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The spatiotemporal patterns of urban expansion have attracted worldwide attention and have been generalized into several prevalent hypotheses, such as the diffusion–coalescence hypothesis and the three-growth-type hypothesis. Although many studies have examined the applicability of these hypotheses, long-term research and evidence are still lacking. This study incorporated a compiled dataset of multisource remote sensing images and historical maps covering nine snapshots of the urban built-up area from 1914 to 2018 to monitor the urban expansion process in Hangzhou, China. A fractal analysis of the area–radius relationship was employed for areal demarcation to explore the heterogenous patterns across different intra-city spatial extents. The results show that (1) Hangzhou has experienced a turbulent period of primitive urbanization in the pre-reform era and a consecutive period of market-oriented urbanization after the economic reform; (2) the urban expansion pattern characterized by landscape metrics demonstrates the existence of multiple alternations between diffusion and coalescence phases with peculiarities across different intra-city spatial extents; (3) the analysis of urban growth types documents a consistent predominance of edge-expansion with wax and wane between infilling and leapfrogging; and (4) institutional reform, industrial development, and administrative division adjustment are the main drivers of urban expansion in Hangzhou. Our findings suggest that effective planning policies need to be raised to curb urban sprawl. Differentiated planning strategies should be proposed to accommodate unique conditions in different urban subregions. The integrated-analysis approach based on multisource remote sensing images and historical maps establishes a feasible pathway for long-term urban research. [ABSTRACT FROM AUTHOR]

The ecological restoration of territorial space emphasizes the synergy between ecology and social development. On this basis, we used landscape index analysis methods to explore the spatiotemporal evolution of landscape patterns in urban areas on a district scale. Then, we used multiple regression analysis to explore the driving factors behind this evolution. The results showed the following: (1) Landscape compositions have changed significantly. The growth rate of construction land in the main districts was about three times that in the urban area. (2) There were differences in the characteristics of landscape pattern evolution. Arable land is becoming more fragmented as construction land expands outward. The shapes of public green spaces, arable land, and woodlands tend to be simple and regular. The degree of both urban sprawl and agglomeration decreased in the urban area and the main districts. Meanwhile, landscape separation first decreased and then increased, and landscape diversity increased. (3) Population growth, industrial development, changes in industrial structure, and real estate development are the main driving factors of landscape pattern evolution. Based on this, this study puts forward some suggestions for landscape pattern optimization, which is significant for ecological restoration planning and promotion. [ABSTRACT FROM AUTHOR]

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• The relationship between landscape patterns and SUHII were detected by SMLR model. • The SUHII in 2030 in Hangzhou were predicted using a RF model. • Implications for mitigating SUHI through landscape optimization were suggested. During rapid urbanization, global land use and land cover change drastically, leading to increasingly severe problems in the urban environment. Among them, the urban heat island effect has attracted much attention owing to its magnification effect on climate change and its negative role in urban livability and sustainable development. In this context, predicting the future surface urban heat island intensity (SUHII) and distribution is important in dealing with the urban thermal environment. In this study, we conducted a prediction of SUHII using a random forest model based on future landscape patterns. According to the results, the built-up area is expected to grow to 3740.67 km2, and the non-forest green space (GS2) is estimated to decrease by 1130.96 km2 by 2030. In the context of urban expansion, the area with SUHII of higher than 5 °C will increase significantly, showing a more concentrated spatial distribution, while the region with SUHII of below −2.5 °C will decrease in coverage. In addition, our results showed that the scattered built-up areas and GS1, as well as concentrated GS2, will contribute to reducing SUHII. The results are expected to help policymakers and urban planners to design reasonable measures for achieving sustainable urban development. [ABSTRACT FROM AUTHOR]

