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Zhaoxin Dai
Chinese academy of surveying and mapping, Beijing, China

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Article
Published: 21 August 2021 in Applied Spatial Analysis and Policy
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As air pollution becomes more serious in China, it is critical to study its influencing factors for targeted environmental governance. Existing researchers have conducted various studies on the factors of PM2.5 (fine particulate matter with a diameter less than or equal to 2.5 microns) pollution. However, these studies mostly conducted analyses focused on macroscopic factors and lacked an impact analysis of specific entity distributions on PM2.5 pollution. Furthermore, most existing studies used ordinary regression models that ignored the spatial heterogeneity of influence of various factors on pollution, leading to biased results. To address these issues, focusing on air quality in heavily polluted city (Weifang City), this study aims to measure the influence of spatial differentiation of the impacts of four roughly classified POIs, namely, industry, restaurants, scenic spots, and parking lots, on PM2.5 pollution quantitatively by using a geographically weighted regression (GWR) model (spatial varying-coefficient regression model). The results indicate that the spatial distribution of effects of industry, restaurant and parking lot POIs on PM2.5 concentrations in Weifang are similar. The impact of all four POIs on PM2.5 is spatially nonstationary and have certain spatial trends, parking lots have the greatest influence on PM2.5 pollution. Based on the findings, pollution prevention and control measures are suggested to be designed based on the actual situation. For instance, some counties in Weifang should be encouraged to develop tertiary industries dominated by tourism. This research investigated the spatial impacts of the specific entity distributions on air pollution and provided targeted advice based on findings, which can contribute to policy-making aimed at air pollution mitigation.

ACS Style

Chengming Li; Yuxue Zou; Zhaoxin Dai; Jie Yin; Zheng Wu; Zhaoting Ma. The Impacts of POI Data on PM2.5: A Case Study of Weifang City in China. Applied Spatial Analysis and Policy 2021, 1 -20.

AMA Style

Chengming Li, Yuxue Zou, Zhaoxin Dai, Jie Yin, Zheng Wu, Zhaoting Ma. The Impacts of POI Data on PM2.5: A Case Study of Weifang City in China. Applied Spatial Analysis and Policy. 2021; ():1-20.

Chicago/Turabian Style

Chengming Li; Yuxue Zou; Zhaoxin Dai; Jie Yin; Zheng Wu; Zhaoting Ma. 2021. "The Impacts of POI Data on PM2.5: A Case Study of Weifang City in China." Applied Spatial Analysis and Policy , no. : 1-20.

Journal article
Published: 30 April 2021 in Sustainability
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Urban built-up areas, where urbanization process takes place, represent well-developed areas in a city. The accurate and timely extraction of urban built-up areas has a fundamental role in the comprehension and management of urbanization dynamics. Urban built-up areas are not only a reflection of urban expansion but also the main space carrier of social activities. Recent research has attempted to integrate the social factor to improve the extraction accuracy. However, the existing extraction methods based on nighttime light data only focus on the integration of a single factor, such as points of interest or road networks, which leads to weak constraint and low accuracy. To address this issue, a new index-based methodology for urban built-up area extraction that fuses nighttime light data with multisource big data is proposed in this paper. The proposed index, while being conceptually simple and computationally inexpensive, can extract the built-up areas efficiently. First, a new index-based methodology, which integrates nighttime light data with points-of-interest, road networks, and the enhanced vegetation index, was constructed. Then, based on the proposed new index and the reference urban built-up data area, urban built-up area extraction was performed based on the dynamic threshold dichotomy method. Finally, the proposed method was validated based on actual data in a city. The experimental results indicate that the proposed index has high accuracy (recall, precision and F1 score) and applicability for urban built-up area boundary extraction. Moreover, this paper discussed different existing urban area extraction methods, and provides an insight into the appropriate approaches selection for further urban built-up area extraction in cities with different conditions.

ACS Style

Chengming Li; Xiaoyan Wang; Zheng Wu; Zhaoxin Dai; Jie Yin; Chengcheng Zhang. An Improved Method for Urban Built-Up Area Extraction Supported by Multi-Source Data. Sustainability 2021, 13, 5042 .

AMA Style

Chengming Li, Xiaoyan Wang, Zheng Wu, Zhaoxin Dai, Jie Yin, Chengcheng Zhang. An Improved Method for Urban Built-Up Area Extraction Supported by Multi-Source Data. Sustainability. 2021; 13 (9):5042.

Chicago/Turabian Style

Chengming Li; Xiaoyan Wang; Zheng Wu; Zhaoxin Dai; Jie Yin; Chengcheng Zhang. 2021. "An Improved Method for Urban Built-Up Area Extraction Supported by Multi-Source Data." Sustainability 13, no. 9: 5042.

Research article
Published: 26 February 2021 in Environmental Science and Pollution Research
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As urban green spaces have significant cooling effects on the urban heat island (UHI), a precise understanding of these effects is necessary to devise precise greenspace strategies for abating the UHI. This paper explores the impacts of different greenspace (trees, grass, and water) patterns on the UHI in Beijing’s Olympic Area, using different grid cell sizes and spatial statistical models. Greenspace pattern metrics include percent cover, mean patch size (MPS), mean patch shape index (MSI), edge density (ED), and largest percent index (LPI). The results show that different greenspace metrics have varying effects on surface temperature. The spatial error model (SEM) turns out to be a good choice for estimating the relationship between Land Surface Temperature (LST) and the greenspace metrics. The regression coefficients of these metrics vary with grid cell size. Tree and grass edge densities have opposite effects, which suggest that trees should be planted in smaller clusters, whereas grass should be planted in larger and continuous patches in order to reach maximum LST cooling. The optimal grid cell size is in the [120–240 m] range. These findings can help urban planners mitigate the UHI in a city with limited green space availability.

