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Wenze Yue
Department of Land Management, Zhejiang University, 12377 Hangzhou, Zhejiang, China

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Journal article
Published: 09 July 2021 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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The urban heat island (UHI) phenomenon, arising from rapid urbanization, has become a crucial research topic across various fields due to its adverse impacts on the ecological environment and human well-being. This study investigated the spatiotemporal patterns of summer UHI from 2001 to 2018 in Beijing-Tianjin-Hebei (BTH) urban agglomeration, and also examined the influence of natural and social factors on summer UHI by using the spatial regression model and ordinary regression model. We find that the mean summer UHI intensity in August was the highest at 0.76, followed by July and June (0.57 and 0.08, respectively). The results of spatiotemporal trend analysis reveal that the summer UHI of more than one-third of research districts and counties (68 of 200) have the significant increasing trends. The largest significant increasing trend was observed in Dongli District, Tianjin (0.17/year). Meanwhile, the summer UHI exhibited an apparent spatial pattern. Most of the high UHIs were dispersedly located in the southeast plain area, while low UHIs were mainly congregated in the northwest mountain area. For the relationships between summer UHI and influencing factors, different models have different the goodness of fit. Compared with the ordinary regression model, the spatial regression model performed better. And the optimal model indicated that the proportion of impervious surface and average temperature should take lead role for the summer UHI. The findings are of great help for understanding the features of summer UHI dynamic and provide a theoretical basis for optimizing urban agglomeration planning.

ACS Style

Li Hou; Wenze Yue; Xue Liu. Spatiotemporal patterns and drivers of summer heat island in Beijing-Tianjin-Hebei Urban Agglomeration, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021, PP, 1 -1.

AMA Style

Li Hou, Wenze Yue, Xue Liu. Spatiotemporal patterns and drivers of summer heat island in Beijing-Tianjin-Hebei Urban Agglomeration, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021; PP (99):1-1.

Chicago/Turabian Style

Li Hou; Wenze Yue; Xue Liu. 2021. "Spatiotemporal patterns and drivers of summer heat island in Beijing-Tianjin-Hebei Urban Agglomeration, China." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing PP, no. 99: 1-1.

Journal article
Published: 07 June 2021 in Land
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There is growing concern about the consequences of future urban expansion on carbon storage as our planet experiences rapid urbanization. While an increasing body of literature was focused on quantifying the carbon storage impact of future urban expansion across the globe, rare attempts were made from the comparative perspective on the same scale, particularly in Central Asia. In this study, Central Asian capitals, namely Ashkhabad, Bishkek, Dushanbe, Nur Sultan, and Tashkent, were used as cases. According to the potential impacts of BRI (Belt and Road Initiative) on urban expansion, baseline development scenario (BDS), cropland protection scenario (CPS), and ecological protection scenario (EPS) were defined. We then simulated the carbon storage impacts of urban expansion from 2019 to 2029 by using Google Earth Engine, the Future Land Use Simulation model, and the Integrated Valuation of Environmental Services and Tradeoffs model. We further explored the drivers for carbon storage impacts of future urban expansion in five capitals. The results reveal that Nur Sultan will experience carbon storage growth from 2019 to 2029 under all scenarios, while Ashkhabad, Bishkek, Dushanbe, and Tashkent will show a decreasing tendency. EPS and CPS will preserve the most carbon storage for Nur Sultan and the other four cities, respectively. The negative impact of future urban expansion on carbon storage will be evident in Ashkhabad, Bishkek, Dushanbe, and Tashkent, which will be relatively inapparent in Nur Sultan. The potential drivers for carbon storage consequences of future urban expansion include agricultural development in Bishkek, Dushanbe, and Tashkent, desert city development in Ashkhabad, and prioritized development of the central city and green development in Nur Sultan. We suggest that future urban development strategies for five capitals should be on the basis of differentiated characteristics and drivers for the carbon storage impacts of future urban expansion.

ACS Style

Yang Chen; Wenze Yue; Xue Liu; Linlin Zhang; Ye’An Chen. Multi-Scenario Simulation for the Consequence of Urban Expansion on Carbon Storage: A Comparative Study in Central Asian Republics. Land 2021, 10, 608 .

AMA Style

Yang Chen, Wenze Yue, Xue Liu, Linlin Zhang, Ye’An Chen. Multi-Scenario Simulation for the Consequence of Urban Expansion on Carbon Storage: A Comparative Study in Central Asian Republics. Land. 2021; 10 (6):608.

Chicago/Turabian Style

Yang Chen; Wenze Yue; Xue Liu; Linlin Zhang; Ye’An Chen. 2021. "Multi-Scenario Simulation for the Consequence of Urban Expansion on Carbon Storage: A Comparative Study in Central Asian Republics." Land 10, no. 6: 608.

