosphere (TOA) reflectance has been validated as an effective index for estimating PM2.5 concentrations due to its high spatial coverage and relatively high spatial resolution (i.e., 1 km). For this paper, we developed an emsembled random forest (RF) model incorporating satellite top-of-atmosphere (TOA) reflectance with four categories of supplemental parameters to derive the PM2.5 concentrations in the region of the Yangtze River Delta-Fujian (i.e., YRD-FJ) located in east China. The landscape pattern indices at two levels (i.e., type level and overall level) retrieved from 3-year land classification imageries (i.e., 2016, 2018, and 2020) were used to discuss the correlation between county-based PM2.5 values and landscape pattern. We achieved a cross validation R2 of 0.91 (RMSE = 9.06 μg/m3), 0.89 (RMSE = 10.19 μg/m3), and 0.90 (RMSE = 8.02 μg/m3) between the estimated and observed PM2.5 concentrations in 2016, 2018, and 2020, respectively. The PM2.5 distribution retrieved from the RF model showed a trend of a year-on-year decrease with the pattern of “Jiangsu > Shanghai > Zhejiang > Fujian” in the YRD-FJ region. Our results also revealed that the landscape pattern of farmland, water bodies, and construction land exhibited a highly positive relationship with the county-based average PM2.5 values, as the r coefficients reached 0.74 while the forest land was negatively correlated with the county-based PM2.5 (r = 0.84). There was also a significant correlation between the county-based PM2.5 and shrubs (r = 0.53), grass land (r = 0.76), and bare land (r = 0.60) in the YRD-FJ region, respectively. Three landscape pattern indices at an overall level were positively correlated with county-based PM2.5 concentrations (r = 0.80), indicating that the large landscape fragmentation, edge density, and landscape diversity would raise the PM2.5 pollution in the study region.

Quantifying the effects of 2D/3D urban landscape patterns on land surface temperature: A perspective from cities of different sizes

With the continuous development of urbanization, two-dimensional (2D) landscape pattern is insufficient to explain the complex urban thermal phenomenon, while three-dimensional (3D) urban composition directly affects the process of surface energy exchange and becomes an important influencing factor in regard to land surface temperature (LST). There have been some studies on the relationship between 2D/3D urban patterns and LST, however, there are relatively few studies on the effects of 2D/3D urban landscape on LST in cities of different sizes. In this research, the relationship of 2D/3D urban patterns and LST in three cities (Beijing, Shijiazhuang and Cangzhou) of different sizes were analyzed by using the boosted regression tree model. The results were as follows: 1) With the increase in city size, LST gradually increased in summer and decreased in winter. 2) The larger the size of the city was, the greater the number of factors that significantly affected LST (p < 0.05). 3) In spring, summer and autumn, volume of tree (TV), mean tree height (MTH) and the largest patch index of impervious surface (LPI_IS) had a high relative influence, and the average total relative influences of these three metrics were 80.08%, 78.99% and 45.14%, respectively. 4)There was a significant negative correlation between TV and LST, a positive correlation between LPI_IS and LST and a combination of positive and negative correlations between MTH and LST. The study of the effects of 2D and 3D urban morphology on LST could help urban planners and managers create more scientific urban planning and development management measures to mitigate urban thermal environment problems.

What Are the Correlations between Human Disturbance, the Spatial Pattern of the Urban Landscape, and Eco-Environmental Quality?