ACS Style

Yunfeng Hu; Zhaoxin Dai; Jean-Michel Guldmann. Greenspace configuration impact on the urban heat island in the Olympic Area of Beijing. Environmental Science and Pollution Research 2021, 28, 33096 -33107.

AMA Style

Yunfeng Hu, Zhaoxin Dai, Jean-Michel Guldmann. Greenspace configuration impact on the urban heat island in the Olympic Area of Beijing. Environmental Science and Pollution Research. 2021; 28 (25):33096-33107.

Chicago/Turabian Style

Yunfeng Hu; Zhaoxin Dai; Jean-Michel Guldmann. 2021. "Greenspace configuration impact on the urban heat island in the Olympic Area of Beijing." Environmental Science and Pollution Research 28, no. 25: 33096-33107.

Journal article
Published: 06 November 2020 in ISPRS International Journal of Geo-Information
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With the arrival of the big data era, mobile phone data have attracted increasing attention due to their rich information and high sampling rate. Currently, researchers have conducted various studies using mobile phone data. However, most existing studies have focused on macroscopic analysis, such as urban hot spot detection and crowd behavior analysis over a short period. With the development of the smart city, personal service and management have become very important, so microscopic portraiture research and mobility pattern of an individual based on big data is necessary. Therefore, this paper first proposes a method to depict the individual mobility pattern, and based on the long-term mobile phone data (from 2007 to 2012) of volunteers from Beijing as part of project Geolife conducted by Microsoft Research Asia, more detailed individual portrait depiction analysis is performed. The conclusions are as follows: (1) Based on high-density cluster identification, the behavior trajectories of volunteers are generalized into three types, and among them, the two-point-one-line trajectory and evenly distributed behavior trajectory were more prevalent in Beijing. (2) By integrating with Google Maps data, five volunteers’ behavior trajectories and the activity patterns of individuals were analyzed in detail, and a portrait depiction method for individual characteristics comprehensively considering their attributes, such as occupation and hobbies, is proposed. (3) Based on analysis of the individual characteristics of some volunteers, it is discovered that two-point-one-line individuals are generally white-collar workers working in enterprises or institutions, and the situation of a single cluster mainly exists among college students and home freelancer. The findings of this study are important for individual classification and prediction in the big data era and can also provide useful guidance for targeted services and individualized management of smart cities.

ACS Style

Chengming Li; Jiaxi Hu; Zhaoxin Dai; Zixian Fan; Zheng Wu. Understanding Individual Mobility Pattern and Portrait Depiction Based on Mobile Phone Data. ISPRS International Journal of Geo-Information 2020, 9, 666 .

AMA Style

Chengming Li, Jiaxi Hu, Zhaoxin Dai, Zixian Fan, Zheng Wu. Understanding Individual Mobility Pattern and Portrait Depiction Based on Mobile Phone Data. ISPRS International Journal of Geo-Information. 2020; 9 (11):666.

Chicago/Turabian Style

Chengming Li; Jiaxi Hu; Zhaoxin Dai; Zixian Fan; Zheng Wu. 2020. "Understanding Individual Mobility Pattern and Portrait Depiction Based on Mobile Phone Data." ISPRS International Journal of Geo-Information 9, no. 11: 666.

Journal article
Published: 26 October 2020 in ISPRS International Journal of Geo-Information
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Catchment division constitutes the foundation for urban water flood forecasting but represents a technically challenging task. The accurate division of catchments is significant for precisely forecasting urban waterlogging. However, existing catchment division methods usually lead to produce results that do not accurately reflect the actual land-use distributions. In recent years, most research has been performed in smaller study areas (less than 10 km2), in residential areas, parks and campuses, and usually focused on a single landscape type. However, for large highly urbanized areas with complex land uses, due to the spatial heterogeneity and complexity of such areas in terms of building, traffic network and hydrology, etc., there is few studies on sub-catchment division. Moreover, the division results by using existing method usually have deviate with the actual land-type distributions. To address the above-mentioned issues, a sub-catchment division method was here proposed that accounts for land-use types and flow directions, and it is suitable for large urban areas by introducing an auto-adaptive threshold adjustment in a novel algorithm. First, the study area is divided into first- and second-level (FL and SL, respectively) catchments according to the macroscale features such as natural landforms, canals, and pipe network. Second, an amended DEM (Digital Elevation Model) and flow direction data are used to divide the SL catchments into third-level direction-based (D-B) catchments. Finally, a novel land use-based algorithm is proposed to divide the D-B catchments into the “smallest” catchments (S-catchments). A large-scale area (44 km2) in Dongying City of China was employed to validate the proposed method. The experiment showed that the proposed method is suitable for subcatchment divisions in large regions and can ensure that the subcatchments are consistent with the actual distribution of land uses and runoff directions.

ACS Style

Chengming Li; Zixian Fan; Zheng Wu; Zhaoxin Dai; Li Liu; Chengcheng Zhang. Methodology of Sub-Catchment Division Considering Land Uses and Flow Directions. ISPRS International Journal of Geo-Information 2020, 9, 634 .

