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Urban modeling and visualization are highly useful in the development of smart cities. Buildings are the most prominent features in the urban environment, and are necessary for urban decision support; thus, buildings should be modeled effectively and efficiently in three dimensions (3D). In this study, with the help of Gaofen-7 (GF-7) high-resolution stereo mapping satellite double-line camera (DLC) images and multispectral (MUX) images, the boundary of a building is segmented via a multilevel features fusion network (MFFN). A digital surface model (DSM) is generated to obtain the elevation of buildings. The building vector with height information is processed using a 3D modeling tool to create a white building model. The building model, DSM, and multispectral fused image are then imported into the Unreal Engine 4 (UE4) to complete the urban scene level, vividly rendered with environmental effects for urban visualization. The results of this study show that high accuracy of 95.29% is achieved in building extraction using our proposed method. Based on the extracted building vector and elevation information from the DSM, building 3D models can be efficiently created in Level of Details 1 (LOD1). Finally, the urban scene is produced for realistic 3D visualization. This study shows that high-resolution stereo mapping satellite images are useful in 3D modeling for urban buildings and can support the generation and visualization of urban scenes in a large area for different applications.
Heng Luo; Biao He; Renzhong Guo; Weixi Wang; Xi Kuai; Bilu Xia; Yuan Wan; Ding Ma; Linfu Xie. Urban Building Extraction and Modeling Using GF-7 DLC and MUX Images. Remote Sensing 2021, 13, 3414 .
AMA StyleHeng Luo, Biao He, Renzhong Guo, Weixi Wang, Xi Kuai, Bilu Xia, Yuan Wan, Ding Ma, Linfu Xie. Urban Building Extraction and Modeling Using GF-7 DLC and MUX Images. Remote Sensing. 2021; 13 (17):3414.
Chicago/Turabian StyleHeng Luo; Biao He; Renzhong Guo; Weixi Wang; Xi Kuai; Bilu Xia; Yuan Wan; Ding Ma; Linfu Xie. 2021. "Urban Building Extraction and Modeling Using GF-7 DLC and MUX Images." Remote Sensing 13, no. 17: 3414.
An easement is an important usufructuary right, and its main purpose is that one party wants to use the property of others to improve the benefits and interests of his own real estate. Because of the increasing population and accelerating urbanization urban planners have focused on the development and utilization of three-dimensional urban space, namely, underground, near ground and aboveground space, to use the spatial resources fully. Therefore, jurisprudence-confined planar easement must be combined with spatial information from two dimensions (2D) to three dimensions (3D), as well as 2D property boundaries to be extended to 3D to adapt to urban development. This paper focuses on the easement of access, which is the right to cross the property to go to and from another, under the context of 3D cadastres. The model of easement spatialization based on BIM (Building Information Model) specified by IFC (Industry Foundation Class) standards is constructed and analysed. The servient owner and the dominant owner of the easement can be linked because they are both attached to the same physical space. This paper takes a multistory building having individually owned condominium units as an example to demonstrate how to access the semantic information associated with the geometric information of 3D property objects in the BIM/IFC. The research results show that BIM/IFC can optimize the complex presentation of 3D property attributes and is an effective carrier of easement spatialization. The combination of legal information and spatial information of 3D properties not only optimizes the operation and maintenance of buildings but also improves land management and accelerates the development of 3D cities.
Shen Ying; Yifan Xu; Chengpeng Li; Renzhong Guo; Lin Li. Easement spatialization with two cases based on LADM and BIM. Land Use Policy 2021, 109, 105641 .
AMA StyleShen Ying, Yifan Xu, Chengpeng Li, Renzhong Guo, Lin Li. Easement spatialization with two cases based on LADM and BIM. Land Use Policy. 2021; 109 ():105641.
Chicago/Turabian StyleShen Ying; Yifan Xu; Chengpeng Li; Renzhong Guo; Lin Li. 2021. "Easement spatialization with two cases based on LADM and BIM." Land Use Policy 109, no. : 105641.
A country can be well-comprehended through its core cities. Similarly, we can learn about a city from its hotspots, as they manifest the concentration of urban infrastructures and human activities. Following this philosophy, this paper studies the intra-urban form and function from a complexity science perspective by exploring the power law distribution of hotspot sizes and related socio-economic attributes. To detect hotspots, we rely on spatial clustering of geospatial big data sets, including street data from OpenStreetMap platform and nighttime light (NTL) data from the visible infrared imaging radiometer suite (VIIRS) imagery. Unlike conventional spatial units, which are imposed by governments or authorities (such as census block), the delineation of hotspots is done in a totally bottom-up manner and, more importantly, can help us examine precisely the scaling pattern of urban morphological and functional aspects. This results in two types of urban hotspots—street-based and NTL-based hotspots—being generated across 20 major cities in China. We find that Zipf’s law of hotspot sizes (both types) holds remarkably well for each city, as do the city-size distributions at the country level, indicating a statistically self-similar structure of geographic space. We further find that the urban scaling law can be effectively detected when using NTL-based hotspots as basic units. Furthermore, the comparison between two types of hotspots enables us to gain in-depth insights of urban planning and urban economic development.