Human transformation of the landscape is reflected in its composition and spatial pattern. Therefore, exploring the response of the eco-environment to the composition and spatial pattern of the landscape is beneficial to providing a theoretical basis for urban planners. In this study, we take a typical oil city in China as an example and introduce the hemeroby index, landscape metrics, and a remote sensing-based ecological index (RSEI) to calculate and evaluate the urban landscape pattern, human disturbance, and eco-environmental quality, as well as exploring the relationships between them. The results demonstrate that the mean RSEI value of the study area was 0.4866, indicating that its eco-environmental quality was relatively moderate. The whole study area had a relatively high degree of human disturbance (hemeroby index = 7.4498), where the effect of human disturbance on the eco-environment was more intense in natural ecosystems, such as forest and grasslands, but less intense in artificial landscapes, such as built-up areas and farmlands. The urban landscape pattern was significantly correlated with eco-environmental quality, among which the proportion of green space and impervious surface had the strongest correlations with the mean RSEI, with correlation coefficients of 0.538 and −0.577, respectively. In addition, the correlation between the landscape pattern and the RSEI presented obvious spatial heterogeneity.

基于不同样带的干旱区城市景观格局时空演变特征——以张掖市为例

PDF HTML阅读 XML下载 导出引用 引用提醒 基于不同样带的干旱区城市景观格局时空演变特征——以张掖市为例 DOI: 10.5846/stxb202202210408 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（42101276）；甘肃省科技计划项目（20JR5RA529）；国家自然科学基金项目（41661035） Spatio-temporal evolution of urban landscape pattern in arid areas based on different zones: A case study of Zhangye City Author: Affiliation: Fund Project: National Natural Science Foundation of China, No.42101276; Science and Technology Project of Gansu Province, No.20JR5RA529; National Natural Science Foundation of China, No.41661035; Regional Fund of National Natural Science Foundation of China, No.41961027 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:景观格局的变化影响着区域生态安全及可持续发展，研究干旱区城市景观格局时空变化特征，对干旱区景观格局优化具有一定的指导意义。基于1987、1995、2000、2006、2011和2016年6期土地利用数据，利用景观格局指数计算方法，研究张掖市景观格局的时空演变特征。结果表明：（1）2016年张掖市景观类型主要为未利用地，最大斑块指数和斑块聚集度最高，草地和耕地次之，草地的斑块个数和密度最大。（2）张掖市景观格局呈现明显的地域分异特征，圈层梯度带上揭示了绿洲-荒漠用地变化，研究期内第1梯度带内破碎度先上升后下降，城市在2006-2016年扩张较快，其余梯度带破碎度逐年升高；空间演变上，居住地在圈层上的变化呈"L"型，未利用地呈"N"型，张掖市从中心城区到外围区域依次为绿洲城市区、绿洲农业区和自然景观区。（3）水平样带揭示了山地-绿洲-荒漠的用地变化，将张掖市分为4类区域，分别为绿洲城市区、绿洲农业区、荒漠区、山地区；西北-东南样带上景观破碎度年变化不规律，在空间上经过居民点波动变化；东北-西南样带研究期内景观水平指数经过居民点波动变化，其余范围内年变化较稳定，中心城区景观异质性较强。（4）人类围绕河流进行各种生产生活活动，将河流样带分为上中下三段，样带上段和下段景观指数年变化基本保持稳定，以未利用地为主，上段存在部分林地、草地；中段景观指数在空间上波动变化，景观类型以未利用地和耕地为主。 Abstract:The change of landscape pattern affects the regional ecological security and sustainable development. The study on the spatio-temporal change characteristics of urban landscape pattern has a certain guiding significance to the optimization of landscape pattern in arid areas. Based on the land use data of 1987, 1995, 2000, 2006, 2011 and 2016, the temporal and spatial evolution characteristics of landscape pattern in Zhangye City were studied by using landscape pattern index calculation method. The results showed that:(1) The unused land was the main landscape type in Zhangye City in 2016, and the maximum patch index and patch aggregation degree were the highest, followed by grassland and cultivated land, and the grassland patch number and density were the largest. (2) The landscape pattern of Zhangye City showed obviously regional differentiation characteristics, and the gradient zone of circle layer revealed the change of oasis-desert land. The fragmentation degree in the first gradient zone increased firstly and then decreased during the study period, and the Zhangye City expanded rapidly from 2006 to 2016, while the fragmentation degree in the rest gradient zones increased year by year. In terms of spatial evolution, the change of residential area on the circle layer is "L" shape, and the unused land is "N" shape. From the central area to the periphery area, Zhangye City was divided into oasis urban area, oasis agricultural area and natural landscape area successively. (3) The horizontal transect revealed the land use change of mountain, oasis and desert, and Zhangye City was divided into four regions:oasis urban area, oasis agricultural area, desert area and mountain area. The annual change of landscape fragmentation degree in northwest-southeast transect is irregular, and fluctuated through residential area in space. The landscape level index from the northeast to southwest transect fluctuated through residential areas during the study period, and the annual change was relatively stable in the remaining areas. The landscape heterogeneity of the central urban area was strong. (4) The river transect was divided into upper, middle and lower sections by human activities. The landscape index of the transect and the lower section remained stable, and the unused land was the main part, while the upper section had some woodland and grassland. The landscape index in the middle section fluctuated in space, and the landscape types were mainly unused land and cultivated land. 参考文献 相似文献 引证文献

