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Juntao Tan
School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China

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Research article
Published: 27 July 2020 in Complexity
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Under the trend of rapid urbanization, the urban heat island (UHI) effect has become a hot issue for scholars to study. In order to better alleviate UHI effect, it is important to understand the effect of landuse/landcover (LULC) and landscape patterns on the urban thermal environment from perspective of landscape ecology. This research aims to quantitatively investigate the effect of LULC landscape patterns on UHI effects more accurately based on a landscape metrics analysis. In addition, we also explore the complex relationship between land surface temperature (LST) and vegetation cover. Taking Zhengzhou City of China as a case study, an integrated method which includes the geographic information system (GIS), remote-sensing (RS) technology, and landscape metrics was employed to facilitate the analysis. Landsat data (2000–2014) were applied to investigate the spatiotemporal evolution patterns of LST and LULC. The results indicated that the mean LST value increased by 2.32°C between 2000 and 2014. The rise of LST was consistent with the trend of rapid urbanization in Zhengzhou City, which resulted in sharp increases in impervious surfaces (IS) and substantial losses of vegetation cover. Furthermore, the investigation of LST and vegetation cover demonstrated that fractional vegetation cover (FVC) had a stronger negative effect on LST than normalized differential vegetation index (NDVI). In addition, LST was obviously correlated with LULC landscape patterns, and both landscape composition and spatial configuration affected UHI effects to varying degrees. This study not only illustrates a feasible way to investigate the relationship between LULC and urban thermal environment but also suggests some important measures to improve urban planning to reduce UHI effects for sustainable development.

ACS Style

Hongbo Zhao; Juntao Tan; Zhibin Ren; Zheye Wang. Spatiotemporal Characteristics of Urban Surface Temperature and Its Relationship with Landscape Metrics and Vegetation Cover in Rapid Urbanization Region. Complexity 2020, 2020, 1 -12.

AMA Style

Hongbo Zhao, Juntao Tan, Zhibin Ren, Zheye Wang. Spatiotemporal Characteristics of Urban Surface Temperature and Its Relationship with Landscape Metrics and Vegetation Cover in Rapid Urbanization Region. Complexity. 2020; 2020 ():1-12.

Chicago/Turabian Style

Hongbo Zhao; Juntao Tan; Zhibin Ren; Zheye Wang. 2020. "Spatiotemporal Characteristics of Urban Surface Temperature and Its Relationship with Landscape Metrics and Vegetation Cover in Rapid Urbanization Region." Complexity 2020, no. : 1-12.

Article
Published: 27 April 2020 in Chinese Geographical Science
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This study analyzed the spatial-temporal heterogeneity of green development efficiency and its influencing factors in the growing Xuzhou Metropolitan Area for the period 2000-2015. The slacks-based measure (SBM) model, spatial autocorrelation, and the geographically weighted regression (GWR) model were used to conduct the analysis. The conclusions were as follows: first, the overall efficiency of green development of the Xuzhou Metropolitan Area decreased, the regional differences and spatial agglomeration shrunk and differences within the region were the main contributors to the regional differences of green development efficiency. Second, the counties with high-efficiency green development were distributed along the coast, and along the routes of the Beijing-Shanghai and the Eastern Longhai railways. A developing axis of the high-efficiency counties was the main feature of the spatial pattern for green development efficiency. Third, regarding spatial correlation and green development efficiency, the High-High type counties in the Xuzhou Metropolitan Area formed a centralized distribution corridor along the inter-provincial border areas of Henan and Jiangsu, whereas the Low-Low type counties were concentrated in the external, marginal parts of the metropolitan area. Fourth, the major factors (ranked in decreasing order of impact) influencing green development efficiency were innovation, government regulations, the economic development level, energy consumption, and industrial structure. These factors exerted their influence to varying extents; the influence of the same factor had different effects in different regions and obvious spatial differences were observed for the different regions.

ACS Style

Fangdao Qiu; Yang Chen; Juntao Tan; Jibin Liu; Ziyan Zheng; Xinlin Zhang. Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area. Chinese Geographical Science 2020, 30, 352 -365.

AMA Style

Fangdao Qiu, Yang Chen, Juntao Tan, Jibin Liu, Ziyan Zheng, Xinlin Zhang. Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area. Chinese Geographical Science. 2020; 30 (2):352-365.

Chicago/Turabian Style

Fangdao Qiu; Yang Chen; Juntao Tan; Jibin Liu; Ziyan Zheng; Xinlin Zhang. 2020. "Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area." Chinese Geographical Science 30, no. 2: 352-365.