Ding Ma; Renzhong Guo; Ying Jing; Ye Zheng; Zhigang Zhao; Jiahao Yang. Intra-Urban Scaling Properties Examined by Automatically Extracted City Hotspots from Street Data and Nighttime Light Imagery. Remote Sensing 2021, 13, 1322 .
AMA StyleDing Ma, Renzhong Guo, Ying Jing, Ye Zheng, Zhigang Zhao, Jiahao Yang. Intra-Urban Scaling Properties Examined by Automatically Extracted City Hotspots from Street Data and Nighttime Light Imagery. Remote Sensing. 2021; 13 (7):1322.
Chicago/Turabian StyleDing Ma; Renzhong Guo; Ying Jing; Ye Zheng; Zhigang Zhao; Jiahao Yang. 2021. "Intra-Urban Scaling Properties Examined by Automatically Extracted City Hotspots from Street Data and Nighttime Light Imagery." Remote Sensing 13, no. 7: 1322.
Three-dimensional (3D) building models play an important role in digital cities and have numerous potential applications in environmental studies. In recent years, the photogrammetric point clouds obtained by aerial oblique images have become a major source of data for 3D building reconstruction. Aiming at reconstructing a 3D building model at Level of Detail (LoD) 2 and even LoD3 with preferred geometry accuracy and affordable computation expense, in this paper, we propose a novel method for the efficient reconstruction of building models from the photogrammetric point clouds which combines the rule-based and the hypothesis-based method using a two-stage topological recovery process. Given the point clouds of a single building, planar primitives and their corresponding boundaries are extracted and regularized to obtain abstracted building counters. In the first stage, we take advantage of the regularity and adjacency of the building counters to recover parts of the topological relationships between different primitives. Three constraints, namely pairwise constraint, triplet constraint, and nearby constraint, are utilized to form an initial reconstruction with candidate faces in ambiguous areas. In the second stage, the topologies in ambiguous areas are removed and reconstructed by solving an integer linear optimization problem based on the initial constraints while considering data fitting degree. Experiments using real datasets reveal that compared with state-of-the-art methods, the proposed method can efficiently reconstruct 3D building models in seconds with the geometry accuracy in decimeter level.
Linfu Xie; Han Hu; Qing Zhu; XiaoMing Li; Shengjun Tang; You Li; Renzhong Guo; Yeting Zhang; Weixi Wang. Combined Rule-Based and Hypothesis-Based Method for Building Model Reconstruction from Photogrammetric Point Clouds. Remote Sensing 2021, 13, 1107 .
AMA StyleLinfu Xie, Han Hu, Qing Zhu, XiaoMing Li, Shengjun Tang, You Li, Renzhong Guo, Yeting Zhang, Weixi Wang. Combined Rule-Based and Hypothesis-Based Method for Building Model Reconstruction from Photogrammetric Point Clouds. Remote Sensing. 2021; 13 (6):1107.
Chicago/Turabian StyleLinfu Xie; Han Hu; Qing Zhu; XiaoMing Li; Shengjun Tang; You Li; Renzhong Guo; Yeting Zhang; Weixi Wang. 2021. "Combined Rule-Based and Hypothesis-Based Method for Building Model Reconstruction from Photogrammetric Point Clouds." Remote Sensing 13, no. 6: 1107.
Indoor positioning is of great importance in the era of mobile computing. Currently, considerable focus has been on RSS-based locations because they can provide position information without additional equipment. However, this method suffers from two challenges: (1) fingerprint ambiguity and (2) labour-intensive fingerprint collection. To overcome these drawbacks, we provide a near relation-based indoor positioning method under a sparse Wi-Fi fingerprint. To effectively obtain the fingerprint database, certain interpolation methods are used to enrich sparse Wi-Fi fingerprints. A near relation boundary is provided, and Wi-Fi fingerprints are constrained to this region to reduce fingerprint ambiguity, which can also improve the efficiency of fingerprint matching. Extensive experiments show that the kriging interpolation method performs well, and a positioning accuracy of 2.86 m can be achieved with a near relation under a 1 m interpolation density.
Yankun Wang; Renzhong Guo; Weixi Wang; XiaoMing Li; Shengjun Tang; Wei Zhang; Luyao Wang; Liang Chen; You Li; Wenqun Xiu. Near Relation-Based Indoor Positioning Method under Sparse Wi-Fi Fingerprints. ISPRS International Journal of Geo-Information 2020, 9, 714 .
AMA StyleYankun Wang, Renzhong Guo, Weixi Wang, XiaoMing Li, Shengjun Tang, Wei Zhang, Luyao Wang, Liang Chen, You Li, Wenqun Xiu. Near Relation-Based Indoor Positioning Method under Sparse Wi-Fi Fingerprints. ISPRS International Journal of Geo-Information. 2020; 9 (12):714.
