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  • 2018 Volume 20 Issue 6
    Published: 20 June 2018
      

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  • HU Di,LV Guonian,JIANG Nan,CAO Weican,LIU Longyu,LI Yang
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    In recent years, more and more historians and historical geographers have begun to focus on applying GIS technology, and conducted extensive explorations in the research and construction of historical GIS databases and information systems. However, most of these researches are technology-dominated applications. The organization of historical information and historical geographic information mostly focuses on specific topics or applications, lacking data model for the historical GIS basic software. From the dual perspectives of geography and history, this paper is based on the four elements of history: time, place, person, and event (from beginning to the end), integrating geography to emphasize the idea of the "man-earth relationship" and abstracting historical information into historical figures, events, features and scenes, as well as the relationships and experiences/processes. This paper proposed and designed a general historical GIS data model, discussed the composition, attribute, storage scheme of space-temporal objects, the relationship between spatial-temporal objects in the data model. In the application system, the validity of the model was verified by taking the storage and visualization of typical historical figures, events, features and scenes as examples.

  • LU Xiaomin,YAN Haowen,WANG Zhonghui
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    In geographic space, many objects appear in forms of groups, such as settlements, islands, roads, rivers and so on. The direction relation between object groups usually need to be identified in addition to single object's direction relation. For example, when exploring a site for a petrochemical enterprise, the direction relation between it and nearby settlements, rivers, railways need to be identified in order to reduce pollution and improve profits. But most of the existing models for spatial direction relation description aim at single spatial objects. The researches on models for object groups are rare and primitive. Therefore a qualitative description and a quantitative computation models for spatial direction relation description between object groups are proposed. The methods for qualitative description modeling are as follows. First, the minimum boundary rectangle for subject object group is constructed and its direction relation matrix is built, which consists of 9 directional regions. Secondly, the boundary polygon of source object group is computed by methods of constraint Delaunay triangulation and "stripping" with dynamic threshold. Finally, the boundary polygon is set in the direction relation matrix, the intersections of boundary polygon and 9 directional regions are computed, and the qualitative description is represented as the direction relation matrix. The main steps of quantitative computation modeling are as follows. First, the minimum boundary rectangle of subject object group is constructed. Secondly, theory of mathematical morphologic transformation is introduced to "expend" the minimum boundary rectangle of subject object group. The "expanding" starts from due north and finally end up in due north too, which translates the source object group in a series of angles with an angle increment of 5o. The intersection of the "expanded" subject object group and the source object group is computed. Finally, the spectrum density is computed and the average value as well as variance of the corresponding spectrum density are calculated. The distribution figures of spectral vector are drawn to represent the direction relation between object groups visually and vividly. Experiments were conducted respectively to illustrate the soundness and universality of the models. The experiments shows that the qualitative description model has taken the influence of spatial form on spatial direction relation into account and an accurate qualitative judgment between object groups can be made. The quantitative computation model realizes the quantitative computation of spatial direction relation which can visually represent the spatial direction relation between object groups by means of geo-information spectrum. The description and computation of spatial direction relation between object groups can be finely resolved by these two models.

  • WU Enchao,ZHANG Hengcai,WU Sheng
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    The rapid generation and updating of indoor and outdoor integrated navigation network are of great significance for pedestrian-oriented cross-scene navigation. The current researches mainly focus on the establishment of the navigation network in a single scene, and few researches on the automatic generation of the navigation network across the indoor and outdoor scenes. In this paper, a method for automatic generation of indoor and outdoor integrated navigation network is proposed based on Dual Graph and Medial Axis Transform algorithm, then a case study was carried out based on the data of a building's CAD plan and it's surrounding road network. The results show that this method can automatically build the navigation network according to the geometry, topology and semantic information of the original data and support the shortest path query of indoor and outdoor cross-scene. Compared with traditional sub-scene, the overall efficiency of the proposed routing algorithm has been improved by 10.18%; the integrated navigation network can combine the indoor navigation network with the outdoor navigation network reasonably through the semantic information. Compared with the navigation network under single scene, this method could solve the problem of finding optimal path across scenes, and provide a new idea for the research of first-best path planning.

