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  • FANG Zhixiang,YU Hongchu,HUANG Shouqian
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    With the rapid development of economic globalization, the scale of international trade has continued to be expanded. Global maritime network are attracting much attention from researchers in multidisciplinary areas, such as ocean transportation, geographical information science, mathematical physics, statistics science, complex network science, big data science, computer science and so on. The maritime network studies become hot research topics among them, which plays an important role in designing affective and sustainable macro strategies and policies for countries. This paper summarizes the data sources, theoretical models and research methods in maritime network studies, for example, the used data includes the statistics data and Automatic Identification System (AIS) traced vessel trajectory data, the used methods are from mathematics, physics and statistical theory methods, complex network science, data mining theory, etc. Then, this paper reviewed the research works of maritime network from the perspectives of maritime network transportation mode, network structure characteristics, and evolution mechanism of maritime network, and concluded the existing problems in these perspectives. Previous studies on maritime transportation mode design and optimization are useful to improve shipping service quality, assess the feasibility of new routes and improve the efficiency and capacity of the transportation system. The researches for maritime network structure reveal the static (i.e. network connectivity, clustering coefficient, mean shortest path lengths, closeness centrality, betweeness centrality, and straightness centrality) and dynamic characteristics (i.e. spatial-temporal changes, hierarchical characteristics, dynamic connectivity) through the approaches of modelling, statistical and empirical analyzing. The studies on evolution mechanism for maritime network focus on the structure evolution and traffic flow evolution, which are helpful to identify the influential factors and to predict traffic flow in the maritime network. The future promising research avenues on maritime network include involving experts from multidisciplinary areas, using the research methods from cross-domains, integrating multi-source heterogeneous data, and linking the theoretical analysis with practical application problems.

  • LU Qiang,WU Lin,CHEN Zhao,WANG Qi,XU Yongjun,KAN Rongcai
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    With the globalization of the Belt and Road national strategy, the volume of shipping trade is increasing rapidly. As a result, the problem of the safety of maritime navigation and monitoring has become increasingly prominent. The real-time monitoring of large-scale ships, based on the spatio-temporal data, through target tracking and information fusion is an effective method, but it also faces great challenges. Data association, as the basis and a key step of target tracking and information fusion, has important application value in military and civil fields. This paper summarizes the problems related to data association. Firstly, the data sources for trajectories of the marine targets were introduced and compared, showing its necessity and feasibility. Then two kinds of problems in data association, i.e., measurement-to-track association (MTTA) and track-to-track association (TTTA), were described. Based on the data association methods in MTTA, we abstracted a data association model consisting of state estimation and association judgment, and described the Kalman filter used generally in state estimation. After that, the basic principles and improvements of nearest neighbor (NN), probabilistic data association (PDA), joint probabilistic data association (JPDA) and multiple hypothesis tracking (MHT) were introduced. NN implements the data association using the distance between the measured and predicted values. PDA, considering only a single target, calculates the association probability of each measurement in the circumstance with presence of clutter and target missing, and associates the measurement with the maximum association probability to the target. JPDA as the extension of PDA, suitable for multiple targets, calculates the joint association probability of measurements and targets by joining all targets, and selects the association event corresponding to the maximum joint association probability as the association result. MHT is a multi-scan multi-hypothesis method and has the characteristics of track creation, maintenance, deletion and false alarm. It achieves the optimum in theory by maintaining multiple possible hypotheses generated by each association cycle. The key to the MHT is how to control the scale of the hypotheses by effective pruning in order to improve the efficiency of time and space of the algorithm. With regard to TTTA, two kinds of methods, based on statistics and fuzzy mathematics, were introduced respectively. The statistics methods consist of NN/K-NN/MK-NN, double threshold track correlation, sequential track correlation, etc. The key of fuzzy methods is the construction of fuzzy factor set and membership function. We also introduced the evaluation methods for data association. Finally, the problems in the existing methods, e.g., the application scenarios, and further researches were explained.