Journal article
Published: 04 June 2021 in Sustainable Cities and Society
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This article aims to examine the pathways of urban spatial forms in mitigating urban heat island (UHI) intensity across urban areas in different seasons. By investigating the case of Wuhan, we quantified urban spatial form (USF) factors concerning land use, land cover, and building-group morphology and the land surface temperatures (LST) in summer, autumn and winter of 2,357 block units. The seasonal relationships between USF and LST are explored at the large scale of the whole study area and different zones of block units categorized by floor area ratio. The results suggest that relationships between USF and LST vary spatially and temporally. First, although most urban spatial form factors show significant correlations on LST at the global scale, the correlations vary significantly among low, medium, and high floor-area-ratio zones. Second, USFs largely contribute to the variance of LST in summer and autumn compared with winter. Third, building morphology exerts more impact on LST in relatively highly intensive built-up zones, while land use and land cover factors have more impact in low-intensity areas. Lastly, UHI can be precisely mitigated by optimizing USFs considering the varied relationships between USFs and LST. This study theoretically deepens the understanding of the variation of the relationships between built-up urban areas and UHI at the scale of the basic planning regulation units, which is conducive to formulating down-to-earth regulation measures to cool cities and communities.

ACS Style

Youpeng Lu; Wenze Yue; Yong Liu; Yaping Huang. Investigating the spatiotemporal non-stationary relationships between urban spatial form and land surface temperature: A case study of Wuhan, China. Sustainable Cities and Society 2021, 72, 103070 .

AMA Style

Youpeng Lu, Wenze Yue, Yong Liu, Yaping Huang. Investigating the spatiotemporal non-stationary relationships between urban spatial form and land surface temperature: A case study of Wuhan, China. Sustainable Cities and Society. 2021; 72 ():103070.

Chicago/Turabian Style

Youpeng Lu; Wenze Yue; Yong Liu; Yaping Huang. 2021. "Investigating the spatiotemporal non-stationary relationships between urban spatial form and land surface temperature: A case study of Wuhan, China." Sustainable Cities and Society 72, no. : 103070.

Journal article
Published: 28 May 2021 in Resources, Conservation and Recycling
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Anthropogenic heat is a dominant component in the urban surface energy system and a key to understanding urban thermal environments. The top-down method was widely used to estimate anthropogenic heat flux (AHF) using statistical energy consumption data and proxies. However, there are several limitations. First, the coarse resolutions of current proxies cannot capture the heterogeneous AHF. Besides, the temporal resolution is generally low (annual) in most AHF studies using the top-down method. This study estimated AHFs from three sectors and their monthly and hourly patterns in Beijing, China by developing a new framework. We first used a new proxy of building volume to obtain the AHF from buildings. Then, we estimated the AHF from vehicles and human metabolism using road density and population density, respectively. Finally, the monthly and hourly (workday and non-workday) AHFs were derived using temporal downscaling methods. The results show that the historic buildings in the urban center have a relatively low AHF. Areas with high AHF mainly distribute in the region between the 2nd and 4th ring-road and industrial zones outside the 5th ring-road. The magnitude of AHF varies among months, with the maximum monthly AHF at the district level reaching 68.1 W/m2 in January. AHF in January workdays is significantly higher than that in January non-workdays during 7:00 h to 20:00 h. The estimated AHF in this study can better capture multi-temporal AHF through the top-down method and temporal downscaling methods. The improved AHF data help policymakers design various strategies to improve urban thermal environments under sustainable development goals.

ACS Style

Xue Liu; Wenze Yue; Yuyu Zhou; Yong Liu; Changsheng Xiong; Qi Li. Estimating multi-temporal anthropogenic heat flux based on the top-down method and temporal downscaling methods in Beijing, China. Resources, Conservation and Recycling 2021, 172, 105682 .

AMA Style

Xue Liu, Wenze Yue, Yuyu Zhou, Yong Liu, Changsheng Xiong, Qi Li. Estimating multi-temporal anthropogenic heat flux based on the top-down method and temporal downscaling methods in Beijing, China. Resources, Conservation and Recycling. 2021; 172 ():105682.

Chicago/Turabian Style

Xue Liu; Wenze Yue; Yuyu Zhou; Yong Liu; Changsheng Xiong; Qi Li. 2021. "Estimating multi-temporal anthropogenic heat flux based on the top-down method and temporal downscaling methods in Beijing, China." Resources, Conservation and Recycling 172, no. : 105682.

Journal article
Published: 11 March 2021 in Remote Sensing
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Producing gridded electric power consumption (EPC) maps at a fine geographic scale is critical for rational deployment and effective utilization of electric power resources. Brightness of nighttime light (NTL) has been extensively adopted to evaluate the spatial patterns of EPC at multiple geographical scales. However, the blooming effect and saturation issue of NTL imagery limit its ability to accurately map EPC. Moreover, limited sectoral separation in applying NTL leads to the inaccurate spatial distribution of EPC, particularly in the case of industrial EPC, which is often a dominant portion of the total EPC in China. This study pioneers the separate estimation of spatial patterns of industrial and nonindustrial EPC over mainland China by jointly using points of interest (POIs) and multiple remotely sensed data in a random forests (RF) model. The POIs provided fine and detailed information about the different socioeconomic activities and played a significant role in determining industrial and nonindustrial EPC distribution. Based on the RF model, we produced industrial, non-industrial, and overall EPC maps at a 1 km resolution in mainland China for 2011. Compared against statistical data at the county level, our results showed a high accuracy (R 2 = 0.958 for nonindustrial EPC estimation, 0.848 for industrial EPC estimation, and 0.913 for total EPC). This study indicated that the proposed RF-based method, integrating POIs and multiple remote sensing data, can markedly improve the accuracy for estimating EPC. This study also revealed the great potential of POIs in mapping the distribution of socioeconomic parameters.