  • WANG Gang,REN Na,ZHU Changqing,JING Min
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    The importance of data security cannot be ignored in 3D model data of oblique photography, which is an important kind of geographic data. Digital watermarking technique can provide powerful protection for oblique photography 3D models. In the past, among studies of 3D model watermarking algorithms, oblique photography 3D models were mentioned rarely and those algorithms cannot meet the demand for the data security of oblique photography 3D models. If a watermarking algorithm is designed in combination with the characteristics of oblique photography 3D model data, obviously, it will be applicable for corresponding 3D models. In this paper, a blind watermarking algorithm is designed based on the characteristic and vertical stability of oblique photography 3D model data. Before embedding watermark in data, some preprocessing steps must be completed. The 3D points will be extracted from oblique photography 3D model data, and sorted by z-coordinate from smallest to largest. Then, using height difference between neighboring points as the watermark information carrier, watermark information is embedded by modifying the parity of the height difference. In order to build a correspondence between embedding location and watermark information, the horizontal distance of neighboring points is used to complete mapping. In the process of watermark testing, points extracting and sorting should be finished firstly as in the process of embedding. Then information can be extracted by distinguishing the parity of the height difference. In this process, mapping is also used. In order to analyze the robustness of this algorithm quantitatively, some experiments were completed. The results show that the algorithm is robust against some usual attacks such as data cutting, translation and rotation.

  • YANG Jie,ZHU Yunqiang,SONG Jia,LU Feng,SUN Kai,LI Weirong
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    With the deep and interdisciplinary development of research on modern geoscience, geo-spatial models are becoming more and more complicated. Consequently, input data required for geo-spatial models are also growing up increasingly. In order to prepare these data quickly and efficiently, a feasible approach is to automatically match shared data from internet for the input requirements of geo-spatial model(MD4GSM). Under this background, in order to automatically convert or transform those incomplete matching data during the process of MD4GSM, this paper conduct the study on the precise description method for the matching result of shared data and geo-spatial model. Firstly, it analyzes the automatic data matching process. On this basis, this paper proposes a precise description structure and its formalization method to represent the matching result. The matching result includes three essential characteristics of data content, spatial information, temporal information, as well as morphological characteristics, such as data type, format, and structure, etc. In addition, each characteristic item is described clearly and precisely by similarity, matching relation and matching extent based on XML (eXtensible Markup Language) to reveal whether the shared data and model’s input data are consistent, where the difference is and how large the difference is. If the similarity of a characteristic is 1 or that of an essential characteristic is 0, it means the characteristic completely or not meets the requirement of geo-spatial model. In this condition, there is no need to precisely describe the matching result further; otherwise the matching result of the characteristic should be described formally and precisely according to the above method. The experiment of soil potential productivity calculation in Hunan province in 2010 shows that the method can be a foundation for automatic combining data processing services and dealing with data in the next, and finally recommending data that fully meet the needs of geo-spatial model.

  • SUN Jingwei,SUN Guangzhong,ZHAN Shiyan,MAO Rui,ZHOU Yinghua
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    Path routing problem is a fundamental problem in many applications on road networks. The A* algorithm is an efficient method to find the point-to-point path. Road networks with Cartesian coordinates can provide Euclidean distance as a heuristic function to guide the search direction of A*, then A* can simply and intuitively outperforms the classic Dijkstra's algorithm. However, Euclidean distance is a fairly relaxed lower bound of the real distance. It limits the potential of pruning more search space of A* on road networks. Higher performance is needed to fit the real-time requirement in the application on large-scale networks. Parallel computing is an effective approach to accelerate many algorithms. However, there are strong data dependencies between iterations of A*, and each iteration has little potential parallelism because of the low-dimensional property of road network. Thus, it is difficult to efficiently exploit the availability of multiple cores with the standard A* algorithm. In this paper, we propose Segmented A* (SA*) algorithm, which is more adaptable to modern multi-core CPU platform than A*. It selects some waypoints that split the required shortest path into several segments, then it searches on each segment separately and concatenates these segments as an approximate result. SA* performs better than A* on account of two factors. One is that sequential SA* can prune more search space than A*. The other is that the searches of SA* on segments can be parallelized, so SA* can make better use of multi-core CPU. The selection of waypoints has a key impact on both calculation performance and the accuracy of path. To exploit the benefit from segmented search and meanwhile reduce the performance overhead from this selection, we consider using some low-cost heuristic strategies to select the waypoints before handling each path routing sub-problem. At first, we rapidly calculate a rough path as a guidance, then select the nodes in this rough path that uniformly split the path to several segments. We can easily guarantee that each segment has the same number of nodes. This split has more possibility to lead to a balanced search space in parallel calculating each segment. In our experiments, using 16 cores, SA* can be 30 times faster than A* on a large-scale real-world road network with a loss of path accuracy less than 10%.