AMA Style

Chengming Li, Zixian Fan, Zheng Wu, Zhaoxin Dai, Li Liu, Chengcheng Zhang. Methodology of Sub-Catchment Division Considering Land Uses and Flow Directions. ISPRS International Journal of Geo-Information. 2020; 9 (11):634.

Chicago/Turabian Style

Chengming Li; Zixian Fan; Zheng Wu; Zhaoxin Dai; Li Liu; Chengcheng Zhang. 2020. "Methodology of Sub-Catchment Division Considering Land Uses and Flow Directions." ISPRS International Journal of Geo-Information 9, no. 11: 634.

Article
Published: 09 September 2020 in Multimedia Tools and Applications
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Techniques for the fusion of real-world videos with virtual scenes are key to the augmentation of three-dimensional (3-D) virtual geographic scenes, which greatly enhances the immersive visual experience. When a 3-D scene is updated dynamically, the existing video projection-based method for real-virtual fusion is generally slow and inefficient, as all rendered objects must be traversed in the new scene to identify the objects to be fused in the user’s new field of view (FOV). To address this issue, a fast, topology-accounting method for multi-video fusion with 3-D geographic information system (GIS) scenes is proposed. First, the topological models for video object and rendered object are constructed, respectively. Second, by using the topological models, a method that considering topological relationships is proposed to realize rapid identification of rendered objects during the dynamic update of 3-D scenes. Finally, real video and 3-D scene data in Tengzhou City were used to validate the method proposed in this paper. The experiments demonstrated that the method is fast and efficient in the fusion of videos with 3-D GIS scenes, and the computational cost of the proposed method is significantly lower than that of the current method. The proposed method is highly viable and robust, facilitating the fusion of videos with virtual environments.

ACS Style

Chengming Li; Zhendong Liu; Zhanjie Zhao; Zhaoxin Dai. A fast fusion method for multi-videos with three-dimensional GIS scenes. Multimedia Tools and Applications 2020, 80, 1671 -1686.

AMA Style

Chengming Li, Zhendong Liu, Zhanjie Zhao, Zhaoxin Dai. A fast fusion method for multi-videos with three-dimensional GIS scenes. Multimedia Tools and Applications. 2020; 80 (2):1671-1686.

Chicago/Turabian Style

Chengming Li; Zhendong Liu; Zhanjie Zhao; Zhaoxin Dai. 2020. "A fast fusion method for multi-videos with three-dimensional GIS scenes." Multimedia Tools and Applications 80, no. 2: 1671-1686.

Journal article
Published: 16 July 2020 in International Journal of Environmental Research and Public Health
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As air pollution becomes highly focused in China, the accurate identification of its influencing factors is critical for achieving effective control and targeted environmental governance. Land-use distribution is one of the key factors affecting air quality, and research on the impact of land-use distribution on air pollution has drawn wide attention. However, considerable studies have mostly used linear regression models, which fail to capture the nonlinear effects of land-use distribution on PM2.5 (fine particulate matter with a diameter less than or equal to 2.5 microns) and to show how impacts on PM2.5 vary with land-use magnitudes. In addition, related studies have generally focused on annual analyses, ignoring the seasonal variability of the impact of land-use distribution on PM2.5, thus leading to possible estimation biases for PM2.5. This study was designed to address these issues and assess the impacts of land-use distribution on PM2.5 in Weifang, China. A machine learning statistical model, the boosted regression tree (BRT), was applied to measure nonlinear effects of land-use distribution on PM2.5, capture how land-use magnitude impacts PM2.5 across different seasons, and explore the policy implications for urban planning. The main conclusions are that the air quality will significantly improve with an increase in grassland and forest area, especially below 8% and 20%, respectively. When the distribution of construction land is greater than around 10%, the PM2.5 pollution can be seriously substantially increased with the increment of their areas. The impact of gardens and farmland presents seasonal characteristics. It is noted that as the weather becomes colder, the inhibitory effect of vegetation distribution on the PM2.5 concentration gradually decreases, while the positive impacts of artificial surface distributions, such as construction land and roads, are aggravated because leaves drop off in autumn (September–November) and winter (December–February). According to the findings of this study, it is recommended that Weifang should strengthen pollution control in winter, for instance, expand the coverage areas of evergreen vegetation like Pinus bungeana Zucc. and Euonymus japonicus Thunb, and increase the width and numbers of branches connecting different main roads. The findings also provide quantitative and optimal land-use planning and strategies to minimize PM2.5 pollution, referring to the status of regional urbanization and greening construction.

ACS Style

Chengming Li; Kuo Zhang; Zhaoxin Dai; Zhaoting Ma; Xiaoli Liu. Investigation of the Impact of Land-Use Distribution on PM2.5 in Weifang: Seasonal Variations. International Journal of Environmental Research and Public Health 2020, 17, 5135 .

AMA Style

Chengming Li, Kuo Zhang, Zhaoxin Dai, Zhaoting Ma, Xiaoli Liu. Investigation of the Impact of Land-Use Distribution on PM2.5 in Weifang: Seasonal Variations. International Journal of Environmental Research and Public Health. 2020; 17 (14):5135.

Chicago/Turabian Style

Chengming Li; Kuo Zhang; Zhaoxin Dai; Zhaoting Ma; Xiaoli Liu. 2020. "Investigation of the Impact of Land-Use Distribution on PM2.5 in Weifang: Seasonal Variations." International Journal of Environmental Research and Public Health 17, no. 14: 5135.