Chicago/Turabian StyleYankun Wang; Renzhong Guo; Weixi Wang; XiaoMing Li; Shengjun Tang; Wei Zhang; Luyao Wang; Liang Chen; You Li; Wenqun Xiu. 2020. "Near Relation-Based Indoor Positioning Method under Sparse Wi-Fi Fingerprints." ISPRS International Journal of Geo-Information 9, no. 12: 714.
Location-based social media have facilitated us to bridge the gap between virtual and physical worlds through the exploration of human online dynamics from a geographic perspective. This study uses a large collection of geotagged photos from Flickr to investigate the complexity of spatial interactions at the country level. We adopted three levels of administrative divisions in mainland China—province, city, and county—as basic geographic units and established three types of topology—province–province network, city–city network, and county–county network—from the extracted user movement trajectories. We conducted the scaling analysis based on heavy-tailed distribution statistics including power law exponents, goodness of fit index, and ht-index, by which we characterized a great complexity of the trajectory lengths, spatial distribution of geotagged photos, and the related metrics of built networks. The great complexity indicates the highly imbalanced ratio of populated-to-unpopulated areas or large-to-small flows between areas. More interestingly, all power law exponents were around 2 for the networks at various spatial and temporal scales. Such a recurrence of scaling statistics at multiple resolutions can be regarded a statistical self-similarity and could thus help us to reveal the fractal nature of human mobility patterns.
Wei Zhu; Ding Ma; Zhigang Zhao; Renzhong Guo. Investigating the Complexity of Spatial Interactions between Different Administrative Units in China Using Flickr Data. Sustainability 2020, 12, 9778 .
AMA StyleWei Zhu, Ding Ma, Zhigang Zhao, Renzhong Guo. Investigating the Complexity of Spatial Interactions between Different Administrative Units in China Using Flickr Data. Sustainability. 2020; 12 (22):9778.
Chicago/Turabian StyleWei Zhu; Ding Ma; Zhigang Zhao; Renzhong Guo. 2020. "Investigating the Complexity of Spatial Interactions between Different Administrative Units in China Using Flickr Data." Sustainability 12, no. 22: 9778.
Map generalization is a process of reducing the contents of a map or data to properly show a geographic feature(s) at a smaller extent. Over the past few years, the fractal way of thinking has emerged as a new paradigm for map generalization. A geographic feature can be deemed as a fractal given the perspective of scaling, as its rough, irregular, and unsmooth shape inherently holds a striking scaling hierarchy of far more small elements than large ones. The pattern of far more small things than large ones is a de facto heavy tailed distribution. In this paper, we apply the scaling hierarchy for map generalization to polygonal features. To do this, we firstly revisit the scaling hierarchy of a classic fractal: the Koch Snowflake. We then review previous work that used the Douglas–Peuker algorithm, which identifies characteristic points on a line to derive three types of measures that are long-tailed distributed: the baseline length (d), the perpendicular distance to the baseline (x), and the area formed by x and d (area). More importantly, we extend the usage of the three measures to other most popular cartographical generalization methods; i.e., the bend simplify method, Visvalingam–Whyatt method, and hierarchical decomposition method, each of which decomposes any polygon into a set of bends, triangles, or convex hulls as basic geometric units for simplification. The different levels of details of the polygon can then be derived by recursively selecting the head part of geometric units and omitting the tail part using head/tail breaks, which is a new classification scheme for data with a heavy-tailed distribution. Since there are currently few tools with which to readily conduct the polygon simplification from such a fractal perspective, we have developed PolySimp, a tool that integrates the mentioned four algorithms for polygon simplification based on its underlying scaling hierarchy. The British coastline was selected to demonstrate the tool’s usefulness. The developed tool can be expected to showcase the applicability of fractal way of thinking and contribute to the development of map generalization.
Ding Ma; Zhigang Zhao; Ye Zheng; Renzhong Guo; Wei Zhu. PolySimp: A Tool for Polygon Simplification Based on the Underlying Scaling Hierarchy. ISPRS International Journal of Geo-Information 2020, 9, 594 .
AMA StyleDing Ma, Zhigang Zhao, Ye Zheng, Renzhong Guo, Wei Zhu. PolySimp: A Tool for Polygon Simplification Based on the Underlying Scaling Hierarchy. ISPRS International Journal of Geo-Information. 2020; 9 (10):594.
Chicago/Turabian StyleDing Ma; Zhigang Zhao; Ye Zheng; Renzhong Guo; Wei Zhu. 2020. "PolySimp: A Tool for Polygon Simplification Based on the Underlying Scaling Hierarchy." ISPRS International Journal of Geo-Information 9, no. 10: 594.