  • LIN Nan,YIN Ling,ZHAO Zhiyuan
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    With the development and popularization of mobile phones, mobile phone location data have become an important source of data for analyzing individual mobility characteristics. With these location data, many studies can be performed at a fine spatiotemporal scale in fields such as population management, urban planning, transportation analysis and health intervention. Detection of individual stay areas is an important and basic step in many studies based on mobile phone location data. However, the sparse spatial and temporal resolution of raw mobile phone location data and data noise caused by location oscillation and location drift introduce great challenges in effectively detecting individual stay areas from raw mobile phone location data. Considering the spatiotemporal continuity of individual behavior, this study proposes an incremental clustering algorithm based on a moving window to improve the accuracy of detecting individual stay areas from mobile phone location data. Specifically, the proposed algorithm first sorts the raw records in chronological order. Then, the algorithm consecutively examines the adjacent records with a given distance threshold. Records that satisfy the rule will be added to the current cluster. For each unqualified record, the algorithm extracts a series of records within a moving window and calculates the spatial distance of these records as a criterion for clustering. The time interval between the unqualified record and the selected records should be less than a given time threshold, which is also the width of the moving window in this proposed algorithm. In this step, the algorithm treats some unqualified records as location drift records or location oscillation records based on the detection rules and aggregates them into the current cluster, and unqualified records that do not fit the detection rules are excluded from the current cluster and the algorithm creates a new cluster for the unqualified records. Finally, the algorithm calculates the location and temporal information of each valid cluster as the parameters of the corresponding stay area and constructs a stay area sequence for each mobile user. We compared the results of the proposed algorithm with those obtained using the ST-DBSCAN and SMoT algorithms. The experiment applied the three algorithms to a mobile phone location dataset in Shenzhen that is a type of Call Detail Records, and the results show that the proposed algorithm significantly improves the accuracy by up to 35% for detecting individual stay areas from sparse mobile phone location data compared to the other two algorithms. Due to privacy issues associated with the government or telecom operators, the temporal resolution of large-scale mobile phone location data used in recent research is usually sparse, and thus the proposed algorithm can be used to improve the effectiveness of detecting individual stay areas and to provide reliable results for many studies based on mobile phone location data.

  • ZHANG Qian,YAN Haowen,ZHANG Liming,HE Yi
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    The accidents of maritime trade and marine safety have been increasing in recent years. Due to the sudden danger and other reasons, the maritime rescue is getting more and more attention. To do a good job in maritime emergency rescue, we should not only strengthen maritime emergency search and rescue capability in all countries, but also need to send rescue forces appropriately. In other words, how to arrange rescue forces to reach the scene of distress and carry out effective rescue is an important subject worth studying in the case of maritime emergency. This study attempts to apply the Voronoi diagram of GIS to the maritime emergency rescue. Based on the analysis of the deficiency in the application of common Voronoi diagram to sea rescue, we put forward the "Maritime Rescue Voronoi Diagram" (MRVD), to improve the maritime rescue operation. The MRVD effectively expanded the application of the Voronoi diagram. In addition, the evaluation of the index weights of maritime search and rescue needs to consider many factors, so it is difficult to assess. The aim of this study was to evaluate the weight of the index of multiple maritime search and rescue by combined use of the fuzzy hierarchy analysis and gravity model. Compared with the single evaluation method used in previous studies, the multi-method research can greatly reduce the interference of subjective factors and improve the accuracy of evaluation results. Finally, for the specific rescue cases, a marine emergency rescue model MRSV based on Voronoi diagram is proposed. It can be seen from the results of each case that the model can take into consideration the special geographical environment of the sea, with high efficiency of rescue and reasonable scheduling results. Compared with the traditional maritime rescue cases, the scope of rescue services allocated by this project is more scientific and more dynamic. According to different shipwrecks, MRSV model draws different rescue service scope, dispatches different rescue forces, and effectively completes the low cost rescue mission.