ACS Style

Cheng Jin; Yili Zhang; Xuchao Yang; Naizhuo Zhao; Zutao Ouyang; Wenze Yue. Mapping China’s Electronic Power Consumption Using Points of Interest and Remote Sensing Data. Remote Sensing 2021, 13, 1058 .

AMA Style

Cheng Jin, Yili Zhang, Xuchao Yang, Naizhuo Zhao, Zutao Ouyang, Wenze Yue. Mapping China’s Electronic Power Consumption Using Points of Interest and Remote Sensing Data. Remote Sensing. 2021; 13 (6):1058.

Chicago/Turabian Style

Cheng Jin; Yili Zhang; Xuchao Yang; Naizhuo Zhao; Zutao Ouyang; Wenze Yue. 2021. "Mapping China’s Electronic Power Consumption Using Points of Interest and Remote Sensing Data." Remote Sensing 13, no. 6: 1058.

Journal article
Published: 01 January 2021 in JOURNAL OF NATURAL RESOURCES
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ACS Style

Jin-Hui Xiong; Wen-Ze Yue; Yang Chen; Rong Liao; Kai Fang. Multi-scenario urban expansion simulation for SDGs: Taking the Central Asian region along the Belt and Road as an example. JOURNAL OF NATURAL RESOURCES 2021, 36, 841 -853.

AMA Style

Jin-Hui Xiong, Wen-Ze Yue, Yang Chen, Rong Liao, Kai Fang. Multi-scenario urban expansion simulation for SDGs: Taking the Central Asian region along the Belt and Road as an example. JOURNAL OF NATURAL RESOURCES. 2021; 36 (4):841-853.

Chicago/Turabian Style

Jin-Hui Xiong; Wen-Ze Yue; Yang Chen; Rong Liao; Kai Fang. 2021. "Multi-scenario urban expansion simulation for SDGs: Taking the Central Asian region along the Belt and Road as an example." JOURNAL OF NATURAL RESOURCES 36, no. 4: 841-853.

Journal article
Published: 24 December 2020 in Applied Geography
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The important ecological and recreational functions of public green spaces for metropolitan regions have been increasingly recognized, especially in the last few decades in developing countries that experienced rapid urbanization at the cost of ecological land. This study developed a green accessibility index (GAI) that quantifies the efficiency of accessing different levels of public green spaces. The GAI used the improved estimation method by using web map services, which can acquire information such as optimized path choices and corresponding time-cost information in different trip modes. Taking Shanghai as a case, this study measured and mapped the accessibility of different types of public green spaces at the spatial resolution of 50 m. The results illustrated that the Central Activities Zone had the highest accessibility, whereas most rural areas beyond the Inner Ring Road had low accessibility, except for some parts dotted with several public parks. Overall, the accessibility decreased from the city core to the urban periphery within the Outer Ring Road. This study proposed an improved method to estimate the green space accessibility at a much finer scale with high accuracy, due to the advantages of the data provided by web map services. This method can be an effective tool in planning public green spaces, and can be adapted to plan other public service facilities.

ACS Style

Jiamin Zhang; Wenze Yue; Peilei Fan; Jiabin Gao. Measuring the accessibility of public green spaces in urban areas using web map services. Applied Geography 2020, 126, 102381 .

AMA Style

Jiamin Zhang, Wenze Yue, Peilei Fan, Jiabin Gao. Measuring the accessibility of public green spaces in urban areas using web map services. Applied Geography. 2020; 126 ():102381.

Chicago/Turabian Style

Jiamin Zhang; Wenze Yue; Peilei Fan; Jiabin Gao. 2020. "Measuring the accessibility of public green spaces in urban areas using web map services." Applied Geography 126, no. : 102381.

Journal article
Published: 16 November 2020 in Sustainable Cities and Society
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Urban vitality is widely recognized as an authentic philosophy that reflects chaotic urbanization and orthodox planning in the developed world. However, comparative studies on the urban vitality of developing countries are scarce. This study developed a framework for analyzing urban vitality in developing countries. Using Ho Chi Minh City and Shanghai as cases, we measured urban vitality and analyzed its spatial pattern by using a projection pursuit model based on three dimensions of human activity, built environment, and their linkage. Both cities show a declining gradient of urban vitality from the urban cores to suburbs. However, Shanghai also fosters several peaks of urban vitality in its subcenters. The different spatial patterns of urban vitality are largely determined by the monocentric or polycentric urban form. A similar pattern of high urban vitality in both urban cores may be associated with the European-style block planning in the former concession areas. Recently, these two cities launched large-scale transport projects and replicated the modern style of broad and grid roads from the US, thereby reducing their urban vitality. This comparative study can improve our understanding of urban vitality patterns in developing countries and provide some planning suggestions that can help nurture urban vitality.