  • YU Hongchu,FANG Zhixiang,LU Feng,PENG Peng,ZHAO Zhiyuan,FENG Mingxiang
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    MSR (countries along the Maritime Silk Road), BRICS (Brazil, Russia, India, China, and South Africa) and AJK (the United States, Japan and South Korea) are important economic developing zones to promote international trade. Study on the spatio-temporal evolution pattern of maritime network is helpful to analyze the competition and balance of international trade between different countries, and to make scientific strategic deployment and intelligent decision in global maritime trade. Automatic Identification System (AIS) data makes the real-time analysis of maritime network possible for its advantages of real-time and the near-complete coverage for the offshore area of the ports. Based on the AIS data of three main types of business ships in international trade, namely bulk ship, container ship and tanker ship, this paper reveals spatio-temporal evolution patterns of maritime networks between important economic developing zones, using the timeline method to describe the change of the networks in and outside different zones. The result shows that the structural maritime network evolutions of bulk-layer, container-layer, and tanker-layer inside the MSR are much larger than the evolutions inside BRICS and AJK, which indicates that the Belt and Road Initiative has promoted the trade between MSR countries. The dynamics outside three typical important economic developing zones (MSR, BRICS, and AJK) are large from 2013 to 2016, which indicates that the networks between them have changed greatly with the implementation of the Belt and Road Initiative. The structural maritime network dynamics weighted by cargo handling capacity in 2015 and 2016 are smaller than 2013 and 2014, which indicates that under the implementation of the Belt and Road Initiative, the changes of cargo handling capacity in and outside the three economic developing zones have decreased in 2015 and 2016. Obviously, the Belt and Road Initiative has different influences on MSR, BRICS, and AJK. The maritime networks inside and outside MSR are affected by this initiative. The bulk, container, tanker maritime networks inside BRICS have diverse dynamics derived from this initiative, which also affected the maritime networks outside BRICS to some extent. This initiative has no influences on the network inside AJK, but partly affects the network outside AJK. Improving the throughput and position of MSR in the maritime network is still very important to global trade balance.

  • SUN Tao,WU Lin,WANG Fei,WANG Qi,CHEN Zhao,XU Yongjun
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    Among the 65 countries along the Belt and Road, 46 countries have registered ports of entry. At the same time, the trade by maritime shipping account for more than 75% of the total international trade. In order to fully understand the shipping trade in the countries and regions along the Belt and Road and assess the trade relations between countries and regions along the Belt and Road, we selected data which depicts the shipping history movements of the countries along the Belt and Road in the year of 2016 for study in this paper. Firstly, based on the method of rule determination, we excavated the Stop-port events of ships. By use of the ports in the countries of the Belt and Road as the main nodes, and the inter-port cargo transactions events as the edges, we have built the Belt and Road international shipping trade network. Based on this, the following network structure analyses of trade networks were conducted: (1) basic attributes analysis of the Belt and Road trade network, including network connectivity, degree distribution and average shortest path; (2) calculation of network node centrality, mainly using Eigenvector Centrality to evaluate the centrality of nodes in the trade network; (3) Using the concept of community mining in social network mining as the reference, and using the Fast Unfolding algorithm to discover the community of trading network. It can be seen that the trade between the countries and regions along the Belt and Road is intricately interwoven. By analyzing the degree distribution of nodes in the trade network, it can be clearly seen that there are small-world networks within the Belt and Road trade network. Further, Turkey, Russia and China are the three most influential counties in terms of the ports influence. By analyzing the results of the community detection, five major trade communities were identified. The distribution of these communities is basically in line with the geographical distribution. However, there are still some countries that are affected by special trade practices and their communities have broken regional restrictions. By building the trading network under large scale ship data, we evaluated the node's influence and analyzed the structure of the trade network more clearly on the basis of network analysis, and we hope this paper can help to better implement the Belt and Road Initiative strategy.