  • GAO Huiran,QIN Chengzhi,ZHU Liangjun,ZHU A-Xing,LIU Junzhi,WU Hui
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    Scenario analysis based on watershed process model is a widely used method for evaluating watershed management practices (BMP) and controlling non-point source pollution. The commonly used spatial configuration units in current scenario analysis include fields, farms, hydrologic response units, and sub-basins. The weak spatial relationships between these spatial units and the topographic positions along hillslope make the use of these spatial units difficult to effectively represent the effect of different BMP on hillslope processes, and thus affect the efficiency and reasonability of optimized scenarios. In this paper, slope positions are used as the spatial configuration units of BMP under the framework of spatially distributed watershed process model and intelligent optimization method for BMP scenarios. Thus, the knowledge of the spatial relationships between BMP and slope positions can be explicitly considered during optimization. A spatially distributed watershed process model (i.e., SEIMS) and an intelligent optimization algorithm (i.e., the genetic algorithm NSGA-II) were combined in this framework in this paper. A small watershed of red soil dominant region in the east of Hetian county, Changting city, Fujian province, was selected as the case study area. The BMP knowledge base including the relationship between five BMP used in this area and slope positions was built for the study area. The experimental results showed that slope position units can well support the description and application of the knowledge on the spatial configuration of different BMP, compared with the BMP configuration units of fields with upslope-downslope relationship. The proposed method can use BMP spatial configuration knowledge to provide optimal BMP scenarios reasonably and effectively, compared with the random optimization method, a typical BMP scenario optimization method of using NSGA-II optimization algorithm with operations of population initialization, crossover, and mutation randomly.

  • YANG Xiping,FANG Zhixiang,YIN Ling
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    The relationship between human mobility and urban spatial structure has been a long research topic in human geography, which is helpful for understanding the impacts of human mobility and assessing the rationality of urban spatial structure, thus, important and meaningful for urban planning, traffic management, location selection and emergency management. Traditional studies take advantage of travel survey dataset to investigate the relationship between human travel behavior and urban built environment, which makes it difficult to study human convergence and divergence due to the limitation of small sample size. Recently, with the development of Information Communication Technology (ICT), it is possible to collect massive and long-term human spatio-temporal tracing dataset (such as mobile phone data, social media check-in data, floating cars data and so on), which brings a new perspective of studying urban human mobility, spatial structure and their relationship. Based on the previous study, this study focus on the stability of human convergence and divergence, takes traffic analysis zones as spatial analysis unit, aims to explore the correlation between urban spatial structure and the stability of human convergence and divergence. The indicators representing urban structure are constructed from the aspects of socio-economic, land use patterns and urban road network characteristics, respectively. The multiple linear programming is employed to examine the influence of these indicators on the stability of human convergence and divergence. We found that the bigger the population size and density of a place, the less stable the human convergence and divergence. The degree of the mixture of the land use is positively associated with the stability. As for the centrality of road network, the local centrality has significant influence on the stability of human mobility and the impact is different with the increasing of search distance. These knowledges can deepen our understanding of relationship between human mobility and urban spatial structure, which can be utilized by urban operators to guide urban planning, traffic management and make some emergency measures.

  • WU Zaidong,LIN Guangfa,ZHANG Mingfeng,LUO Zunhua,ZHOU Wenjuan
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    Sudden river pollution accidents can occur suddenly and have the uncertainty of development. It is necessary to distribute sufficient emergency resources to the emergency disposal space within limited time. This study constructed a multi resource and multi objective emergency resource scheduling model. Based on the planning objective of shortest emergency disposal time, this model assumed the constraint condition that the total construction time of emergency resource transportation and emergency project must be less than the time that pollutants diffused and arrived the position of emergency disposal, and the multi emergency resource warehouse integrated scheduling resources must meet the processing needs. Assuming that the time of emergency resource's outgoing, loading and unloading is certain, according to the dynamic process of pollutants spreading along the river, the optimal route of dynamic emergency resource distribution was optimized by using Dijkstra algorithm. Then, the time for the amount of resources required from each warehouse to reach the emergency disposal space was calculated. Finally, a strategic solution was exported and the risk of the decision-making was evaluated according to the ratio between the time that emergency resource arrived in disposal position and the time which the pollutants spread to the point. By setting the burst of six valency chromium pollutants as one case study, the experimental results show that the model can verify whether each emergency disposal space position can be treated as the emergency disposal point; the most reasonable emergency resource scheduling scheme at the emergency disposal space position can be obtained; and the emergency vehicle dynamic optimal route can be determined. Besides, the results evaluated the assessment of decision-making risk of emergency resource scheduling for each emergency disposal space position, improved the emergency management decision-making efficiency and reduced the decision-making risk. In addition, the model also had certain applicability in other similar fields, such as disaster relief in cases of dam-break and so on.