Original article
Published: 06 December 2019 in Growth and Change
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Resource‐based cities (RBCs) whose economies depend primarily on exploiting and processing natural resources usually have rigid, singular, and low‐end industrial structures, which often cripples their ability to cope with external disturbances such as international resource price fluctuations and economic downturns. This paper quantitatively analyzes the economic resilience of RBCs in China in terms of resistance and recoverability during the Asian financial crisis and the global financial crisis. Furthermore, it identifies the main factors affecting resilience. There are four main findings: First, RBCs were quickly and negatively impacted by the Asian financial crisis, which suggests that economic resistance was generally low during this period. In the recovery period, while the rate of recovery was slow at the beginning, economic recoverability improved after 2002. Economic resistance and recoverability were found to have a strong negative correlation. Second, at the beginning of the global financial crisis, the economic resistance of RBCs was generally high. However, after 2012, the number of cities that were severely affected by the economic crisis increased rapidly. Third, economic resistance varied across different types of RBCs. Coal‐based and forestry‐based cities had lower economic resistance, while oil & gas‐based cities were more resistant. RBCs in the Eastern region generally had low economic resistance, while the economic resilience of recessionary cities was also low. Finally, while factors affecting the economic resilience varied across the two economic cycles, we found that economic development, labor conditions and, most of all, the industrial structure had a statistically significant negative effect on economic resilience.

ACS Style

Juntao Tan; Kevin Lo; Fangdao Qiu; Xinlin Zhang; Hongbo Zhao. Regional economic resilience of resource‐based cities and influential factors during economic crises in China. Growth and Change 2019, 51, 362 -381.

AMA Style

Juntao Tan, Kevin Lo, Fangdao Qiu, Xinlin Zhang, Hongbo Zhao. Regional economic resilience of resource‐based cities and influential factors during economic crises in China. Growth and Change. 2019; 51 (1):362-381.

Chicago/Turabian Style

Juntao Tan; Kevin Lo; Fangdao Qiu; Xinlin Zhang; Hongbo Zhao. 2019. "Regional economic resilience of resource‐based cities and influential factors during economic crises in China." Growth and Change 51, no. 1: 362-381.

Journal article
Published: 04 March 2019 in Sustainability
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Economic polarization is a special manifestation of economic disparity which intensifies the gap between the rich and the poor in a region and brings about a series of social problems. Though more and more scholars are studying the phenomenon of economic polarization, there are few studies on polarization level division and early warning analysis in the existing literature. The main purpose of this paper is to propose a standard for rationally dividing the level of economic polarization. This paper firstly analyzes the current situation of economic polarization by using the economic data of 54 counties and cities in Jiangsu Province from 2000 to 2016 and secondly predicts the economic polarization level of Jiangsu Province from 2017 to 2015 through the grey model. We find that, according to the classification criteria of polarization levels, the phenomenon of economic polarization in Jiangsu Province is both not as serious as expected and at a moderate level of alertness. The results of this study can provide important reference value for the coordinated development of Jiangsu Province.

ACS Style

Chen Zou; Xiangjun Ou; Juntao Tan. Temporal and Spatial Characteristics and Early Warning Analysis of Economic Polarization Evolution: A Case Study of Jiangsu Province in China. Sustainability 2019, 11, 1339 .

AMA Style

Chen Zou, Xiangjun Ou, Juntao Tan. Temporal and Spatial Characteristics and Early Warning Analysis of Economic Polarization Evolution: A Case Study of Jiangsu Province in China. Sustainability. 2019; 11 (5):1339.

Chicago/Turabian Style

Chen Zou; Xiangjun Ou; Juntao Tan. 2019. "Temporal and Spatial Characteristics and Early Warning Analysis of Economic Polarization Evolution: A Case Study of Jiangsu Province in China." Sustainability 11, no. 5: 1339.