  • FENG Suyun,ZHANG Kaixuan,LU Linlin
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    With the rapid process of urbanization, it is very important for sustainable urban development that how to evaluate the changes of urban environmental quality in time and accurately, and thus make reasonable urban developmental plans. In this paper, the fine particulate matter (PM2.5) concentration data, land surface temperature (LST) data, normalized difference vegetation index (NDVI) data and supplementary information data of urban land use obtained by satellite remote sensing were obtained and synthetically used to assess the urban environment changes in mega cities along the Maritime Silk Road. The dynamic changes of urban environmental quality of 12 mega cities along the Maritime Silk Road were analyzed based on the comprehensive evaluation index (CEI) from 2000 to 2013. The results showed that, from 2000 to 2013, approximately 75 percent of the mega cities along the Maritime Silk Road showed different degrees of environmental deterioration. The area of environmental deterioration and moderately environmental deterioration accounted for 31.33 percent (4732.39 km2) of the total urban areas in the 12 mega cities. And 29.48 percent (3765.83 km2) of the total expanded urban areas from 2000 to 2013 exhibited environmental degradation or moderately environmental degradation. The rise of average land surface temperature, the sharp decrease of vegetation coverage and the increase of the fine particulate matter concentration all had an impact on the urban environmental quality changes of the mega cities along the Maritime Silk Road. Among them, the significant increase of the fine particulate matter (PM2.5) concentration in the air was one of the main manifestations for the environmental degradation of the expanded urban areas from 2000 to 2013 in mega cities along the Maritime Silk Road. These findings suggested that more attentions should be paid to urban environment issues to ensure sustainable urban development along the Maritime Silk Road.

  • MOU Naixia,LIAO Mengdi,ZHANG Hengcai,PENG Peng,LIU Xiliang
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    The port is the critical node in the Maritime Silk Road. The location advantages evaluation of the port along the Maritime Silk Road is of great significance to the rational planning of the port and its hinterland infrastructure, and also plays an important role in the port investment forecast and the Belt and Road initiative promotion. From the perspective of the sea-land combined transportation, this paper comprehensively considers the influence of the road network density of port hinterland, traffic artery, city, strategic shipping hub port and channel, then builds the evaluation model of port location advantages to analyze the advantages of important ports along the Maritime Silk Road. This study shows that: (1) For the ports along the Maritime Silk Road, their location advantages have a significant discrepancy in different regions, and the distribution pattern presents the characteristics of high-low-high from east to west; (2) While the location advantages of ports are similar within a country, the regional difference is obvious. The ports in Southeast Asia have the highest location advantages, followed by Southern Europe to Western Europe, South Asia, North Africa and West Asia. The ports in East African to South Africa regions have the lowest location advantages; (3) There are significant regional differences in the influence factors of port location, and the port location advantages are more relevant to the influences of the traffic artery and the city. The results can provide scientific support for the investment and construction process of overseas port infrastructure.

  • “海上丝绸之路空间数据分析”专辑
  • “海上丝绸之路空间数据分析”专辑
    YANG Ren,MOU Naixia,PENG Peng,LIU Xiliang,ZHANG Hengcai,LU Feng
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    The 21st-Century Maritime Silk Road is designed to go from China's coast to Europe through the South China Sea and the Indian Ocean in one route, and from China's coast through the South China Sea to the South Pacific in the other. The study on the competitiveness of the important ports in this region can provide beneficial suggestions for further constructions of ports. This paper evaluates the competitiveness of 99 important ports in 51 countries along the Maritime Silk Road via entropic weight-analytic hierarchy process with the help of the influence of natural conditions, hinterland, infrastructure, service, corruption perceptions index and different status in the ports' shipping network. This method can objectively assign weights to make the results more scientific. Final results show that (1) the spatial distribution of port competitiveness shows obvious regional characteristics, and it is significantly correlated to the development level of the country. The competitiveness of ports in the Mediterranean region is generally stronger, followed by ports in Asia, and the ports in Africa are the weakest. (2) The network status of a port has the greatest influence on port's competitiveness, and most of the high competitive ports are in strategic channels. (3) Although there are real competitiveness gaps of the ports invested by China compared with the mature ports along the 21st-Century Maritime Silk Road, a great space exists for further improvement of these ports.