  • LIANG Chunyang,LIN Guangfa,ZHANG Mingfeng,WANG Weiyang,ZHANG Wenfu,LIN Jinhuang,DENG Chao
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    When a disaster occurs, a large number of images and texts with geographic information quickly flood the social network, which provides a new data source for timely awareness of disaster situations. However, due to the regional variation in the number of social media users and characteristics of information diffusion in cyberspace, new problems have risen in the mode analysis of spatial point processes represented by the check-in data. Examples are the correlation between check-in point density and disaster location density, spatial relation between check-in points or spatial heterogeneity of point pattern and associated influences. In this study, we took Typhoon No.14 in 2016 as an example and collected Sina Weibo data between September 14 and September 17, 2016 using keywords “Typhoon” and “Meranti”. We classified the Weibo texts using Latent Dirichlet Allocation (LDA) and Support Vector Machine (SVM) algorithms and constructed a disaster database containing relevant check-in information. In addition, considering the spatial heterogeneity of Weibo users, we proposed a weighted model based on user activity at the check-in points. Using the global autocorrelation statistics Moran′s I as an indicator, we compared the check-in data before and after adding weights and discovered obvious spatial autocorrelation of the check-in data in real geographical locations. We tested our model on Weibo data with keyword “rain” and “power failure”. The results show that a series of maps generated by our model is able to reflect the typhoon disaster spatio-temporal process trends.

  • ZHAO Xinyi,PU Yingxia
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    Interregional migration is a significant component of regional population growth as well as a major driving force in urbanization process. The evolution of migration flows is not only related to the characteristics of origin and destination regions, but also the past and surrounding migration flows. Most empirical migration studies based on traditional gravity models have failed to capture space-time spillover effects during the migration process due to ignoring time or spatial dependence among migration flows. By introducing several space-time interaction effects, this paper constructed the space-time gravity model of interprovincial migration flows in China over the period of 1985-2015 and estimated the model using Bayesian Markov Chain Monte Carlo (MCMC) method. The space-time spillover effects evaluation framework further explained the space and time dynamics in the evolution of interprovincial migration associated with changes in regional GDP per capita and population size. The preliminary results are as follow: firstly, the estimates of time, spatial and space-time diffusion dependence are all significant, which can provide powerful means for exploring complex and systematic behaviors among regional migration flows. Secondly, regional population size dominates the Chinese interprovincial migration process more than twice the influence of regional GDP per capita. Thirdly, the spillover effects of regional socio-economic factors play a quite significant role during regional migration process, which are greater than the corresponding origin and destination effects in the short term. More importantly, the decaying spillover effects through the whole space-time network will help the migration system stay at an equilibrium state over the long term. All in all, the coupled space-time gravity model contributes to capture the space-time spillover effects and driving forces during the regional migration process, which provides a scientific basis for predicting future migration trends and promoting balanced regional population development.