Research article
Published: 29 May 2020 in Transactions in GIS
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Small‐area patch merging is a common operation in land use data generalization. However, existing research on small‐area patch merging has mainly focused on local compatibility measures, which often lead to area imbalances among land use types from a global perspective. To address the shortcomings of previous studies by resolving local and global concerns simultaneously, this article proposes a merging method that considers both local constraints and the overall area balance. First, a local optimization model that considers three constraints—namely, the areas of neighboring patches, the lengths of shared arcs, and semantic similarity—is established. The areas of small patches are first pre‐allocated. Subsequently, in accordance with an area change threshold for individual land use types, land use types with area changes that exceed this threshold are identified. The patches corresponding to these land use types are subjected to iterative adjustments while considering the overall area balance. Based on their area splitting abilities, the split lines for small‐area patches are determined, and small‐area patches are merged. Finally, actual data from Guangdong Province are used for validation. The experimental results demonstrate that the proposed method is capable of preserving the local compatibility of patches while balancing the overall area associated with each land use type.

ACS Style

Chengming Li; Yong Yin; Zhaoxin Dai; Wei Wu. Small‐area patch‐merging method accounting for both local constraints and the overall area balance. Transactions in GIS 2020, 24, 1098 -1118.

AMA Style

Chengming Li, Yong Yin, Zhaoxin Dai, Wei Wu. Small‐area patch‐merging method accounting for both local constraints and the overall area balance. Transactions in GIS. 2020; 24 (4):1098-1118.

Chicago/Turabian Style

Chengming Li; Yong Yin; Zhaoxin Dai; Wei Wu. 2020. "Small‐area patch‐merging method accounting for both local constraints and the overall area balance." Transactions in GIS 24, no. 4: 1098-1118.

Journal article
Published: 29 April 2020 in Journal of Environmental Management
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Understanding how complex urban factors affect the Urban Heat Island (UHI) is crucial for assessing the impacts of urban planning and environmental management on the thermal environment. This paper investigates the relationships between two-dimensional (2D) and three-dimensional (3D) factors and land surface temperatures (LST) within the Olympic Area of Beijing in different seasons, using the boosted regression tree (BRT) model. The BRT model captures the specific contributions of each urban factor to LST in each season and across a continuum of magnitudes for this factor. The results show that these relationships are complex and highly nonlinear. The four most common dominant factors are the Normalized Difference Built-up Index (NDBI), the Normalized Difference Vegetation Index (NDVI), a gravity index for parks (GPI), and average building height (BH). The most important factor in spring is NDBI, with a 45.5% contribution rate. In the other seasons, NDVI is the dominant factor, with contributions of 40% in summer, 21% in autumn, and 19% in winter. NDVI has an overall negative impact on LST in spring and summer, with a quadratic nonlinear decreasing curve, but a positive one in autumn and winter. The 2D land-use variables are most strongly related to LST in summer and spring, but 3D building-related variables have stronger impacts in colder weather. The Sky View Factor (SVF), a 3D measure of urban morphology, has also strong impacts in summer and winter. Both a building-based and a DSM-based SVFs are computed. The latter accounts for buildings, bridges, and trees. In contrast to a building-based SVF, the DSM-based SVF reduces LST when it varies between 0 and 0.75, reflecting the effects of high-density tree canopies that increase shades and evapotranspiration while blocking sky view. The marginal effect curves produced by the BRT are often characterized by thresholds. For instance, the maximal NDVI effect in summer takes place when NDVI = 0.7, suggesting that a very intense green coverage is not necessary to achieve maximal thermal results. Implications for urban planning and environmental management are outlined, including the increased use of evergreen trees that provide thermal benefits in both summer and winter.

ACS Style

Yunfeng Hu; Zhaoxin Dai; Jean-Michel Guldmann. Modeling the impact of 2D/3D urban indicators on the urban heat island over different seasons: A boosted regression tree approach. Journal of Environmental Management 2020, 266, 110424 .

AMA Style

Yunfeng Hu, Zhaoxin Dai, Jean-Michel Guldmann. Modeling the impact of 2D/3D urban indicators on the urban heat island over different seasons: A boosted regression tree approach. Journal of Environmental Management. 2020; 266 ():110424.

Chicago/Turabian Style

Yunfeng Hu; Zhaoxin Dai; Jean-Michel Guldmann. 2020. "Modeling the impact of 2D/3D urban indicators on the urban heat island over different seasons: A boosted regression tree approach." Journal of Environmental Management 266, no. : 110424.

Journal article
Published: 20 April 2020 in Applied Sciences
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As air pollution becomes progressively more serious, accurate identification of urban air pollution characteristics and associated pollutant transport mechanisms helps to effectively control and alleviate air pollution. This paper investigates the pollution characteristics, transport pathways, and potential sources of PM2.5 in Weifang based on PM2.5 monitoring data from 2015 to 2016 using three methods: Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT), the potential source contribution function (PSCF), and concentration weighted trajectory (CWT). The results show the following: (1) Air pollution in Weifang was severe from 2015 to 2016, and the annual average PM2.5 concentration was more than twice the national air quality second-level standard (35 μg/m3). (2) Seasonal transport pathways of PM2.5 vary significantly: in winter, spring and autumn, airflow from the northwest and north directions accounts for a large proportion; in contrast, in summer, warm-humid airflows from the ocean in the southeastern direction dominate with scattered characteristics. (3) The PSCF and CWT results share generally similar characteristics in the seasonal distributions of source areas, which demonstrate the credibility and accuracy of the analysis results. (4) More attention should be paid to short-distance transport from the surrounding areas of Weifang, and a joint pollution prevention and control mechanism is critical for controlling regional pollution.