Thermal Environment Effect of Landscape Ecological Pattern and Dynamic Analysis of Pattern Evolution

The obvious characteristics of urban thermal environment and heat island effect have brought a series of negative effects on urban ecosystem structure and residents' health. Scholars at home and abroad have conducted basic researches on urban thermal environment, but there is a lack of researches on areas with rapid urbanization and many interference factors. There are few researches on measures or suggestions to improve urban thermal environment and heat island effect from the perspective of ecological sustainable development. To this end, this paper conducts a study on thermal environment effect of landscape ecological pattern and dynamic analysis of pattern evolution. This paper, based on the radiative transfer equation method, carries out back calculation and back analysis on the parameters of urban surface temperature to obtain the dynamic characteristics of urban thermal ecological landscape pattern. By combining the obtained urban surface temperature with the landscape index, this paper analyzes the internal change of urban surface thermal ecological landscape pattern. Through the spatial characteristics of the barycenter of urban thermal environment effect, the expansion and development trend of urban thermal environment effect is revealed. Then based on Moran'sI coefficient, the whole spatial correlation of urban thermal environment effect and the degree of spatial aggregation in local areas are analyzed. Finally, the corresponding experimental results and analytical results are given in combination with the experiments.

Multi-Level Dynamic Analysis of Landscape Patterns of Chinese Megacities during the Period of 2016–2021 Based on a Spatiotemporal Land-Cover Classification Model Using High-Resolution Satellite Imagery: A Case Study of Beijing, China

In today’s accelerating urbanization process, timely and effective monitoring of land-cover dynamics, landscape pattern analysis, and evaluation of built-up urban areas (BUAs) have important research significance and practical value for the sustainable development, planning and management, and ecological protection of cities. High-spatial-resolution remote sensing (HRRS) images have the advantages of high-accuracy Earth observations, covering a large area, and having a short playback period, and they can objectively and accurately provide fine dynamic spatial information about the land cover in urban built-up areas. However, the complexity and comprehensiveness of the urban structure have led to a single-scale analysis method, which makes it difficult to accurately and comprehensively reflect the characteristics of the BUA landscape pattern. Therefore, in this study, a joint evaluation method for an urban land-cover spatiotemporal-mapping chain and multi-scale landscape pattern using high-resolution remote sensing imagery was developed. First, a pixel–object–knowledge model with temporal and spatial classifications was proposed for the spatiotemporal mapping of urban land cover. Based on this, a multi-scale district–BUA–city block–land cover type map of the city was established and a joint multi-scale evaluation index was constructed for the multi-scale dynamic analysis of the urban landscape pattern. The accuracies of the land cover in 2016 and 2021 were 91.9% and 90.4%, respectively, and the kappa coefficients were 0.90 and 0.88, respectively, indicating that the method can provide effective and reliable information for spatial mapping and landscape pattern analysis. In addition, the multi-scale analysis of the urban landscape pattern revealed that, during the period of 2016–2021, Beijing maintained the same high urbanization rate in the inner part of the city, while the outer part of the city kept expanding, which also reflects the validity and comprehensiveness of the analysis method developed in this study.