  • LI Zhi,LI Weihong
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    Spatiotemporal co-occurrence patterns represent subsets of different object-types whose instances are frequently located together in both space and time. Using movement data to mine and analyze spatiotemporal co-occurrence patterns among diverse criminal suspects not only can help us better understand those unusual moving behaviors and relationships of them, but also provide decision-making supports for police departments in key suspects monitoring or arresting. Therefore, such pattern is one of the most important and useful way for the geography of crime researchers and police officers to extract and comprehend the implicit knowledge in large police databases which hold a large amount of crime data with spatiotemporal information. Additionally, to some extent, mining spatiotemporal co-occurrence patterns can also assist the police departments to save the limited police resources and improve their efficiency of handling criminal cases. However, current methods for mining spatiotemporal co-occurrence patterns can hardly be applied to the geography of crime studies directly because the way of determining spatial and temporal prevalence thresholds is presently difficult and lack of objectivity. Thus, in this paper, a novel candidate spatiotemporal co-occurrence pattern mining model was first built based on the spatiotemporal status co-occurrence pattern and the minimum spatiotemporal participation rate. Then, a framework for mining spatiotemporal co-occurrence patterns among criminal suspects under the point distribution was given through combining our proposed model and generalized ESD test. Finally, based on the proposed framework, a real case study in a province of China was conducted with an amount of real trajectory data of two criminal type (fraud and theft). The result shows that our proposed method is feasible in mining and analyzing the spatiotemporal co-occurrence patterns among criminal suspects. Specifically, 219 candidate spatiotemporal co-occurrence patterns were discovered under the condition that spatial neighbor distance equals to 688 meters and temporal neighbor distance equals to 504 seconds, and 6 of them were identified as the spatiotemporal co-occurrence patterns under the condition that significance level equals to 0.05. Importantly, the spatiotemporal distributions of those detected spatiotemporal co-occurrence patterns are not only approximately consistent with the common sense that criminal activities are more common in non-agricultural production areas, but also conform to the basic viewpoints of routine activity theory. This research expands the application of spatiotemporal co-occurrence pattern mining method to the geography of crime studies, and the study result can play an important role for police departments in key suspects monitoring and police resources allocation and deployment.

  • ZENG Xuan,CUI Haishan,LIU Yihua
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    The catering industry has been considered as one of the most important indicators concerning economic development of a city. Using appropriate methods to study catering industry has been playing an important part in research fields such as city planning, business location and economic development. Many restaurants in a city can be abstracted as point objects in the study of geography. It is one of the most commonly used methods to study the spatial layout of facility events by using spatial point patterns. The traditional point pattern analysis methods are basically based on the Euclidean distance and assume that the plane space is a homogeneous and isotropic space. However, many geo-objects are usually distributed on the road network or along the road network, such as restaurants, banks, supermarkets and road traffic accidents. If the traditional method of plane space point analysis is applied to the trend events occurring along the road network, wrong aggregation mode may occur. By using the network spatial point pattern analysis method, the shortest path distance instead of the Euclidean distance can be used to study the distribution characteristics of the event points, and more accurate spatial analysis results can be obtained. Take Haizhu District of Guangzhou city as an example, on the basis of restaurants POI (point of interest) data, Kernel density estimation is adopted to analyze spatial distribution characteristics of restaurants. The network kernel density method is used to investigate the distribution characteristics of the hot roads, and double variable K function method is applied to analyze the relations between distribution of restaurants and bus stations and residential areas. The spatial pattern of Haizhu District restaurants shows much more dense in the West and comparatively sparser in the East. The restaurant hot spots are mainly concentrated along the streets of Jiangnan West and Jiangnan Zhong, and the density of the restaurants decreases with the increase of the distance from the hot spots. The degree of aggregation of restaurants, bus stations and residential areas is also investigated under the road network structure. The results show that restaurants have strong aggregation relations with bus stations, which indicates that the restaurant tends to close to the traffic stations, but have no significant aggregation relationship with the residential areas. As far as the spatial point objects along streets are concerned, better results can be obtained by using network analysis of spatial point pattern.

  • ZHU Jingwei,FANG Zhixiang,YANG Xiping,YIN Ling
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    Distribution and movement of people in urban areas are important information for studying urban dynamics and crowd displacement rhythm. The temporal variation of people flow between different spatial regions shows how people interact with physical locations and is highly related to its function and structure in the city. Previous researches usually use density-based approaches to investigate the temporal variation of people flows in different spatial regions. This kind of approach can present time slice-based hot-spot maps but cannot reflect the consistency of changing processes. Therefore, this paper proposes an approach of synchronization measurement to fill in this gap. Our method is designed to measure the similarity of temporal people flow processes between stations in the 3D feature space and quantify property of synchronization of communication network areas based on the average similarity. An experiment of measuring synchronization was conducted using a dataset of mobile phone data in Shenzhen. The people flow processes within this city was derived from the mobile phone dataset. The results show: firstly, the neighboring-area radius and feature space threshold depend on the distribution of mobile station and flow process in corresponding serving areas. In most cases, the neighboring-area radius can be set as the average distance between mobile stations. The feature space threshold depends on the neighboring area radius, and the smaller the radius, the smaller the threshold should be. Secondly, different from administrative areas, the synchronized areas show the characteristics of human dynamics in the city with a smaller spatial unit. We found that the centers with higher level of planning have more synchronized regions with relatively small area in them. Finally, compared with the density map result, our approach indicates that the synchronized regions not only exist in the city centers with high flow changes but also in rural areas with relatively small flow changes. Combined with additional information such as land use attributes, the synchronized areas clarify the spatial structure of the population and its aggregated boundary effect in the city. This approach can be used to assess the output of urban planning and optimize the distribution of service facilities such as emergency management and transportation network design.