ACS Style

Chengming Li; Zhaoxin Dai; Xiaoli Liu; Pengda Wu. Transport Pathways and Potential Source Region Contributions of PM2.5 in Weifang: Seasonal Variations. Applied Sciences 2020, 10, 2835 .

AMA Style

Chengming Li, Zhaoxin Dai, Xiaoli Liu, Pengda Wu. Transport Pathways and Potential Source Region Contributions of PM2.5 in Weifang: Seasonal Variations. Applied Sciences. 2020; 10 (8):2835.

Chicago/Turabian Style

Chengming Li; Zhaoxin Dai; Xiaoli Liu; Pengda Wu. 2020. "Transport Pathways and Potential Source Region Contributions of PM2.5 in Weifang: Seasonal Variations." Applied Sciences 10, no. 8: 2835.

Journal article
Published: 08 April 2020 in Sustainability
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Smart city evaluation is a critical component in smart city construction and plays an important role in guiding and promoting smart development of cities. Currently, existing research and applications of smart city evaluation are still in the exploration stage. They mainly focus on evaluation of one single aspect, use indicators with distinct regional characteristics and poor extensibility, and cannot be well-integrated with common and shareable smart city frameworks; these limitations have led to biased evaluation results. Based on a common and shareable smart city framework, this paper proposes a well-integrated, universal, strongly practical, and highly extensible evaluation system. Then, using the above-mentioned evaluation system, 17 smart cities in China are assessed. This application demonstrates that the evaluation system plays an important guiding role for better understanding the overall smart city platform construction situation in China, performing horizontal comparisons and establishing benchmarks among smart cities. Comparative analyses of indicators demonstrate that future smart city construction in China should pay more attention to novel innovations, the construction of dynamic information resources and spatiotemporal big data.

ACS Style

Chengming Li; Zhaoxin Dai; Xiaoli Liu; Wei Sun. Evaluation System: Evaluation of Smart City Shareable Framework and Its Applications in China. Sustainability 2020, 12, 2957 .

AMA Style

Chengming Li, Zhaoxin Dai, Xiaoli Liu, Wei Sun. Evaluation System: Evaluation of Smart City Shareable Framework and Its Applications in China. Sustainability. 2020; 12 (7):2957.

Chicago/Turabian Style

Chengming Li; Zhaoxin Dai; Xiaoli Liu; Wei Sun. 2020. "Evaluation System: Evaluation of Smart City Shareable Framework and Its Applications in China." Sustainability 12, no. 7: 2957.

Journal article
Published: 31 March 2020 in ISPRS International Journal of Geo-Information
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Point of interest (POI) matching is critical but is the most technically difficult part of multi-source POI fusion. The accurate matching of POIs from different sources is important for the effective reuse of POI data. However, the existing research on POI matching usually adopts weak constraints, which leads to a low POI matching accuracy. To address the shortcomings of previous studies, this paper proposes a POI matching method with multiple determination constraints. First, according to various attributes (name, class, and spatial location), a new calculation model considering spatial topology, name role labeling, and bottom-up class constraints is established. In addition, the optimal threshold values corresponding to the different attribute constraints are determined. Second, according to the multiattribute constraint values and optimal thresholds, a constraint model with multiple strict determination constraints is proposed. Finally, actual POI data from Baidu Map and Gaode Map in Dongying city is used to validate the method. Comparing to the existing method, the accuracy and recall of the proposed method increase 0.3% and 7.1%, respectively. The experimental results demonstrate that the proposed POI matching method attains a high matching accuracy and high feasibility.

ACS Style

Chengming Li; Li Liu; Zhaoxin Dai; Xiaoli Liu. Different Sourcing Point of Interest Matching Method Considering Multiple Constraints. ISPRS International Journal of Geo-Information 2020, 9, 214 .

AMA Style

Chengming Li, Li Liu, Zhaoxin Dai, Xiaoli Liu. Different Sourcing Point of Interest Matching Method Considering Multiple Constraints. ISPRS International Journal of Geo-Information. 2020; 9 (4):214.

Chicago/Turabian Style

Chengming Li; Li Liu; Zhaoxin Dai; Xiaoli Liu. 2020. "Different Sourcing Point of Interest Matching Method Considering Multiple Constraints." ISPRS International Journal of Geo-Information 9, no. 4: 214.

Journal article
Published: 26 November 2019 in ISPRS International Journal of Geo-Information
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Trajectory data include rich interactive information of humans. The correct identification of trips is the key to trajectory data mining and its application. A new method, multi-rule-constrained homomorphic linear clustering (MCHLC), is proposed to extract trips from raw trajectory data. From the perspective of the workflow, the MCHLC algorithm consists of three parts. The first part is to form the original sub-trajectory moving/stopping clusters, which are obtained by sequentially clustering trajectory elements of the same motion status. The second part is to determine and revise the motion status of the original sub-trajectory clusters by the speed, time duration, directional constraint, and contextual constraint to construct the stop/move model. The third part is to extract users’ trips by filtering the stop/move model using the following rules: distance rule, average speed rule, shortest path rule, and completeness rule, which are related to daily riding experiences. Verification of the new method is carried out with the shared electric bike trajectory data of one week in Tengzhou city, evaluated by three indexes (precision, recall, and F1-score). The experiment shows that the index values of the new algorithm are higher (above 93%) than those of the baseline methods, indicating that the new algorithm is better. Compared to the baseline velocity sequence linear clustering (VSLC) algorithm, the performance of the new algorithm is improved by approximately 10%, mainly owing to two factors, directional constraint and contextual constraint. The better experimental results indicate that the new algorithm is suitable to extract trips from the sparse trajectories of shared e-bikes and other transportation forms, which can provide technical support for urban hotspot detection and hot route identification.