ACS Style

Wenze Yue; Yang Chen; Pham Thi Mai Thy; Peilei Fan; Yong Liu; Wei Zhang. Identifying urban vitality in metropolitan areas of developing countries from a comparative perspective: Ho Chi Minh City versus Shanghai. Sustainable Cities and Society 2020, 65, 102609 .

AMA Style

Wenze Yue, Yang Chen, Pham Thi Mai Thy, Peilei Fan, Yong Liu, Wei Zhang. Identifying urban vitality in metropolitan areas of developing countries from a comparative perspective: Ho Chi Minh City versus Shanghai. Sustainable Cities and Society. 2020; 65 ():102609.

Chicago/Turabian Style

Wenze Yue; Yang Chen; Pham Thi Mai Thy; Peilei Fan; Yong Liu; Wei Zhang. 2020. "Identifying urban vitality in metropolitan areas of developing countries from a comparative perspective: Ho Chi Minh City versus Shanghai." Sustainable Cities and Society 65, no. : 102609.

Journal article
Published: 31 August 2020 in Remote Sensing
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Urban land-use information is important for urban land-resource planning and management. However, current methods using traditional surveys cannot meet the demand for the rapid development of urban land management. There is an urgent need to develop new methods to overcome the shortcomings of conventional methods. To address the issue, this study used the random forest (RF), support vector machine (SVM), and artificial neural network (ANN) models to build machine-leaning methods for urban land-use classification. Taking Hangzhou as an example, these machine-leaning methods could all successfully classify the essential urban land use into 6 Level I classes and 13 Level II classes based on the semantic features extracted from Sentinel-2A images, multi-source features of types of points of interest (POIs), land surface temperature, night lights, and building height. The validation accuracy of the RF model for the Level I and Level II land use was 79.88% and 71.89%, respectively, performing better compared to SVM (78.40% and 68.64%) and ANN models (71.30% and 63.02%). However, the variations of the user accuracy among the methods depended on the urban land-use level. For the Level I land-use classification, the user accuracy was high, except for the transportation land by all methods. In general, the RF and SVM models performed better than the ANN model. For the Level II land-use classification, the user accuracy of different models was quite distinct. With the RF model, the user accuracy of educational and medical land was above 80%. Moreover, with the SVM model, the user accuracy of the business office and educational land classification was above 75%. However, the user accuracy of the ANN model on the Level II land-use classification was poor. Our results showed that the RF model performs best, followed by SVM model, and ANN model was relatively poor in the essential urban land-use classification. The results proved that the use of machine-learning methods can quickly extract land-use types with high accuracy, and provided a better method choice for urban land-use information acquisition.

ACS Style

Wanliu Mao; Debin Lu; Li Hou; Xue Liu; Wenze Yue. Comparison of Machine-Learning Methods for Urban Land-Use Mapping in Hangzhou City, China. Remote Sensing 2020, 12, 2817 .

AMA Style

Wanliu Mao, Debin Lu, Li Hou, Xue Liu, Wenze Yue. Comparison of Machine-Learning Methods for Urban Land-Use Mapping in Hangzhou City, China. Remote Sensing. 2020; 12 (17):2817.

Chicago/Turabian Style

Wanliu Mao; Debin Lu; Li Hou; Xue Liu; Wenze Yue. 2020. "Comparison of Machine-Learning Methods for Urban Land-Use Mapping in Hangzhou City, China." Remote Sensing 12, no. 17: 2817.

Research article
Published: 27 August 2020 in Environment and Planning B: Urban Analytics and City Science
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Nighttime light imageries are widely used for mapping the gross domestic product (GDP) over large areas. However, nighttime light imagery is inappropriate to disaggregate agricultural GDP and inadequate to differentiate the GDP from the secondary and tertiary sectors. Points-of-interest, a kind of geospatial big data with geographic locations and textual descriptions of the category, can effectively distinguish industrial and commercial areas, and therefore have the potential to improve the precise GDP mapping from secondary and tertiary sectors. In this study, a machine learning method, random forest, was used to disaggregate the 2010 county-level census GDP data of mainland China to 1 km × 1 km grids. Six Random Forest models were constructed for different economic sectors to explore the non-linear relationships between various geographic predictors and GDP from different sectors. By fusing points-of-interest of varying categories, the spatial distribution of economic activities from the secondary and tertiary sectors was effectively distinguished. Compared to previous studies, the strategy of developing specific Random Forest models for different sectors generated a more reasonable distribution of GDP. Our results highlight the feasibility of using point-of-interest data in disaggregating non-agricultural GDP by exploiting the complementary features of the different data sources.

ACS Style

Qian Chen; Tingting Ye; Naizhuo Zhao; Mingjun Ding; Zutao Ouyang; Peng Jia; Wenze Yue; Xuchao Yang. Mapping China’s regional economic activity by integrating points-of-interest and remote sensing data with random forest. Environment and Planning B: Urban Analytics and City Science 2020, 1 .