A heavy workload is required for sample collection for urban land use classification, and researchers are in urgent need of sampling strategies as a guide to achieve more effective work. In this paper, we make use of an urban land use survey to obtain a complete sample set of a city, test the impact of different training and validation sample sizes on the accuracy, and summarize the sampling strategy. The following conclusions are drawn based on our systematic analysis in Shenzhen. (1) For the best classification accuracy, the number of training samples should be no less than 40% of the total number of parcels or no less than 5500 parcels. For the best labor cost performance, the number should be no less than 7% or no less than 900. (2) The accuracy evaluation is stable and reliable and requires validation sample numbers of no less than 10% of the total or no less than 1200. (3) Samples with a purity of 60–90% are preferred, and the classification effectiveness is better in samples with a purity greater than 90% under the same number. (4) If spatial equilibrium sampling cannot be carried out, sampling areas with complex land use patterns should be preferred.
Mo Su; Renzhong Guo; Bin Chen; Wuyang Hong; Jiaqi Wang; Yimei Feng; Bing Xu. Sampling Strategy for Detailed Urban Land Use Classification: A Systematic Analysis in Shenzhen. Remote Sensing 2020, 12, 1497 .
AMA StyleMo Su, Renzhong Guo, Bin Chen, Wuyang Hong, Jiaqi Wang, Yimei Feng, Bing Xu. Sampling Strategy for Detailed Urban Land Use Classification: A Systematic Analysis in Shenzhen. Remote Sensing. 2020; 12 (9):1497.
Chicago/Turabian StyleMo Su; Renzhong Guo; Bin Chen; Wuyang Hong; Jiaqi Wang; Yimei Feng; Bing Xu. 2020. "Sampling Strategy for Detailed Urban Land Use Classification: A Systematic Analysis in Shenzhen." Remote Sensing 12, no. 9: 1497.
Urban form can be reflected by many city elements, such as streets. A street network serves as the backbone of a city and reflects a city’s physical structure. A street network’s topological measures and statistical distributions have been widely investigated in recent years, but previous studies have seldom characterized the heavy-tailed distribution of street connectivities from a fractal perspective. The long-tail distribution of street connectivities can be fractal under the new, third definition: a set or pattern is fractal if the scaling of far more small things than large ones recurs at least twice. The number of recurred scaling patterns of far more less-connected streets than well-connected ones greatly helps in measuring the scaling hierarchy of a street network. Moreover, it enables us to examine the potential fractality of urban street networks at the national scale. In this connection, the present study aims to contribute to urban morphology in China through the investigation of the ubiquity of fractal cities from the lens of street networks. To do this, we generate hundreds of thousands of natural streets from about 4.5 million street segments over 298 Chinese cities and adopted power-law detection as well as three fractal metrics that emerged from the third definition of fractal. The results show that almost all cities bear a fractal structure in terms of street connectivities. Furthermore, our multiple regression analysis suggests that the fractality of street networks is positively correlated with urban socioeconomic status and negatively correlated with energy consumption. Therefore, the fractal metrics can be a useful supplement to traditional street-network configuration measures such as street lengths.
Ding Ma; Renzhong Guo; Ye Zheng; Zhigang Zhao; Fangning He; Wei Zhu. Understanding Chinese Urban Form: The Universal Fractal Pattern of Street Networks over 298 Cities. ISPRS International Journal of Geo-Information 2020, 9, 192 .
AMA StyleDing Ma, Renzhong Guo, Ye Zheng, Zhigang Zhao, Fangning He, Wei Zhu. Understanding Chinese Urban Form: The Universal Fractal Pattern of Street Networks over 298 Cities. ISPRS International Journal of Geo-Information. 2020; 9 (4):192.
Chicago/Turabian StyleDing Ma; Renzhong Guo; Ye Zheng; Zhigang Zhao; Fangning He; Wei Zhu. 2020. "Understanding Chinese Urban Form: The Universal Fractal Pattern of Street Networks over 298 Cities." ISPRS International Journal of Geo-Information 9, no. 4: 192.
Georeferencing by place names (known as toponyms) is the most common way of associating textual information with geographic locations. While computers use numeric coordinates (such as longitude-latitude pairs) to represent places, people generally refer to places via their toponyms. Query by toponym is an effective way to find information about a geographic area. However, segmenting and parsing textual addresses to extract local toponyms is a difficult task in the geocoding field, especially in China. In this paper, a local spatial context-based framework is proposed to extract local toponyms and segment Chinese textual addresses. We collect urban points of interest (POIs) as an input data source; in this dataset, the textual address and geospatial position coordinates correspond at a one-to-one basis and can be easily used to explore the spatial distribution of local toponyms. The proposed framework involves two steps: address element identification and local toponym extraction. The first step identifies as many address element candidates as possible from a continuous string of textual addresses for each urban POI. The second step focuses on merging neighboring candidate pairs into local toponyms. A series of experiments are conducted to determine the thresholds for local toponym extraction based on precision-recall curves. Finally, we evaluate our framework by comparing its performance with three well-known Chinese word segmentation models. The comparative experimental results demonstrate that our framework achieves a better performance than do other models.