GIS-based Ecological Risk Assessment on Land Use In Chongqing City, China

Ecological risk assessment (ERA) is a process of predicting the possibility of harmful effects of environmental pollutants on an entire or part of the ecosystem, which is closely connected with the early human health risk assessment. A rational assessment of ecological risks in an urban area can provide great significance for urban landscape pattern optimization, urban ecological risk warning mechanism establishment, and urban ecological environment risk reduction. This study is based on GIS system to assess the ecological risk of land use in Chongqing in 2020, according to the basic theoretical framework and method system of ecological risk assessment. The main process is using remote sensing image data to construct the Ecological Risk Index (ERI) from the perspective of landscape patterns to reflect the potential impact of resource-based urban land use on the ecological environment. In addition, the ArcGIS spatial analysis method was used to evaluate Chongqing's ecological risk. As a result, high-risk area close to the water body just occupied a small part of Chongqing City (around 5%) and this area should be taken into protective measures urgently.

An analysis of modelling the ecological importance of modern agricultural landscaping

Landscape is an important part of urban ecosystem, and the assessment of landscape ecological importance is important to guide landscape design. The current ecological importance analysis mainly uses the comprehensive index relationship quantification to abstract the corresponding mathematical model, and the sample data interferes with the analysis results. To address the above-mentioned shortcomings, the ecological importance modeling analysis of modern urban landscape design is studied. Based on the calculation of modern urban landscape pattern index, the ecological importance index system of landscape design is established. Using the combination of hierarchical analysis and GIS technology, the index parameters are determined. Using metacellular automata, the ecological importance analysis model was constructed. The results of the case verification show that the constructed analysis model can demonstrate the changes of ecological importance of landscape design more accurately and effectively guide the landscape design.

Evaluation of Urban Spatial Structure from the Perspective of Socioeconomic Benefits Based on 3D Urban Landscape Measurements: A Case Study of Beijing, China

Urban spatial structures (USS) play an essential role in urbanization. Understanding the impact of USS patterns on their socioeconomic benefits is crucial to evaluating urban structure quality. Previous studies have, primarily, relied on statistical data and have significant temporal consistency and spatial accuracy limitations. Moreover, previous evaluation methods mainly determined the weight of indicators based on subjective assessments, such as the Delphi method, without integrating the actual socioeconomic benefits of complex urban systems. By measuring the two-dimensional (2D) urban functional landscape patterns and three-dimensional (3D) building forms of the city and considering the level of urban socioeconomic vitality as revealed by nighttime light intensity (NTLI), this study explores the influence of urban spatial structure on socioeconomic vitality. It provides a new perspective for evaluating the USS level. Furthermore, a comprehensive index, namely the Spatial Structure Socioeconomic Benefit Index (SSSBI), was constructed to quantify the socioeconomic benefits of USS. The results showed that (1) the impact of spatial structure on NTLI differs significantly with the distribution of urban functional landscape patterns and building forms. (2) The combined effect of any two spatial structure factors on NTLI was higher than the effect of each factor separately, indicating that multiple dimensions can improve urban spatial construction. (3) This study quantitatively extracts the characteristics of USS from multiple scales, which helps to find the optimal evaluation scale and build a scientific and objective evaluation model. The results showed that the USS assessment based on the SSSBI index is practical. This study could provide a reference for the government’s urban planning and land-use decisions.

Does the Spatial Pattern of Plants and Green Space Affect Air Pollutant Concentrations? Evidence from 37 Garden Cities in China.