AMA Style

Qian Chen, Tingting Ye, Naizhuo Zhao, Mingjun Ding, Zutao Ouyang, Peng Jia, Wenze Yue, Xuchao Yang. Mapping China’s regional economic activity by integrating points-of-interest and remote sensing data with random forest. Environment and Planning B: Urban Analytics and City Science. 2020; ():1.

Chicago/Turabian Style

Qian Chen; Tingting Ye; Naizhuo Zhao; Mingjun Ding; Zutao Ouyang; Peng Jia; Wenze Yue; Xuchao Yang. 2020. "Mapping China’s regional economic activity by integrating points-of-interest and remote sensing data with random forest." Environment and Planning B: Urban Analytics and City Science , no. : 1.

Journal article
Published: 21 August 2020 in Landscape and Urban Planning
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Green space accessibility is widely acknowledged as a crucial aspect of a livable environment and human well-being. Whether green space accessibility is equitable among communities is increasingly considered as an issue of environmental justice. Therefore, this study focuses on the possible environmental inequality of green space accessibility that can be found among residential communities in the context of Chinese booming housing market. The case study of Shanghai, China was conducted with the use of big data. A real-time navigation route measurement based on Amap application programming interface (AAPI) was developed to calculate green space accessibility, and housing price was used to indicate dwellers’ socioeconomic status. Bivariate Moran’s I, multiple regression, and spatial lag regression were adopted to explore inequality of green space accessibility among residential communities. The results reveal a spatial inequality of green space accessibility between communities in central portion of the city and those in peri-urban areas. We further found a spatial mismatch between green space accessibility and housing price. Environmental inequality is evident within the inner and middle ring road wherein wealthier communities benefit more from green space accessibility than disadvantaged communities. We attribute these findings to spatial restructuring and green gentrification process in Shanghai. The findings can inform planners and policymakers to determine where and how to implement greening strategies and to gain awareness to prevent environmental inequality.

ACS Style

Yang Chen; Wenze Yue; Daniele La Rosa. Which communities have better accessibility to green space? An investigation into environmental inequality using big data. Landscape and Urban Planning 2020, 204, 103919 .

AMA Style

Yang Chen, Wenze Yue, Daniele La Rosa. Which communities have better accessibility to green space? An investigation into environmental inequality using big data. Landscape and Urban Planning. 2020; 204 ():103919.

Chicago/Turabian Style

Yang Chen; Wenze Yue; Daniele La Rosa. 2020. "Which communities have better accessibility to green space? An investigation into environmental inequality using big data." Landscape and Urban Planning 204, no. : 103919.

Journal article
Published: 07 July 2020 in Environmental Pollution
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Rapid urbanization and industrialization in China stimulated the great increase of energy consumption, which leads to drastic rise in the emission of anthropogenic waste heat. Anthropogenic heat emission (AHE) is a crucial component of urban energy budget and has direct implications for investigating urban climate and environment. However, reliable and accurate representation of AHE across China is still lacking. This study presented a new machine learning-based top–down approach to generate a gridded anthropogenic heat flux (AHF) benchmark dataset at 1 km spatial resolution for China in 2010. Cubist models were constructed by fusing points-of-interest (POI) data of varying categories and multisource remote sensing data to explore the nonlinear relationships between various geographic predictors and AHE from different heat sources. The strategy of developing specific models for different components and exploiting the complementary features of POIs and remote sensing data generated a more reasonable distribution of AHF. Results showed that the AHF values in urban centers of metropolises over China range from 60 to 190 W m−2. The highest AHF values were observed in some heavy industrial zones with value up to 415 W m−2. Compared with previous studies, the spatial distribution of AHF from different heating components was effectively distinguished, which highlights the potential of POI data in improving the precision of AHF mapping. The gridded AHF dataset can serve as input of urban numerical models and can help decision makers in targeting extreme heat sources and polluters in cities and making differentiated and tailored strategies for emission mitigation.

ACS Style

Qian Chen; Xuchao Yang; Zutao Ouyang; Naizhuo Zhao; Qutu Jiang; Tingting Ye; Jun Qi; Wenze Yue. Estimation of anthropogenic heat emissions in China using Cubist with points-of-interest and multisource remote sensing data. Environmental Pollution 2020, 266, 115183 .

AMA Style

Qian Chen, Xuchao Yang, Zutao Ouyang, Naizhuo Zhao, Qutu Jiang, Tingting Ye, Jun Qi, Wenze Yue. Estimation of anthropogenic heat emissions in China using Cubist with points-of-interest and multisource remote sensing data. Environmental Pollution. 2020; 266 ():115183.

Chicago/Turabian Style

Qian Chen; Xuchao Yang; Zutao Ouyang; Naizhuo Zhao; Qutu Jiang; Tingting Ye; Jun Qi; Wenze Yue. 2020. "Estimation of anthropogenic heat emissions in China using Cubist with points-of-interest and multisource remote sensing data." Environmental Pollution 266, no. : 115183.