Xi Kuai; Renzhong Guo; Zhijun Zhang; Biao He; Zhigang Zhao; Han Guo. Spatial Context-Based Local Toponym Extraction and Chinese Textual Address Segmentation from Urban POI Data. ISPRS International Journal of Geo-Information 2020, 9, 147 .
AMA StyleXi Kuai, Renzhong Guo, Zhijun Zhang, Biao He, Zhigang Zhao, Han Guo. Spatial Context-Based Local Toponym Extraction and Chinese Textual Address Segmentation from Urban POI Data. ISPRS International Journal of Geo-Information. 2020; 9 (3):147.
Chicago/Turabian StyleXi Kuai; Renzhong Guo; Zhijun Zhang; Biao He; Zhigang Zhao; Han Guo. 2020. "Spatial Context-Based Local Toponym Extraction and Chinese Textual Address Segmentation from Urban POI Data." ISPRS International Journal of Geo-Information 9, no. 3: 147.
Nowadays, mobile laser scanning is widely used for understanding urban scenes, especially for extraction and recognition of pole-like street furniture, such as lampposts, traffic lights and traffic signs. However, the start-of-art methods may generate low segmentation accuracy in the overlapping scenes, and the object classification accuracy can be highly influenced by the large discrepancy in instance number of different objects in the same scene. To address these issues, we present a complete paradigm for pole-like street furniture segmentation and classification using mobile LiDAR (light detection and ranging) point cloud. First, we propose a 3D density-based segmentation algorithm which considers two different conditions including isolated furniture and connected furniture in overlapping scenes. After that, a vertical region grow algorithm is employed for component splitting and a new shape distribution estimation method is proposed to obtain more accurate global shape descriptors. For object classification, an integrated shape constraint based on the splitting result of pole-like street furniture (SplitISC) is introduced and integrated into a retrieval procedure. Two test datasets are used to verify the performance and effectiveness of the proposed method. The experimental results demonstrate that the proposed method can achieve better classification results from both sites than the existing shape distribution method.
You Li; Weixi Wang; XiaoMing Li; Linfu Xie; Yankun Wang; Renzhong Guo; Wenqun Xiu; Shengjun Tang. Pole-Like Street Furniture Segmentation and Classification in Mobile LiDAR Data by Integrating Multiple Shape-Descriptor Constraints. Remote Sensing 2019, 11, 2920 .
AMA StyleYou Li, Weixi Wang, XiaoMing Li, Linfu Xie, Yankun Wang, Renzhong Guo, Wenqun Xiu, Shengjun Tang. Pole-Like Street Furniture Segmentation and Classification in Mobile LiDAR Data by Integrating Multiple Shape-Descriptor Constraints. Remote Sensing. 2019; 11 (24):2920.
Chicago/Turabian StyleYou Li; Weixi Wang; XiaoMing Li; Linfu Xie; Yankun Wang; Renzhong Guo; Wenqun Xiu; Shengjun Tang. 2019. "Pole-Like Street Furniture Segmentation and Classification in Mobile LiDAR Data by Integrating Multiple Shape-Descriptor Constraints." Remote Sensing 11, no. 24: 2920.
Evaluation of the railway network distribution and its impacts on social and economic development has great significance for building an efficient and comprehensive railway system. To address the lack of evaluation indicators to assess the railway network distribution pattern at the macro scale, this study selects eight indicators—railway network density, railway network proximity, the shortest travel time, train frequency, population, Gross Domestic Product (GDP), the gross industrial value above designated size, and fixed asset investment—as the basis of an integrated railway network distribution index which is used to characterize China’s railway network distribution using geographical information system (GIS) technology. The research shows that, in 2015, the railway network distribution was low in almost half of China’s counties and that there were obvious differences in distribution between counties in the east and west. In addition, multiple dense areas of railway network distribution were identified. The results suggest that it might be advisable to strengthen the connections between large and small cities in the eastern region and that the major urban agglomerations in the midwest could focus on strengthening the construction of railway facilities to increase the urban vitality of the western region. This study can be used to guide the optimization of railway network structures and provide a macro decision-making reference for the planning and evaluation of major railway projects in China.
Minmin Li; Renzhong Guo; You Li; Biao He; Yong Fan. The Distribution Pattern of the Railway Network in China at the County Level. ISPRS International Journal of Geo-Information 2019, 8, 336 .
AMA StyleMinmin Li, Renzhong Guo, You Li, Biao He, Yong Fan. The Distribution Pattern of the Railway Network in China at the County Level. ISPRS International Journal of Geo-Information. 2019; 8 (8):336.
Chicago/Turabian StyleMinmin Li; Renzhong Guo; You Li; Biao He; Yong Fan. 2019. "The Distribution Pattern of the Railway Network in China at the County Level." ISPRS International Journal of Geo-Information 8, no. 8: 336.