Abstract: Dynamics of soil sealing and soil landscape patterns under rapid urbanization were qualified in the Urban Agglomeration around Hangzhou Bay (UAHB), China. Rapid population growth, economic development, and settlement sprawl were identified from 1994 to 2009. Such accelerating urbanization resulted in considerable soil sealing. For the entire region, percentage of sealed soils increased from 2.7% in 1994 to 4.7% in 2003 and to 8.7% in 2009. Paddy soils, especially those of the highest quality, were the first victims. Soil landscapes, at the regional scale, became more fragmented and irregular, but less dominated, diverse and connected as urbanization intensified. Spatial regression uncovered the diverging relationships between landscape metrics with urbanization indicators and measurement period. The dynamics of soil sealing and soil landscape patterns not only reflected common tendencies in China, but represented a global process. Our study provided a practical methodological framework, by integrating remote sensing, geographical information systems, landscape metrics and spatial regression, for monitoring the impacts of urbanization on soil resources. [Copyright &y& Elsevier]

Abstract: This study employed geographically weighted regression (GWR), a local spatial modeling approach, to characterize the local varying response of paddy soils to urbanization at the landscape scale in the urban agglomeration around Hangzhou Bay, China. Spatial non-stationary and scale-dependent relationships between three geographical urbanization indices (the common urbanization intensity index, distance to road corridors and distance to urban centers) and four spatial metrics depicting paddy soil landscape patterns (total area, edge density, aggregation index, and perimeter area ratio distribution) were captured at two block scales (4 km × 4 km and 7 km × 7 km) because the predictive ability of GWR and the nature and strength of the identified relationships all varied significantly in space and scale. Moreover, GWR models have achieved better performance than their corresponding global ordinary least squares (OLS) models given their greater ability to (1) describe data (higher adjusted R 2 and lower Akaike Information Criterion values) and (2) address spatial autocorrelation in model residuals. This study highlighted scale effects when applying GWR. Both bandwidth and block size can impact the predictive ability of GWR as well as estimated parameters for GWR analysis. This study demonstrates a novel joint application of GWR and associated metrics in applied geography. [Copyright &y& Elsevier]

The rapid urbanization worldwide has brought various environmental problems. The urban heat island (UHI) phenomenon is one of the most concerning issues because of its strong relation with daily lives. Water bodies are generally considered a vital resource to relieve the UHI. In this context, it is critical to develop a method for measuring the cooling effect and scale of water bodies in urban areas. In this study, West Lake and Xuanwu Lake, two famous natural inner-city lakes, are selected as the measuring targets. The scatter plot and multiple linear regression model were employed to detect the relationship between the distance to the lake and land surface temperature based on Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Sentinel-2 data. The results show that West Lake and Xuanwu Lake massively reduced the land surface temperature within a few hundred meters (471 m for West Lake and 336 m for Xuanwu Lake) and have potential cooling effects within thousands of meters (2900 m for West Lake and 3700 m for Xuanwu Lake). The results provide insights for urban planners to manage tradeoffs between the large lake design in urban areas and the cooling effect demands. [ABSTRACT FROM AUTHOR]

• Spatiotemporal pattern of habitat quality in Hangzhou was assessed by InVEST model. • Spatial distribution of habitat quality showed positive spatial auto-correlation. • Negative impact of urbanization on habitat quality varied with time and space. • Impacts of landscape pattern on habitat quality differed in magnitude and direction. China has experienced the most serious habitat degradation, especially in fast-growing metropolis cities. Although increasing attentions have been brought to this issue, we still lack the understanding of the quantitative impacts of urbanization and landscape pattern on habitats. In this study, we used the "Integrated Valuation of Environmental Services and Trade-off" (InVEST) model to evaluate the habitat quality in Hangzhou city. We further employed spatial auto-correlation to analyze its spatiotemporal pattern variation characteristics. Finally, the ordinary least squares (OLS) and geographically weighted regression (GWR) models were used to explore the impacts of urbanization and landscape pattern change on habitat quality. The results show that the habitat quality index of Hangzhou decreased from 0.608 to 0.577 during 2004–2015, and these areas mainly located around the suburb decreased significantly. The spatial distribution of habitat quality showed significantly positive spatial auto-correlation, and the overall spatial auto-correlation degree of the habitat quality increased during this time. Rapid urbanization has significant negative effects on habitat quality in various areas, while the magnitude and direction of the impacts of landscape pattern on habitat quality differed in time and space. These results provide decision-making criteria for formulating differential urban development policies and landscape management measures for urban ecological sustainability. [ABSTRACT FROM AUTHOR]