Relevant studies have demonstrated that urban green spaces composed of various types of plants are able to alleviate the morbidity and mortality of respiratory diseases, by reducing air pollution levels. In order to explore the relationship between the spatial pattern of urban green spaces and air pollutant concentrations, this study takes 37 garden cities with subtropical monsoon climate in China as the research object and selects the urban air quality monitoring data and land use type data in 2019 to analyze the relationship between the spatial pattern and the air pollutant concentration through the landscape metrics model and spatial regression model. Moreover, the threshold effect of the impact of green space on air pollutant concentrations is estimated, as well. The results showed that the spatial pattern of urban green space was significantly correlated with the concentrations of PM2.5 (PM with aerodynamic diameters of 2.5 mmor less), NO2 (Nitrogen Dioxide), and SO2 (Sulfur dioxide) pollutants in the air, while the concentrations of PM10 (PM with aerodynamic diameters of 10 mmor less) pollutants were not significantly affected by the green space pattern. Among them, the patch shape index (LSI), patch density (PD) and patch proportion in landscape area (PLAND) of forest land can affect the concentration of PM2.5, NO2, and SO2, respectively. The PLAND, PD, and LSI of grassland and farmland can also have an additional impact on the concentration of SO2 pollutants. The study also found that there was a significant threshold effect within the impact mechanism of urban green space landscape pattern indicators (LSI, PD, PLAND) on the concentrations of PM2.5, NO2, and SO2 air pollutants. The results of this study not only clarified the impact mechanism of the spatial pattern of urban green space on air pollutant concentrations but also provided quantitative reference and scientific basis for the optimization and updating of urban green space to promote public health.

Improved Landscape Expansion Index and Its Application to Urban Growth in Urumqi

Automatic determination of quantitative parameters describing the pattern of urban expansion is extremely important for urban planning, urban management and civic resource configuration. Though the widely adopted LEI (landscape expansion index) has exhibited the potential to capture the evolution of urban landscape patterns using multi-temporal remote sensing data, erroneous determination still exists, especially for patches with special shapes due to the limited consideration of spatial relationships among patches. In this paper, we improve the identification of urban landscape expansion patterns with an enhancement of the topological relationship. We propose MCI (Mean patch Compactness Index) and AWCI (Area-Weighted Compactness Index) in terms of the moment of inertia shape index. The effectiveness of the improved approach in identifying types of expansion patches is theoretically demonstrated with a series of designed experiments. Further, we apply the proposed approaches to the analysis of urban expansion features and dynamics of urban compactness over Urumqi at various 5-year stages using available SUBAD-China data from 1990–2015. The results achieved by the theoretical experiments and case application show our approach effectively suppressed the effects induced by shapes of patches and buffer or envelope box parameters for the accurate identification of patch type. Moreover, the modified MCI and AWCI exhibited an improved potential in capturing the landscape scale compactness of urban dynamics. The investigated 25-year urban expansion of Urumqi is dominated by edge-expansion patches and supplemented by outlying growth, with opposite trends of increasing and decreasing, with a gradual decrease in landscape fragmentation. Our examination using the proposed MCI and AWCI indicates Urumqi was growing more compact in latter 15-year period compared with the first 10 years studied, with the primary urban patches tending to be compacted earlier than the entire urban setting. The historical transformation trajectories based on remote sensing data show a significant construction land gain—from 1.06% in 1990 to 6.96% in 2015—due to 289.16 km2 of recently established construction, accompanied by fast expansion northward, less dynamic expansion southward, and earlier extension in the westward direction than eastward. This work provides a possible means to improve the identification of patch expansion type and further understand the compactness of urban dynamics.