Research article
Published: 23 June 2020 in Complexity
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Extreme heat is the leading cause of heat-related mortality around the world. Extracting heat vulnerability information from the urban complexity system is crucial for urban health studies. Using heat vulnerability index (HVI) is the most common approach for urban planners to locate the places with high vulnerability for intervention and protection. Previous studies have demonstrated that HVI can play a vital role in determining which areas are at risk of heat-related deaths. Both equal weight approach (EWA) and principal component analysis (PCA) are the conventional methods to aggregate indicators to HVI. However, seldom studies have compared the differences between these two approaches in estimating HVI. In this paper, we evaluated the HVIs in Hangzhou in 2013, employing EWA and PCA, and assessed the accuracies of these two HVIs by using heat-related deaths. Our results show that both HVI maps showed that areas with high vulnerability are located in the central area while those with low vulnerability are located in the suburban area. The comparison between HVIEWA and HVIPCA shows significantly different spatial distributions, which is caused by the various weight factors in EWA and PCA. The relationship between HVIEWA and heat-related deaths performs better than the relationship between HVIPCA and deaths, implying EWA could be a better method to evaluate heat vulnerability than PCA. The HVIEWA can provide a spatial distribution of heat vulnerability at intracity to direct heat adaptation and emergency capacity planning.

ACS Style

Xue Liu; Wenze Yue; Xuchao Yang; Kejia Hu; Wei Zhang; Muyi Huang. Mapping Urban Heat Vulnerability of Extreme Heat in Hangzhou via Comparing Two Approaches. Complexity 2020, 2020, 1 -16.

AMA Style

Xue Liu, Wenze Yue, Xuchao Yang, Kejia Hu, Wei Zhang, Muyi Huang. Mapping Urban Heat Vulnerability of Extreme Heat in Hangzhou via Comparing Two Approaches. Complexity. 2020; 2020 ():1-16.

Chicago/Turabian Style

Xue Liu; Wenze Yue; Xuchao Yang; Kejia Hu; Wei Zhang; Muyi Huang. 2020. "Mapping Urban Heat Vulnerability of Extreme Heat in Hangzhou via Comparing Two Approaches." Complexity 2020, no. : 1-16.

Journal article
Published: 01 June 2020 in Journal of Urban Planning and Development
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Environmental pollution incidents affect urban residents and the natural environment. This article employs hedonic price models and a difference-in-difference (DID) approach to examine how widely in space an environmental incident affects housing prices and how great this effect is over several time periods. Using the well-known 2014 Hangzhou Pesticide Plant (HPP) pollution cleanup incident as an example, this research confirms the following: (1) This pesticide plant incident depreciated house prices within 3 km by 2.955%, that is by 41,712 yuan, at the 5% significance level. (2) The devaluation persisted even after the removal of the pollution. Our results suggest that environmental events can devaluate nearby properties beyond the extent of the actual pollution by imposing a “quasi-stigma” (negative perception) on these houses. This effect can be persistent and hard to overturn and arises from perceived disamenitities, taints on the properties.

ACS Style

Wenze Yue; Chaoran Ni; Chuanhao Tian; Haizhen Wen; Li Fang. Impacts of an Urban Environmental Event on Housing Prices: Evidence from the Hangzhou Pesticide Plant Incident. Journal of Urban Planning and Development 2020, 146, 04020015 .

AMA Style

Wenze Yue, Chaoran Ni, Chuanhao Tian, Haizhen Wen, Li Fang. Impacts of an Urban Environmental Event on Housing Prices: Evidence from the Hangzhou Pesticide Plant Incident. Journal of Urban Planning and Development. 2020; 146 (2):04020015.

Chicago/Turabian Style

Wenze Yue; Chaoran Ni; Chuanhao Tian; Haizhen Wen; Li Fang. 2020. "Impacts of an Urban Environmental Event on Housing Prices: Evidence from the Hangzhou Pesticide Plant Incident." Journal of Urban Planning and Development 146, no. 2: 04020015.

Journal article
Published: 21 April 2020 in Research in Transportation Economics
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This study investigates the property price premium brought by the opening of a subway to illustrate temporal dynamics and heterogeneous mechanism of property value effects. The estimation of changes caused by subways on property value can aid in assessing the benefits of public transit investments well. On the basis of residential property transaction records in Hangzhou, China in 2009–2013, hedonic models in a difference-in-differences framework are applied to handle certain endogeneity problems of estimation by eliminating unobserved factors. Results show that treatment groups located within 1000 m of a subway have an average price increase of 444 yuan per m2 from the opening of Line1. High-cost houses constantly gain significant increment and their price premium regress during the research period. However, for their counterparts in low-cost communities, the insignificant price effects are negative for a short time, and then become positive. The generalized results are robust when subway radius is adjusted.

ACS Style

Chuanhao Tian; Ying Peng; Haizhen Wen; Wenze Yue; Li Fang. Subway boosts housing values, for whom: A quasi-experimental analysis. Research in Transportation Economics 2020, 100844 .

AMA Style

Chuanhao Tian, Ying Peng, Haizhen Wen, Wenze Yue, Li Fang. Subway boosts housing values, for whom: A quasi-experimental analysis. Research in Transportation Economics. 2020; ():100844.

Chicago/Turabian Style

Chuanhao Tian; Ying Peng; Haizhen Wen; Wenze Yue; Li Fang. 2020. "Subway boosts housing values, for whom: A quasi-experimental analysis." Research in Transportation Economics , no. : 100844.