  • YU Bingchen,LIU Yuxuan,CHEN Gang
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    Port city in South China Sea, the important transportation hub in South China Sea and the 21st Century Maritime Silk Road, is significant for research on resource and environment monitoring of South China Sea. However, there is a lack of research about urban spatial structure of port city in South China Sea, especially the role of the port in urban spatial structure. Both of nighttime light data and POI (Point of Interest) data are widely used in research on urban spatial structure as data source, but few research focus on the spatial coupling between nighttime light data and POI data, and the integrated application of two data sources. As an example on the spatial coupling between nighttime light data and POI data, we take Sanya City, a typical representative port city in South China Sea, as study area, and use NPP-VIIRS nighttime light data and POI data of study area in 2016 as data source. In addition, we use overlay analysis to transform both data, the nighttime light data and the processed POI data by kernel density method, into regular grids. Then we use the method for mapping double factors to discuss the spatial coupling relationship between both data, and analyze the relationship between areas with different spatial couplings and urban spatial structures, especially the ports. The results show that: (1) The nighttime light data and POI data have strong spatial coupling relationship, which indicates a significant consistency. The global trend of spatial distribution between both data in Sanya City is pretty similar, and 85.6% of total area have same spatial coupling. (2) The regions where spatial coupling between nighttime light data and POI data differs have some significant spatial characteristics of urban structures, such as the large-scale homogeneous regions, rural-urban fringe, suburbs, and township. POI data has few distributions in economic development zone, new urban districts and so on, but much distribution in suburbs, townships and so on. By contrast, nighttime light data can characterize urban construction significantly, but can't characterize the township. (3) Sanya City, as an important port city in South China Sea, shows a strong relationship between its urban centers and ports. All of three urban centers revolve around three main ports and spread from it in a ring or line form. This study provides a new perspective of the research ont urban spatial structure of port cities in South China Sea.

  • PEI Fengsong,WANG Kun,LIU Xiaoping,WU Changjiang,ZHOU Yi,LIU Li'an
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    The process of urbanization, especially the urban land expansion, frequently shows an important influence on vegetation primary productivity. Past studies mainly focused on the direct impacts of urban land sprawl on the vegetation primary productivity, such as transformation of natural land use into urban impervious surface. However, little effort was exerted to understand the indirect impacts of urban land use (i.e., changes of urban greenery coverage). Taking the Yangtze River Delta, China as a case study, this paper analyzed the temporal and spatial changes of vegetation primary productivity in the study area during 2000-2013. The analysis was conducted by cities and over the whole region, respectively. The relationships between vegetation primary productivity in the urban built-up area and the corresponding size of the built-up area were further analyzed for cities by using statistical analysis. Mechanisms of the changes in vegetation primary productivity were explored from both the large and local scales. That is, correlations were examined between vegetation primary productivity and regional meteorological factors (i.e., the annual mean temperature and total precipitation), as well as greenery coverage rate over the built-up area at different cities. The results show that the vegetation primary productivity in the study area showed an overall increased trend from 2000 to 2013 at a regional scale. In particular, the average vegetation primary productivity revealed a significant increasing trend during 2000-2013 in the urban built-up areas in the Yangtze River Delta (P < 0.05). At city scale, the vegetation primary productivity mainly revealed increased trends over the period 2000-2013 in the built-up area in most of the cities. However, the trends were reversed in the 0~10 km buffer zone of the built-up areas. Under the condition of climate change, this increase of vegetation primary productivity might be associated with the increase of urban greenery coverage in the urban built-up areas, as well as the fast urban expansion in the Yangtze River Delta.