Urban Expansion Assessment Based on Optimal Granularity in the Huaihe River Basin of China

Determining the optimal granularity, which has often been ignored in the analysis of urban expansion and its landscape pattern, is the core problem in landscape ecology research. Here, we calculate the optimal granularities for differently sized cities in the Huaihe River Basin of China based on scale transformation and area loss evaluation. Accordingly, we construct a landscape index and urban land density function to analyze urban expansion and landscape pattern. The results can be summarized as follows. (1) Within the first scale domain of the landscape indices, the optimal granularities of Zhengzhou, Xuzhou, Yancheng, Xinyang, and Bozhou are 60 m, 50 m, 40 m, 40 m, and 40 m, respectively, which are the optimal units in the study of urban expansion. (2) The urban land density decreases from the urban center to the outskirts, the urban core of each city is more compact than the outskirts, and the land density curve parameter α of Zhengzhou is the largest at 4.693 and its urban core the most compact. (3) There are significant spatial and temporal differences in the urban land densities of differently sized cities. The urban land density functions of different cities are similar before 2000; after that, they are similar to the standard inverse S-shaped function and the land use density curve of large cities is closer to the standard inverse S-shaped function than that of small- and medium-sized cities. (4) Large cities have faster expansion, much larger land density curve parameter c than medium- and small-cities, stronger linkage development with surrounding areas, and a higher degree of urban centralization. Urban expansion compactness was influenced by urban locations and functions except for urban sizes. This study offers a method for identifying the optimal granularities for differently sized cities and also provides information for the decision-making efforts that concern the rapid urbanization in major grain-producing areas of China.

Spatiotemporal Changes in The Urban Landscape Pattern and Driving Forces of LUCC Characteristics in The Urban Agglomeration on The Northern Slope of The Tianshan Mountains from 1995 to 2018

Analyses of landscape patterns, analyses of land-use/land-cover evolution characteristics, and a driving force analysis during the expansion of urban agglomerations can assist urban agglomerations in solving ecological and environmental problems; moreover, these tools can provide a reference for urban land-use structure optimization and urban landscape planning. In this study, the rapid urbanization and urban agglomeration of small- and medium-sized cities were evaluated; specifically, the urban agglomeration of the northern slopes of the Tianshan Mountains (UANSTM) was assessed. Using multi-period (1995, 2000, 2005, 2010, 2015, 2018) land-use data and statistical yearbook data, we calculated the landscape index and comprehensive land-use degree index using the Moran index and geographic probe methods. We studied the expansion patterns and spatial distribution patterns of urban land and quantitatively explored the influence mechanisms of natural and socioeconomic factors on the degree of land use to clarify the characteristics and driving forces of land-use evolution. The results show the following: the area of urban land continued to increase between 1995 and 2018; the dominance of the landscape indexes within each time period changed with urban development; and intra-urban landscape heterogeneity is gradually increasing. In terms of the spatial and temporal distribution of the degree of land use, the expansion of urban agglomeration is centered on the city of Urumqi, spreading towards the cities of Changji and Shihezi; the rest of the counties and cities are fast urban-expansion zones. Under the influence of multiple source factors, the expansion of the UANSTM depends on the distribution of oases, which is mainly influenced by the distribution of vegetation and the density of the river network and can only rely on the ecological carrying capacity of oases for production and life. The results of the study can provide a basis for decision-making processes surrounding the future layout of the UANSTM ecological environment.

Exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on GTWR and MGWR: The case of Nanjing, China