Journal article
Published: 29 June 2018 in Sustainability
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Understanding the spatial distribution of land surface temperature (LST) and its impact factors is crucial for mitigating urban heat island effect. However, few studies have quantitatively investigated the spatial non-stationarity and spatial scale effects of the relationships between LST and its impact factors at multi-scales. The main purposes of this study are as follows: (1) to estimate the spatial distributions of urban heat island (UHI) intensity by using hot spots analysis and (2) to explore the spatial non-stationarity and scale effects of the relationships between LST and related impact factors at multiple resolutions (30–1200 m) and to find appropriate scales for illuminating the relationships in a plain city. Based on the LST retrieved from Landsat 8 OLI/TIRS images, the Geographically-Weighted Regression (GWR) model is used to explore the scale effects of the relationships in Zhengzhou City between LST and six driving indicators: The Fractional Vegetation Cover (FVC), the Impervious Surface (IS), the Population Density (PD), the Fossil-fuel CO2 Emission data (FFCOE), the Shannon Diversity Index (SHDI) and the Perimeter-area Fractal Dimension (PAFRAC),which indicate the vegetation abundance, built-up, social-ecological variables and the diversity and shape complexity of land cover types. Our findings showed that the spatial patterns of LST show statistically significant hot spot zones in the center of the study area, partly extending to the western and southern industrial areas, indicating that the intensity of the urban heat island is significantly spatial clustering in Zhengzhou City. In addition, compared with the Ordinary Least Squares (OLS) model, the GWR model has a better ability to characterize spatial non-stationarity and analyze the relationships between the LST and its impact factors by considering the space-varying relationships of different variables, especially at the fine spatial scales (30–480 m). However, the strength of GWR model has become relatively weak with the increase of spatial scales (720–1200 m). This reveals that the GWR model is recommended to be applied in the analysis of UHI problems and related impact factors at scales finer than 480 m in the plain city. If the spatial scale is coarser than 720 m, both OLS and GWR models are suitable for illustrating the correct relationships between UHI effect and its influence factors in the plain city due to their undifferentiated performance. These findings can provide valuable information for urban planners and researchers to select appropriate models and spatial scales seeking to mitigate urban thermal environment effect.

ACS Style

Hongbo Zhao; Zhibin Ren; Juntao Tan. The Spatial Patterns of Land Surface Temperature and Its Impact Factors: Spatial Non-Stationarity and Scale Effects Based on a Geographically-Weighted Regression Model. Sustainability 2018, 10, 2242 .

AMA Style

Hongbo Zhao, Zhibin Ren, Juntao Tan. The Spatial Patterns of Land Surface Temperature and Its Impact Factors: Spatial Non-Stationarity and Scale Effects Based on a Geographically-Weighted Regression Model. Sustainability. 2018; 10 (7):2242.

Chicago/Turabian Style

Hongbo Zhao; Zhibin Ren; Juntao Tan. 2018. "The Spatial Patterns of Land Surface Temperature and Its Impact Factors: Spatial Non-Stationarity and Scale Effects Based on a Geographically-Weighted Regression Model." Sustainability 10, no. 7: 2242.

Journal article
Published: 30 November 2017 in Sustainability
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This paper quantitatively analyzes the economic resilience of resource-based cities (RBCs) in Northeast China in terms of resistance and recoverability during two economic crises: the Asian financial crisis and the global financial crisis. Moreover, it analyzes the main factors that affected regional resilience. There are three main findings. First, the RBCs in general demonstrated poor resistance during both recessions, but there were variations among the different types of RBCs. Petroleum and metal cities demonstrated the most resistance, whereas coal cities performed the worst. Second, the influential factors affecting economic resilience varied across the two economic cycles, but location advantage, research and development (R and D) intensity, foreign trade dependence ratio, and supporting policies had positive effects on resilience during both economic cycles, while the proportion of employed persons in resource industries had a negative effect. Industrial diversity had a weak and ambiguous effect on resilience. Third, the secondary industry was more resilient during the Asian financial crisis, but the tertiary industry was more resilient during the global financial crisis. This shift may be attributed to both the nature of the crises and the strength of the sectors at the time of the crises.

ACS Style

Juntao Tan; Kevin Lo; Fangdao Qiu; Wenxin Liu; Jing Li; Pingyu Zhang. Regional Economic Resilience: Resistance and Recoverability of Resource-Based Cities during Economic Crises in Northeast China. Sustainability 2017, 9, 2136 .

AMA Style

Juntao Tan, Kevin Lo, Fangdao Qiu, Wenxin Liu, Jing Li, Pingyu Zhang. Regional Economic Resilience: Resistance and Recoverability of Resource-Based Cities during Economic Crises in Northeast China. Sustainability. 2017; 9 (12):2136.

Chicago/Turabian Style

Juntao Tan; Kevin Lo; Fangdao Qiu; Wenxin Liu; Jing Li; Pingyu Zhang. 2017. "Regional Economic Resilience: Resistance and Recoverability of Resource-Based Cities during Economic Crises in Northeast China." Sustainability 9, no. 12: 2136.