ACS Style

Xiaoqian Cheng; Chengming Li; Weibing Du; Jianming Shen; Zhaoxin Dai. Trip Extraction of Shared Electric Bikes Based on Multi-Rule-Constrained Homomorphic Linear Clustering Algorithm. ISPRS International Journal of Geo-Information 2019, 8, 526 .

AMA Style

Xiaoqian Cheng, Chengming Li, Weibing Du, Jianming Shen, Zhaoxin Dai. Trip Extraction of Shared Electric Bikes Based on Multi-Rule-Constrained Homomorphic Linear Clustering Algorithm. ISPRS International Journal of Geo-Information. 2019; 8 (12):526.

Chicago/Turabian Style

Xiaoqian Cheng; Chengming Li; Weibing Du; Jianming Shen; Zhaoxin Dai. 2019. "Trip Extraction of Shared Electric Bikes Based on Multi-Rule-Constrained Homomorphic Linear Clustering Algorithm." ISPRS International Journal of Geo-Information 8, no. 12: 526.

Journal article
Published: 12 September 2019 in Sustainability
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Environmentally friendly shared transit systems have become ubiquitous at present. As a result, analyzing the ranges and tracts of human activities and gatherings based on bike share data is scientifically useful. This paper investigates the spatial and temporal travel characteristics of citizens based on real-time-extracted electric bikes (e-bikes) Global Positioning System (GPS) data from May to July in 2018 in the central area of Tengzhou City, Shandong Province, China. The research is conducive for the exploration of citizens’ changes in mobility behaviors, for the analysis of relationships between mobility changes and environmental or other possible factors, and for advancing policy proposals. The main conclusions of the study are as follows. First, in general, citizens’ travelling is featured by rides that are less than 10 min, shorter than 5 km, and with a speed between 5 km/h and 20 km/h. Second, in terms of temporal characteristics, monthly e-bike usage and citizens’ mobility are positively correlated with temperature in May and negatively correlated with temperature in July; an overall negative correlation is also manifested between the e-bike usage (mobility) and air quality index; daily usage reaches a trough on Tuesday and a peak on Friday, indicating the extent of mobility on respective days; e-bike usage and human outdoor behaviors are significantly lowered in rainy weather than in sunny weather; hourly rides reach a peak at 18:00 (more human activities) and a trough at 2:00 (less activities), and average hourly riding speed maximizes at 5:00 and minimizes around 8:00 and 17:00. Third, for spatial characteristics, destinations (D points) during morning rush hour and regions where e-bikes are densely employed are concentrated mainly in mid-north and middle parts of the central area (major human gatherings), and the rides have a diffusing pattern; e-bike origin–destination (O–D) trajectories radiate mostly towards the mid-north and the east during evening rush hour. In addition, 9.4% of the total trips to work areas during morning rush hour represent spillover commuting, indicating that separations between jobs and residential are not severe in the central area of Tengzhou City and commuting is relatively convenient.

ACS Style

Yixiao Li; Zhaoxin Dai; Lining Zhu; Xiaoli Liu. Analysis of Spatial and Temporal Characteristics of Citizens’ Mobility Based on E-Bike GPS Trajectory Data in Tengzhou City, China. Sustainability 2019, 11, 5003 .

AMA Style

Yixiao Li, Zhaoxin Dai, Lining Zhu, Xiaoli Liu. Analysis of Spatial and Temporal Characteristics of Citizens’ Mobility Based on E-Bike GPS Trajectory Data in Tengzhou City, China. Sustainability. 2019; 11 (18):5003.

Chicago/Turabian Style

Yixiao Li; Zhaoxin Dai; Lining Zhu; Xiaoli Liu. 2019. "Analysis of Spatial and Temporal Characteristics of Citizens’ Mobility Based on E-Bike GPS Trajectory Data in Tengzhou City, China." Sustainability 11, no. 18: 5003.

Historical article
Published: 27 August 2019 in International Journal of Environmental Research and Public Health
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Air pollution has become a severe threat and challenge in China. Focusing on air quality in a heavily polluted city (Weifang Cty), this study aims to investigate spatial and temporal distribution characteristics of air pollution and identify the influence of weather factors on primary pollutants in Weifang over a long period from 2014–2018. The results indicate the annual Air quality Index (AQI) in Weifang has decreased since 2014 but is still far from the standard for excellent air quality. The primary pollutants are O3 (Ozone), PM10 (Particles with aerodynamic diameter ≤10 µm), and PM2.5 (Particles with aerodynamic diameter ≤10 µm); the annual concentrations of PM10 and PM2.5 show a significant reduction but that of O3 is basically unchanged. Seasonally, PM10 and PM2.5 show a U-shaped pattern, while O3 exhibits inverted U-shaped variations, and different pollutants also present different characteristics daily. Spatially, O3 exhibits a high level in the central region and a low level in the rural areas, while PM10 and PM2.5 are high in the northwest and low in the southeast. Additionally, the concentration of pollutants is greatly affected by meteorological factors, with PM2.5 being negatively correlated with temperature and wind speed, while O3 is positively correlated with the temperature. This research investigated the spatiotemporal characteristics of the air pollution and provided important policy advice based on the findings, which can be used to mitigate air pollution.