Dengue fever is one of the most common vector-borne diseases in the world and is mainly affected by the interaction of meteorological, human and land-use factors. This study aims to identify the impact of meteorological, human and land-use factors on dengue fever cases, involving the interplay between multiple factors. The analyses identified the statistically significant determinants affecting the transmission of dengue fever, employing cross-correlation analysis and the geo-detector model. This study was conducted in Guangzhou, China, using the data of confirmed cases of dengue fever, daily meteorological records, population density distribution and land-use distribution. The findings highlighted that the dengue fever hotspots were mainly distributed in the old city center of Guangzhou and were significantly shaped by meteorological, land-use and human factors. Meteorological factors including minimum temperature, maximum temperature, atmospheric pressure and relative humidity were correlated with the transmission of dengue fever. Minimum temperature, maximum temperature and relative humidity presented a statistically significant positive correlation with dengue fever cases, while atmospheric pressure presented statistically significant negative correlation. Minimum temperature, maximum temperature, atmospheric pressure and humidity have lag effects on the transmission of dengue fever. The population, community age, subway network density, road network density and ponds presented a statistically significant positive correlation with the number of dengue fever cases, and the interaction among land-use and human factors could enhance dengue fever transmission. The ponds were the most important interaction factors, which might strengthen the influence of other factors on dengue fever transmission. Our findings have implications for pre-emptive dengue fever control.
Yebin Chen; Zhigang Zhao; Zhichao Li; Weihong Li; Zhipeng Li; Renzhong Guo; Zhilu Yuan. Spatiotemporal Transmission Patterns and Determinants of Dengue Fever: A Case Study of Guangzhou, China. International Journal of Environmental Research and Public Health 2019, 16, 2486 .
AMA StyleYebin Chen, Zhigang Zhao, Zhichao Li, Weihong Li, Zhipeng Li, Renzhong Guo, Zhilu Yuan. Spatiotemporal Transmission Patterns and Determinants of Dengue Fever: A Case Study of Guangzhou, China. International Journal of Environmental Research and Public Health. 2019; 16 (14):2486.
Chicago/Turabian StyleYebin Chen; Zhigang Zhao; Zhichao Li; Weihong Li; Zhipeng Li; Renzhong Guo; Zhilu Yuan. 2019. "Spatiotemporal Transmission Patterns and Determinants of Dengue Fever: A Case Study of Guangzhou, China." International Journal of Environmental Research and Public Health 16, no. 14: 2486.
Lampposts, traffic lights, traffic signs, utility poles and so forth are important road furniture in urban areas. The fast and accurate localization and extraction of this type of furniture is urgent for the construction and updating of infrastructure databases in cities. This paper proposes a pipeline for mobile laser scanning data processing to locate and extract road poles. The proposed method is based on the vertical continuity with isolation feature of the pole part and the overall roughness feature of the attachment part of road poles. The isolation feature of the pole part is analysed by constructing two concentric cylinders from bottom to top and there should be no or a limited number of, points between these two cylinders. After splitting up the pole part and the attachment part of a road pole, the roughness of the candidate attachment points is computed and the attachment is obtained by performing region growing method based on roughness values. By applying the proposed pipeline to different situations in two datasets, the proposed method proves to be efficient not only in simple scenes but also in cluttered scenes.
You Li; Weixi Wang; Shengjun Tang; Dalin Li; Yankun Wang; Zhilu Yuan; Renzhong Guo; XiaoMing Li; Wenqun Xiu. Localization and Extraction of Road Poles in Urban Areas from Mobile Laser Scanning Data. Remote Sensing 2019, 11, 401 .
AMA StyleYou Li, Weixi Wang, Shengjun Tang, Dalin Li, Yankun Wang, Zhilu Yuan, Renzhong Guo, XiaoMing Li, Wenqun Xiu. Localization and Extraction of Road Poles in Urban Areas from Mobile Laser Scanning Data. Remote Sensing. 2019; 11 (4):401.
Chicago/Turabian StyleYou Li; Weixi Wang; Shengjun Tang; Dalin Li; Yankun Wang; Zhilu Yuan; Renzhong Guo; XiaoMing Li; Wenqun Xiu. 2019. "Localization and Extraction of Road Poles in Urban Areas from Mobile Laser Scanning Data." Remote Sensing 11, no. 4: 401.