Landscape pattern significantly impacts habitat quality, especially in cities undergoing rapid urbanization, where landscape patterns are changing dramatically. However, the spatial and temporal driving mechanisms of landscape pattern on habitat quality are still unclear, and the proposed methods of Geographically and Temporally Weighted Regression (GTWR) and Multiscale Geographic Weighted Regression (MGWR) provide possibilities for the exploration of these mechanisms. This study was conducted in Nanjing from 2001 to 2020. Landscape pattern indices indicating aggregation, connectivity, diversity and compactness were calculated using Fragstats from 2001 to 2020. The habitat quality was computed using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. By combining two new spatial measurement models, GTWR and MGWR, the spatial and temporal driving mechanisms of landscape patterns on habitat quality were explored. The results show that (1) as Nanjing’s land under construction has expanded, habitat quality has decreased significantly, and the overall landscape pattern has fluctuated drastically. (2) GTWR and MGWR are well-suited to such analysis and provide important insights. (3) Overall, aggregation and compactness were negatively associated with habitat quality in areas of low-quality habitat. Increased connectivity on low habitat substrates had a positive effect on habitat. The increase of diversity in proximity had a positive effect on habitat, while the opposite was true in high habitat zones. (4) As the urbanization level increases, the negative effects of aggregation expand, as do the positive effects of connectivity and diversity. (5) The extent of influence of landscape pattern effects are ranked from largest to smallest: compactness, diversity, connectivity, and aggregation, while the intensity of effects is reversed. Based on these findings, a reference point for urban planners is provided to plan urban landscape patterns in a sustainable and rational manner. It also provides a new means of integrating GTWR and MGWR into the study of landscape ecology.

Analysis of land use change on urban landscape patterns in Northwest China: A case study of Xi’an city

Abstract Xi’an, an inland city in Northwest China, borders the Qinling Mountains to the south and Wei River to the north. This city is rich in biodiversity and occupies a unique position in China. In the past few decades, human activities have led to great changes in land use in Xi’an city, and the ecosystem has experienced an accelerated fragmentation process. This study analyzed the degree of land use change and landscape fragmentation in the region. Land use data in 1990, 2000, 2010, and 2018 were used to evaluate the effects of land use change on the landscape pattern in Xi’an city at different scales using mathematical models and landscape indices. Results show that from 1990 to 2018, built-up land expanded the most, from 7.34 to 13.51%. Cropland decreased the most, from 40.12 to 29.81%. Overall, the fragmentation degree of cropland patches decreased, and the fragmentation degree of built-up land patches increased. The landscape patterns of different districts and counties show different change directions. The results can provide necessary information for land use planning and land resource allocation in inland cities in Northwest China.

Is There a Spatial Relationship between Urban Landscape Pattern and Habitat Quality? Implication for Landscape Planning of the Yellow River Basin.

The extent to which landscape spatial patterns can impact the dynamics and distribution of biodiversity is a key geography and ecology issue. However, few previous studies have quantitatively analyzed the spatial relationship between the landscape pattern and habitat quality from a simulation perspective. In this study, the landscape pattern in 2031 was simulated using a patch-generating simulation (PLUS) model for the Yellow River Basin. Then, the landscape pattern index and habitat quality from 2005 to 2031 were evaluated using the Fragstats 4.2 and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. Furthermore, we analyzed the spatial distribution characteristics and spatial spillover effects of habitat quality using spatial autocorrelation analysis. Finally, the spatial association between the landscape pattern index and habitat quality was quantitatively revealed based on a spatial lag model. The simulation results showed that: (1) from 2005 to 2031, the landscape of the Yellow River Basin would be dominated by grassland and unused land, and the areas of construction land and water body will increase significantly, while the area of grassland will decrease; (2) patch density (PD) and Shannon’s diversity index (SHDI) show significant increases, while edge density (ED), landscape shape index (LSI), mean patch area (AREA_MN), and contagion index (CONTAG) decrease; (3) from 2005 to 2031, habitat quality would decrease. The high-value areas of habitat quality are mainly distributed in the upper reaches of the Yellow River Basin, and the low-value areas are distributed in the lower reaches. Meanwhile, both habitat quality and its change rate present positive spatial autocorrelation; and (4) the spatial relationships of habitat quality with PD and COHESION are negative, while ED and LSI have positive impacts on habitat quality. Specifically, landscape fragmentation caused by high PD has a dominant negative influence on habitat quality. Therefore, this study can help decision makers manage future landscape patterns and develop ecological conservation policy in the Yellow River Basin.