ACS Style

Chengming Li; Zhaoxin Dai; Lina Yang; Zhaoting Ma. Spatiotemporal Characteristics of Air Quality across Weifang from 2014–2018. International Journal of Environmental Research and Public Health 2019, 16, 3122 .

AMA Style

Chengming Li, Zhaoxin Dai, Lina Yang, Zhaoting Ma. Spatiotemporal Characteristics of Air Quality across Weifang from 2014–2018. International Journal of Environmental Research and Public Health. 2019; 16 (17):3122.

Chicago/Turabian Style

Chengming Li; Zhaoxin Dai; Lina Yang; Zhaoting Ma. 2019. "Spatiotemporal Characteristics of Air Quality across Weifang from 2014–2018." International Journal of Environmental Research and Public Health 16, no. 17: 3122.

Journal article
Published: 12 August 2019 in Sustainability
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Smart City is a new concept that uses information and communication technology (ICT) to promote the smartification of urban construction, planning and services. Currently, a number of cities have conducted studies on smart cities, but they have mostly focused on analyzing the conceptual connotations or applications in specific domains and lack a shareable and integrated framework, which has led to significant barriers for individual smart projects. By analyzing the framework and applications of Smart City, this paper proposes a common, shareable and integrated conceptual framework. Then, based on this framework, it further proposes a unified portal platform that can balance multiple stakeholders, including the government, citizens and businesses, as well as for common, custom and other application modes. Finally, the implementation of Smart Weifang based on this platform is discussed. The applications indicate that this shareable platform can effectively eliminate the data and technological barriers between different smart city systems while also avoiding redundant financial investments. The investigation of this proposed framework and platform is highly significant for the unified construction of smart cities and the intensification of the hardware environment, thus representing a true achievement in the transition from ‘information islands’ to ‘information sharing and interconnection’ for urban informatization.

ACS Style

Chengming Li; Xiaoli Liu; Zhaoxin Dai; Zhanjie Zhao. Smart City: A Shareable Framework and Its Applications in China. Sustainability 2019, 11, 4346 .

AMA Style

Chengming Li, Xiaoli Liu, Zhaoxin Dai, Zhanjie Zhao. Smart City: A Shareable Framework and Its Applications in China. Sustainability. 2019; 11 (16):4346.

Chicago/Turabian Style

Chengming Li; Xiaoli Liu; Zhaoxin Dai; Zhanjie Zhao. 2019. "Smart City: A Shareable Framework and Its Applications in China." Sustainability 11, no. 16: 4346.

Journal article
Published: 07 March 2019 in Sustainability
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Location-based service (LBS) technologies provide a new perspective for the analysis of the spatiotemporal dynamics of urban systems. Previous studies have been performed using data from mobile communications, public transport vehicles (taxis and buses), wireless hotspots and shared bicycles. However, corresponding analyses based on shared electric bicycle (e-bike) have not yet been reported in the literature. Data cleaning and extraction of the origin-destination (O-D) are prerequisites for the study of the spatiotemporal patterns of urban systems. In this study, based on a dataset of a week of shared e-bike GPS data in the city of Tengzhou (Shandong Province), sparse characteristics of discontinuities and nonuniformities of the GPS trajectory and a lack of riding status are observed. Based on the characteristics and the actual road, we proposed a method for the extraction of O-D pairs for every trajectory segment from continuous and stateless trajectory GPS data. This method cleans the incomplete and invalid trajectory records, which is suitable for sparse trajectory data. A week of shared e-bike GPS data in Tengzhou is scrubbed and, by the sampling method, the extraction accuracy of 91% is verified. We provide preliminary cleaning rules for sparse trajectory shared e-bike data for the first time, which are highly reliable and suitable for data mining from other forms of sparse GPS trajectory data.

ACS Style

Chengming Li; Zhaoxin Dai; Weixiang Peng; Jianming Shen. Green Travel Mode: Trajectory Data Cleansing Method for Shared Electric Bicycles. Sustainability 2019, 11, 1429 .

AMA Style

Chengming Li, Zhaoxin Dai, Weixiang Peng, Jianming Shen. Green Travel Mode: Trajectory Data Cleansing Method for Shared Electric Bicycles. Sustainability. 2019; 11 (5):1429.

Chicago/Turabian Style

Chengming Li; Zhaoxin Dai; Weixiang Peng; Jianming Shen. 2019. "Green Travel Mode: Trajectory Data Cleansing Method for Shared Electric Bicycles." Sustainability 11, no. 5: 1429.