Semantically rich indoor models are increasingly used throughout a facility’s life cycle for different applications. With the decreasing price of 3D sensors, it is convenient to acquire point cloud data from consumer-level scanners. However, most existing methods in 3D indoor reconstruction from point clouds involve a tedious manual or interactive process due to line-of-sight occlusions and complex space structures. Using the multiple types of data obtained by RGB-D devices, this paper proposes a fast and automatic method for reconstructing semantically rich indoor 3D building models from low-quality RGB-D sequences. Our method is capable of identifying and modelling the main structural components of indoor environments such as space, wall, floor, ceilings, windows, and doors from the RGB-D datasets. The method includes space division and extraction, opening extraction, and global optimization. For space division and extraction, rather than distinguishing room spaces based on the detected wall planes, we interactively define the start-stop position for each functional space (e.g., room, corridor, kitchen) during scanning. Then, an interior elements filtering algorithm is proposed for wall component extraction and a boundary generation algorithm is used for space layout determination. For opening extraction, we propose a new noise robustness method based on the properties of convex hull, octrees structure, Euclidean clusters and the camera trajectory for opening generation, which is inapplicable to the data collected in the indoor environments due to inevitable occlusion. A global optimization approach for planes is designed to eliminate the inconsistency of planes sharing the same global plane, and maintain plausible connectivity between the walls and the relationships between the walls and openings. The final model is stored according to the CityGML3.0 standard. Our approach allows for the robust generation of semantically rich 3D indoor models and has strong applicability and reconstruction power for complex real-world datasets.
Shengjun Tang; Yunjie Zhang; You Li; Zhilu Yuan; Yankun Wang; Xiang Zhang; XiaoMing Li; Yeting Zhang; Renzhong Guo; Weixi Wang. Fast and Automatic Reconstruction of Semantically Rich 3D Indoor Maps from Low-quality RGB-D Sequences. Sensors 2019, 19, 533 .
AMA StyleShengjun Tang, Yunjie Zhang, You Li, Zhilu Yuan, Yankun Wang, Xiang Zhang, XiaoMing Li, Yeting Zhang, Renzhong Guo, Weixi Wang. Fast and Automatic Reconstruction of Semantically Rich 3D Indoor Maps from Low-quality RGB-D Sequences. Sensors. 2019; 19 (3):533.
Chicago/Turabian StyleShengjun Tang; Yunjie Zhang; You Li; Zhilu Yuan; Yankun Wang; Xiang Zhang; XiaoMing Li; Yeting Zhang; Renzhong Guo; Weixi Wang. 2019. "Fast and Automatic Reconstruction of Semantically Rich 3D Indoor Maps from Low-quality RGB-D Sequences." Sensors 19, no. 3: 533.
As complex systems, the spatial structure of urban systems can be analyzed by entropy theory. This paper first calculates the interaction force between cities based on the gravity model, the spatial relationship matrix between cities is constructed using the method of network modeling, and the spatial network modeling of urban system can be calculated. Secondly, the Efficiency Entropy (EE), Quality Entropy (QE), and System Entropy (SE) of urban system network are calculated and analyzed by information entropy. Finally, taking the Huaihe River Basin (HRB) as a case study, model verification and empirical analysis are performed. It is found that the spatio–temporal pattern of the urban system network structure in the basin is uneven: in space, the urban system network in the HRB presents a layer-by-layer spatial distribution centered on the core city of Xuzhou; meanwhile, the overall urban system network in the basin presents an orderly development trend. This study has certain theoretical and practical value for the planning of urban and urban systems and the coordinated development of regions.
Yong Fan; Renzhong Guo; Zongyi He; Minmin Li; Biao He; Hao Yang; Nu Wen. Spatio–Temporal Pattern of the Urban System Network in the Huaihe River Basin Based on Entropy Theory. Entropy 2018, 21, 20 .
AMA StyleYong Fan, Renzhong Guo, Zongyi He, Minmin Li, Biao He, Hao Yang, Nu Wen. Spatio–Temporal Pattern of the Urban System Network in the Huaihe River Basin Based on Entropy Theory. Entropy. 2018; 21 (1):20.
Chicago/Turabian StyleYong Fan; Renzhong Guo; Zongyi He; Minmin Li; Biao He; Hao Yang; Nu Wen. 2018. "Spatio–Temporal Pattern of the Urban System Network in the Huaihe River Basin Based on Entropy Theory." Entropy 21, no. 1: 20.
With the accelerating urbanization process, the population increasingly concentrates in urban areas. In view of the huge population in China and a series of problems in the process of rapid urbanization, there are no unified measures for characterizing the population pattern. This study explores the distribution pattern of the Chinese population and proposes a spatial distribution structure of population using GIS (Geographic Information System) analysis. The main findings are as follows: (1) In 2015, the distribution of population density in China presents a pattern of high in the southeast and low in the northwest based on the county-level administrative regions. The population main lives in the southeast of China based on the “Hu Huanyong Line”. (2) There is a great difference of the spatial correlation between land area, population and GDP (Gross Domestic Product) in China. The economic concentration in China is higher than the population concentration. In the areas where population and GDP are aggregated, per capita GDP is higher. (3) Based on the areas with highly aggregated population and GDP, the spatial distribution structure of population of “1 + 4 + 11” for China’s urbanization is put forward, namely, one national-level aggregated area of population and GDP, 4 regional-level aggregated areas of population and GDP, and 11 local regionally aggregated areas of population and GDP. This spatial structure represents an attempt to explore the direction of China’s urbanization, and it can be used to optimize the spatial development pattern and provide scientific guidance for the future urbanization plan.