Journal article
Published: 16 April 2020 in Cities
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Polycentric urban development has become the buzzword among urban scholars, decision-makers, and planners around the world. From the existing polycentric urban research, a functional approach is increasingly concerned by scholars except for morphological terms. Functional linkages are investigated among the (sub)centers of a polycentric urban system (PUS). However, the (sub)centers are usually pre-defined by a city master plan or identified by a density-sliced approach. However, the definition of the (sub)centers is still dependent on the morphological dimensions rather than functional linkages. To fill the gaps, we proposed a flow-based solution for delineating functional urban regions (FURs). We first built a spatially-embedded network of the entire city within extensive travel flows and then used a community detection method to reveal FURs. The characteristics of the whole PUS and the properties of each FUR are further assessed using complex network analysis. Based on the taxi trajectories of Shanghai, this study shows that the subdivisions of FURs are not necessarily consistent with administrative divisions. The functional linkages are strong among the (sub)centers surrounding the main center, and they are relatively weak among the newly established (sub)centers in the periphery. These findings call for policy interventions to increase the functional linkages of (sub)centers.

ACS Style

Tianyu Wang; Wenze Yue; Xinyue Ye; Yong Liu; Debin Lu. Re-evaluating polycentric urban structure: A functional linkage perspective. Cities 2020, 101, 102672 .

AMA Style

Tianyu Wang, Wenze Yue, Xinyue Ye, Yong Liu, Debin Lu. Re-evaluating polycentric urban structure: A functional linkage perspective. Cities. 2020; 101 ():102672.

Chicago/Turabian Style

Tianyu Wang; Wenze Yue; Xinyue Ye; Yong Liu; Debin Lu. 2020. "Re-evaluating polycentric urban structure: A functional linkage perspective." Cities 101, no. : 102672.

Journal article
Published: 11 February 2020 in Journal of Cleaner Production
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Urban heat island (UHI) is a major urban ecological environment issue, and it requires to be comprehensively understood from the perspective of temporal changes. This study investigated UHI in Beijing by building a monthly land surface temperature (LST) dataset at a fine spatial resolution in the summer from 2003 to 2018 using a data fusion method. First, we generated the monthly Landsat-like LST images. We then analyzed the temporal patterns of UHI in the past 16 years. Finally, we explored the spatial patterns of UHI. We find that UHI in Beijing experienced two phases, including the enhanced UHI concentrated in the urban area from 2003 to 2009, and the mitigated UHI dispersed in the suburban area from 2010 to 2018. The results of temporal trend analysis show that sub-districts with significant decreasing trends of UHI mainly locate in the urban center, while sub-districts with significant increasing trends of UHI mainly locate in the suburban areas. Moreover, the results of spatial clusters analysis demonstrate that the sub-districts with high UHIs concentrate in the urban center, while those with low UHIs disperse in the suburban area. The 16-year fine spatial resolution LSTs from this study offer a reliable dataset for studying the UHI in Beijing. The information on spatiotemporal patterns of UHI is of great help for urban planners to design UHI mitigation strategies for sustainable urban development.

ACS Style

Xue Liu; Yuyu Zhou; Wenze Yue; Xuecao Li; Yong Liu; Debin Lu. Spatiotemporal patterns of summer urban heat island in Beijing, China using an improved land surface temperature. Journal of Cleaner Production 2020, 257, 120529 .

AMA Style

Xue Liu, Yuyu Zhou, Wenze Yue, Xuecao Li, Yong Liu, Debin Lu. Spatiotemporal patterns of summer urban heat island in Beijing, China using an improved land surface temperature. Journal of Cleaner Production. 2020; 257 ():120529.

Chicago/Turabian Style

Xue Liu; Yuyu Zhou; Wenze Yue; Xuecao Li; Yong Liu; Debin Lu. 2020. "Spatiotemporal patterns of summer urban heat island in Beijing, China using an improved land surface temperature." Journal of Cleaner Production 257, no. : 120529.

Journal article
Published: 26 December 2019 in Habitat International
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We analyzed the evolution of industrial land use in the Shanghai's central city since 1947, with a more detailed analysis of determinants of change in the expanded city area since the economic reform for 2002–2009 and 2009–2016. Relying on land use data extracted from satellite images, air photos, and historic land use maps produced by local experts, we find that industrial land in the central area of Shanghai increased from 1947 to 1993 but declined from 2002 to 2016. The spatial form was transformed from scattered small industrial land pieces interspersed with other types of urban land within the urban core to a polycentric pattern of large patches with greater distances between patches. Using a binary spatial logistic regression on data from 2002 to 2009 and 2009–2016 for an extended area beyond Shanghai's central city, we found that major spatial determinants contributing to the recent conversion of Shanghai's industrial land include land price, the existing industrial land, and the planning policies for both periods and additionally distance to main transport station and economic development level for the period of 2009–2016. Moreover, patches affiliated with different sizes of industrial areas were driven by different sets of spatial determinants. Both large-size patches (>0.1 km2) and small-size patches (<0.05 km2) seem to be very sensitive to all spatial determinants, i.e., distances to major roads and to major station, economic development level, existing industrial land, land price, and planning policy, except economic development level for large patches for 2002–2009 and for small-size patches for 2009–2016. Our study provides valuable insights for planners as it highlighted important variables that land use planning can focus in order to achieve effective industrial land conversion. Our study also offers an example of utilizing different sources of data and methods for analyzing a specific type of urban land use change.