Research article
Published: 13 January 2019 in Transactions in GIS
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The extraction of partition lines for long and narrow patches (LN patches) is an important yet difficult problem in the generalization of thematic data. When current methods are used to process polygons with irregular shapes or complex branch convergence zones, the extracted line structural features tend to be inaccurate and topologically erroneous. In this article, we propose an improved partition lines extraction algorithm of constrained Delaunay triangulation to counter these issues. The proposed method aims to maintain consistency between the extracted line structure characteristics and the actual object structure, especially for complex branch convergence zones. First, we describe three types of aggregation patterns (Type A, B, and C aggregation zones) that occur in partition line extractions for LN patches of complex branch convergence zones using Delaunay triangulation. Then, a partition line extraction algorithm that accounts for the direction between the edges of triangles and the distance of nodes in aggregation zones is proposed. Finally, we test our method for a dataset relating to Guizhou Province, China. Compared with the current method that uses quantitative indicators and visualization, the results indicate that our method not only has applicability for simple situations but also is superior for preserving structural features of complex branch convergence zones.

ACS Style

Chengming Li; Zhaoxin Dai; Yong Yin; Pengda Wu. A method for the extraction of partition lines from long and narrow patches that account for structural features. Transactions in GIS 2019, 23, 349 -364.

AMA Style

Chengming Li, Zhaoxin Dai, Yong Yin, Pengda Wu. A method for the extraction of partition lines from long and narrow patches that account for structural features. Transactions in GIS. 2019; 23 (2):349-364.

Chicago/Turabian Style

Chengming Li; Zhaoxin Dai; Yong Yin; Pengda Wu. 2019. "A method for the extraction of partition lines from long and narrow patches that account for structural features." Transactions in GIS 23, no. 2: 349-364.

Journal article
Published: 08 October 2018 in Ecological Indicators
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This paper explores the urban land-use determinants of the urban heat island (UHI) in Beijing’s Olympic Area, using different statistical models, land surface temperatures (LST) derived from Landsat 8 remote sensing, and land-use data derived from 1-m high-resolution imagery. Data are captured over grids of different sizes. Spatial regressions are necessary to capture neighboring effects, particularly when the grid unit is small. Grass, trees, water bodies, and shades have all significant and negative effects on LST, whereas buildings, roads and other impervious surfaces have all significant and positive effects. The results also point to significant nonlinear and interaction effects of grass, trees and water, particularly when the grid cell size is small (60 m-90 m). Trees are found to be the most important predictor of LST. When the grids are smaller than 180 m, the indirect impacts are larger than the direct ones, whereas, the opposite takes place for larger grids. Because of their strong performance (R2 ranging from 0.839 to 0.970), the models can be used for predicting the impacts of land-use changes on the UHI and as tools for urban planning. Finally, extensive uncertainty and sensitivity analyses show that the models are very reliable in terms of both input data accuracy and estimated coefficients precision.

ACS Style

Zhaoxin Dai; Jean-Michel Guldmann; Yunfeng Hu. Thermal impacts of greenery, water, and impervious structures in Beijing’s Olympic area: A spatial regression approach. Ecological Indicators 2018, 97, 77 -88.

AMA Style

Zhaoxin Dai, Jean-Michel Guldmann, Yunfeng Hu. Thermal impacts of greenery, water, and impervious structures in Beijing’s Olympic area: A spatial regression approach. Ecological Indicators. 2018; 97 ():77-88.

Chicago/Turabian Style

Zhaoxin Dai; Jean-Michel Guldmann; Yunfeng Hu. 2018. "Thermal impacts of greenery, water, and impervious structures in Beijing’s Olympic area: A spatial regression approach." Ecological Indicators 97, no. : 77-88.

Journal article
Published: 21 August 2018 in Sustainability
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Air pollution, which accompanies industrial progression and urbanization, has become an urgent issue to address in contemporary society. As a result, our understanding and continued study of the spatial-temporal characteristics of a major pollutant, defined as 2.5-micron or less particulate matter (PM2.5), as well as the development of related approaches to improve the environment, has become vital. This paper studies the characteristics of yearly, quarterly, monthly, daily, and hourly PM2.5 concentrations, and discusses the influencing factors based on the hourly data of nationally controlled and provincially controlled monitoring stations, from 2012 to 2016, in Weifang City. The main conclusion of this study is that the annual PM2.5 concentrations reached a peak in 2013. With efficient aid from the government, this value has decreased annually and has high spatial characteristics in the northwest and low spatial characteristics in the southeast. Second, the seasonal and monthly PM2.5 concentrations form a U-shaped trend, meaning that the concentration is high in the summer and low in the winter. These trends are highly relevant to the factors of plantation, humidity, temperature, and precipitation. Third, within a week, higher PM2.5 concentrations appear on Mondays and Saturdays, whereas the lowest concentration occurs on Wednesdays. It can be inferred that PM2.5 concentrations tend to be highly dependent on human activities and living habits. Lastly, there are hourly discrepancies within the peaks and troughs depending on the month, and the overall daytime PM2.5 concentrations and reductive rates are higher in the daytime than in the nighttime.

ACS Style

Yixiao Li; Zhaoxin Dai; Xianlin Liu. Analysis of Spatial-Temporal Characteristics of the PM2.5 Concentrations in Weifang City, China. Sustainability 2018, 10, 2960 .

AMA Style

Yixiao Li, Zhaoxin Dai, Xianlin Liu. Analysis of Spatial-Temporal Characteristics of the PM2.5 Concentrations in Weifang City, China. Sustainability. 2018; 10 (9):2960.

Chicago/Turabian Style

Yixiao Li; Zhaoxin Dai; Xianlin Liu. 2018. "Analysis of Spatial-Temporal Characteristics of the PM2.5 Concentrations in Weifang City, China." Sustainability 10, no. 9: 2960.