Minmin Li; Biao He; Renzhong Guo; You Li; Yu Chen; Yong Fan. Study on Population Distribution Pattern at the County Level of China. Sustainability 2018, 10, 3598 .
AMA StyleMinmin Li, Biao He, Renzhong Guo, You Li, Yu Chen, Yong Fan. Study on Population Distribution Pattern at the County Level of China. Sustainability. 2018; 10 (10):3598.
Chicago/Turabian StyleMinmin Li; Biao He; Renzhong Guo; You Li; Yu Chen; Yong Fan. 2018. "Study on Population Distribution Pattern at the County Level of China." Sustainability 10, no. 10: 3598.
Traditionally, visual-based RGB-D SLAM systems only use correspondences with valid depth values for camera tracking, thus ignoring the regions without 3D information. Due to the strict limitation on measurement distance and view angle, such systems adopt only short-range constraints which may introduce larger drift errors during long-distance unidirectional tracking. In this paper, we propose a novel geometric integration method that makes use of both 2D and 3D correspondences for RGB-D tracking. Our method handles the problem by exploring visual features both when depth information is available and when it is unknown. The system comprises two parts: coarse pose tracking with 3D correspondences, and geometric integration with hybrid correspondences. First, the coarse pose tracking generates the initial camera pose using 3D correspondences with frame-by-frame registration. The initial camera poses are then used as inputs for the geometric integration model, along with 3D correspondences, 2D-3D correspondences and 2D correspondences identified from frame pairs. The initial 3D location of the correspondence is determined in two ways, from depth image and by using the initial poses to triangulate. The model improves the camera poses and decreases drift error during long-distance RGB-D tracking iteratively. Experiments were conducted using data sequences collected by commercial Structure Sensors. The results verify that the geometric integration of hybrid correspondences effectively decreases the drift error and improves mapping accuracy. Furthermore, the model enables a comparative and synergistic use of datasets, including both 2D and 3D features.
Shengjun Tang; Wu Chen; Weixi Wang; XiaoMing Li; Walid Darwish; Wenbin Li; Zhengdong Huang; Han Hu; Renzhong Guo. Geometric Integration of Hybrid Correspondences for RGB-D Unidirectional Tracking. Sensors 2018, 18, 1385 .
AMA StyleShengjun Tang, Wu Chen, Weixi Wang, XiaoMing Li, Walid Darwish, Wenbin Li, Zhengdong Huang, Han Hu, Renzhong Guo. Geometric Integration of Hybrid Correspondences for RGB-D Unidirectional Tracking. Sensors. 2018; 18 (5):1385.
Chicago/Turabian StyleShengjun Tang; Wu Chen; Weixi Wang; XiaoMing Li; Walid Darwish; Wenbin Li; Zhengdong Huang; Han Hu; Renzhong Guo. 2018. "Geometric Integration of Hybrid Correspondences for RGB-D Unidirectional Tracking." Sensors 18, no. 5: 1385.
In contrast with photorealistic visualizations, urban landscape applications, and building information system (BIM), 3D volumetric presentations highlight specific calculations and applications of 3D building elements for 3D city planning and 3D cadastres. Knowing the precise volumetric quantities and the 3D boundary locations of 3D building spaces is a vital index which must remain constant during data processing because the values are related to space occupation, tenure, taxes, and valuation. To meet these requirements, this paper presents a five-step algorithm for performing a 3D building space shift. This algorithm is used to convert multiple building elements into a single 3D volumetric building object while maintaining the precise volume of the 3D space and without changing the 3D locations or displacing the building boundaries. As examples, this study used input data and building elements based on City Geography Markup Language (CityGML) LoD3 models. This paper presents a method for 3D urban space and 3D property management with the goal of constructing a 3D volumetric object for an integral building using CityGML objects, by fusing the geometries of various building elements. The resulting objects possess true 3D geometry that can be represented by solid geometry and saved to a CityGML file for effective use in 3D urban planning and 3D cadastres.
Shen Ying; Renzhong Guo; Jie Yang; Biao He; Zhigang Zhao; Fengzan Jin. 3D Space Shift from CityGML LoD3-Based Multiple Building Elements to a 3D Volumetric Object. ISPRS International Journal of Geo-Information 2017, 6, 17 .
AMA StyleShen Ying, Renzhong Guo, Jie Yang, Biao He, Zhigang Zhao, Fengzan Jin. 3D Space Shift from CityGML LoD3-Based Multiple Building Elements to a 3D Volumetric Object. ISPRS International Journal of Geo-Information. 2017; 6 (1):17.
Chicago/Turabian StyleShen Ying; Renzhong Guo; Jie Yang; Biao He; Zhigang Zhao; Fengzan Jin. 2017. "3D Space Shift from CityGML LoD3-Based Multiple Building Elements to a 3D Volumetric Object." ISPRS International Journal of Geo-Information 6, no. 1: 17.