ACS Style

Peilei Fan; Wenze Yue; Jiamin Zhang; Huiqing Huang; Joseph Messina; Peter H. Verburg; Jiaguo Qi; Nathan Moore; Jianjun Ge. The spatial restructuring and determinants of industrial landscape in a mega city under rapid urbanization. Habitat International 2019, 95, 102099 .

AMA Style

Peilei Fan, Wenze Yue, Jiamin Zhang, Huiqing Huang, Joseph Messina, Peter H. Verburg, Jiaguo Qi, Nathan Moore, Jianjun Ge. The spatial restructuring and determinants of industrial landscape in a mega city under rapid urbanization. Habitat International. 2019; 95 ():102099.

Chicago/Turabian Style

Peilei Fan; Wenze Yue; Jiamin Zhang; Huiqing Huang; Joseph Messina; Peter H. Verburg; Jiaguo Qi; Nathan Moore; Jianjun Ge. 2019. "The spatial restructuring and determinants of industrial landscape in a mega city under rapid urbanization." Habitat International 95, no. : 102099.

Journal article
Published: 11 December 2019 in Sustainability
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Human activity recognition has been of interest in the field of urban planning. This paper established a general framework by which expected human activity intensity (HAI) measured by the built environment and factual HAI measured by the Baidu thermal chart were estimated and comparatively analyzed so as to identify abnormal human activities in Hanghzou, China. Three elements of the built environment (i.e., residential density, road connectivity, and land-use mixing degree) from multi-source data with high precision are selected to assess the expected HAI. Results indicate Hangzhou has evolved into a polycentric city with three urban clusters. In addition, a significant positive correlation exists between the two types of HAIs. However, there are areas with spatial mismatches, particularly in the “urban village” and new towns, suggesting human activities are not equally distributed all over the city. Research implications, limitations, and future research needs are discussed.

ACS Style

Lihua Xu; Huifeng Xu; Tianyu Wang; Wenze Yue; Jinyang Deng; Liwei Mao. Measuring Urban Spatial Activity Structures: A Comparative Analysis. Sustainability 2019, 11, 7085 .

AMA Style

Lihua Xu, Huifeng Xu, Tianyu Wang, Wenze Yue, Jinyang Deng, Liwei Mao. Measuring Urban Spatial Activity Structures: A Comparative Analysis. Sustainability. 2019; 11 (24):7085.

Chicago/Turabian Style

Lihua Xu; Huifeng Xu; Tianyu Wang; Wenze Yue; Jinyang Deng; Liwei Mao. 2019. "Measuring Urban Spatial Activity Structures: A Comparative Analysis." Sustainability 11, no. 24: 7085.

Journal article
Published: 07 October 2019 in Journal of Cleaner Production
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As the spatial carrier of the emission sources and influencing factors of PM2.5, land use and its changes can inevitably affect local and regional PM2.5 concentrations. The relationship between the growth of PM2.5 and the changes of land use in China during 1998-2015 was explored in this paper using the Theil-Sen median trend analysis, Mann-Kendall and spatial econometric model. The results showed that the area where PM2.5 concentration was less than 10 μg/m3 accounted for a small portion (18.33%) of the land area in China, and the area where PM2.5 concentration was more than 35 μg/m3 accounted for 31.30% of the land area. High PM2.5 concentration was found in the East China Plain and Taklimakan desert; artificial surfaces, cultivated land and deserts were coated with high PM2.5 concentration more frequently, while the forest, grassland and unused land were usually covered with low PM2.5 concentration. PM2.5 concentration in desert land and artificial surfaces respectively increased at a pace of 1.07 μg/m3 and 0.80 μg/m3 per year during 1998-2015, higher than those in other land use types. They mainly came from the sand dust aerosol in northwest China, while those in the other areas mainly came from emissions in the human activities. Therefore, reasonable coordinating the proportion of construction land, cultivated land, forest land and grassland in eastern China, and strengthening desert governance in northwest China, are suggested to reduce PM2.5 concentration in China.

ACS Style

Debin Lu; Jianhua Xu; Wenze Yue; Wanliu Mao; Dongyang Yang; Jinzhu Wang. Response of PM2.5 pollution to land use in China. Journal of Cleaner Production 2019, 244, 118741 .

AMA Style

Debin Lu, Jianhua Xu, Wenze Yue, Wanliu Mao, Dongyang Yang, Jinzhu Wang. Response of PM2.5 pollution to land use in China. Journal of Cleaner Production. 2019; 244 ():118741.

Chicago/Turabian Style

Debin Lu; Jianhua Xu; Wenze Yue; Wanliu Mao; Dongyang Yang; Jinzhu Wang. 2019. "Response of PM2.5 pollution to land use in China." Journal of Cleaner Production 244, no. : 118741.