Indexing coordination of ecosystem and urban economic vitality in coastal cities: An observation in yangtze river delta

Advanced geographic technologies provide an opportunity to understand the urban forest landscape and guide the governance of the urban ecosystem. However, only few studies stressed the importance of data techniques in understanding urban sustainability, especially urban forest landscape. Therefore, this study makes an analysis of urban forest resources in a city of Yangtze River Delta with the help of multi-source data techniques and further data analysis of different forest landscape pattern indices in the study area with the help of SPSS (Statistical Product and Service Solutions). The following conclusions are drawn: 1) According to the visual analysis, the spatial distribution of forest patches in the study area has a great difference. 2) All the seven landscape pattern indices are positively correlated with the distribution density of POI (Point of Interest), which represents the urban economic vitality. The correlation coefficients are NP (R2 = 0.3063), PD (R2 = 0.0079), ED (R2 = 0.3955), AREA (R2 = 0.5408), CONTIG (R2 = 0.0323), PAFRAC (R2 = 0.3662) and AI (R2 = 0.2014), respectively. This indicates that the higher the economic vitality is, the more fragmented and complex the urban forest patches are. 3) According to the geographically weighted regression model, the goodness of fit between the spatial distribution density of POI and NP, PD, ED, and AI reaches 0.804, 0.771, 0.634, and 0.619, respectively, and the explanatory power of the model is more than twice that of the corresponding linear regression model. The data illustrates that the correlation between economic vitality and urban forest landscape pattern indices has significant spatial heterogeneity.

Three-Dimensional Landscape Pattern Characteristics of Land Function Zones and Their Influence on PM2.5 Based on LUR Model in the Central Urban Area of Nanchang City, China.

China’s rapid urbanization and industrialization process has triggered serious air pollution. As a main air pollutant, PM2.5 is affected not only by meteorological conditions, but also by land use in urban area. The impacts of urban landscape on PM2.5 become more complicated from a three-dimensional (3D) and land function zone point of view. Taking the urban area of Nanchang city, China, as a case and, on the basis of the identification of urban land function zones, this study firstly constructed a three-dimensional landscape index system to express the characteristics of 3D landscape pattern. Then, the land-use regression (LUR) model was applied to simulate PM2.5 distribution with high precision, and a geographically weighted regression model was established. The results are as follows: (1) the constructed 3D landscape indices could reflect the 3D characteristics of urban landscape, and the overall 3D landscape indices of different urban land function zones were significantly different; (2) the effects of 3D landscape spatial pattern on PM2.5 varied significantly with land function zone type; (3) the effects of 3D characteristics of landscapes on PM2.5 in different land function zones are expressed in different ways and exhibit a significant spatial heterogeneity. This study provides a new idea for reducing air pollution by optimizing the urban landscape pattern.

Investigating the impact of urban landscape composition and configuration on PM2.5 concentration under the LCZ scheme: A case study in Nanchang, China

Urban landscape pattern alters the distribution of fine particulate matter (PM2.5) by affecting “source and sink” directly and microclimate indirectly. Most previous works investigate their relationship by landscape metrics that are difficult to be applied in sustainable urban planning. This study innovatively linked PM2.5 with the local climate zone (LCZ) which is a visible landscape pattern classification framework at urban scale. Impacts of urban landscape composition and configuration on PM2.5 were evaluated through PM2.5 differences analyzes of inter-LCZ categories and intra-built category and correlation analysis between PM2.5 and landscape metrics adopted in LCZ scheme. Results show that significant PM2.5 differences exist both inter-LCZ categories and intra-built category, implying LCZ scheme can reflect the urban spatial variation of PM2.5. The natural category always has a lower PM2.5 concentration than the built category. PM2.5 concentrations “compact > open” and “high-rise > mid-rise > low-rise” in built category generally exist throughout the year. Height of roughness elements (HRE) and aspect ratio (AR) show the most significant correlation with PM2.5. This study provides a novel perspective investigating the impact of urban landscape pattern on PM2.5 and scientific guidance for sustainable urban planning in regard to air pollution mitigation.