  • MEI Qiang,WU Lin,PENG Peng,ZHOU Peng,CHEN Jinhai
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    With the deepening of China's opening to the outside world and the advancement of the Belt and Road Initiative, South China Sea, as an important gateway to China's opening-up and a vital joint for important sea-routes gathering in the world, is embodying prominently strategic position. How to ensure the safety of routes and regulate the vessels sailing in the open water of the south China Sea, safeguard national rights and enhance regional trade is a difficult problem for governmental administrators. In this paper, we excavated the typical spatial distribution of vessels by calculating and visualizing the traffic density of navigation in the South China Sea to analyze the main routes selected by full use of the satellite AIS data of South China sea in 2015 and vessel information database, so the habitual routes could be detected in this region. On the other hand, the statistics on the number of vessels in South China Sea were computed by the statistic line set to find the peak points of the vessel crossing data on the main routes being selected by the most of vessels. Via the above steps, the typical spatial distribution of vessels was defined clearly. Meanwhile, the main flow of trades in South China Sea was determined based on 4 dominant sorts (Bulk, Container, Oil&Chemical and Ro-Ro) of vessels' main routes selected. Research indicated that: (1) The main routes followed the authoritative sailing book《Admiralty Ocean Passage for the World》, which provides sailors with the routes consisting of the waypoints recommended. As a result, the construction and development have little influence on the navigation in this region. Maritime safety administrator can set traffic separation scheme efficiently based on this research; (2) Long-distance shipping is the major mode of transportation. Pearl River Delta being one of the main ends of trade flow indicates the China's dominant position in the South China Sea Trade. This research also attracts more attention to the Beibu Gulf and Hainan Island’s trade potentiality.

  • ZHENG Hailin,HU Qinyou,YANG Chun,CHEN Jinhai,MEI Qiang
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    Mining of the spatial distribution of berthing ships is of great significance in the maritime supervision, port management and fleet management of a shipping company. However, almost all of the existing studies focused on the spatial clustering of ship berthing points to identify berths and anchorages, and only few articles focused on the analysis of berthing ships' features in ports and the detection of the anomalous berthing ships outside the berths and anchorages. Therefore, it is necessary to use the massive automatic identification system (AIS) data to acquire the ship berthing features, which is also feasible due to general equipment of AIS on ships. By setting the threshold value of berthing speed and Variation of the berthing position according to the sea conditions, the model for determining the berthing ships could be established. Filtering by port area and ship type, we could obtain the container ship berthing records at Waigaoqiao Harbour District from January to November 2016. With the purpose of obtaining density distribution of ship berthing points at Waigaoqiao Harbour District, density-based spatial clustering of applications with noise (DBSCAN) algorithm is adopted. The neighborhood radius (ε) and density (MinPts) could be set according to the cluster center density and quantity of clusters. Density clustering is carried out on all berthing ships, and the clustering result is presented in figure with clusters and noises. Compared with the distribution diagram of berths and anchorages at Waigaoqiao Harbour District, a list of suspicious berthing ships is generated. By analyzing historical trajectories of ships in the list, we could make ships' real berthing records clear, and identify anomalous berthing ships at Waigaoqiao Harbour District. The study has found that the abnormal berthing ships at Waigaoqiao Harbour District were located at the Nangang Channel between Yuanyuansha Anchorage and Wusongkou Anchorage or Nangang Channel near Jiangya Nansha Anchorage. What's more, the changes of ships' position before and after berthing position small, while ships' speed before and after berthing position reduced sharply. Therefore, we could speculate that it was ship emergency failure that leads to ships' anomalous berthing. According to the ship maritime mobile service identity (MMSI), maritime safety administration (MSA) can quickly locate the shipping company related to the ship so as to strengthen the onshore ship safety management. Anomalous ships' berthing time and position help to record the failure duration and location, which can supply the important evidence for fleet management of shipping company.

  • WU Qunyong,SU Keyun,ZOU Zhijie
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    Bus passengers' origin and destinations (OD) can truly reflect travel characteristics and demands of residents, which is an important basic data for bus system evaluation, scheduling and route optimization, with significantly practical value in urban planning. Existing OD estimation methods are mostly applied to a small amount of bus data, which cannot directly and rapidly calculate mass transit passenger OD. In order to solve these problems, a parallel method for calculation of massive transit passengers' origin and destinations based on MapReduce is investigated. Firstly, database migration tool was applied to transfer massive bus data stored in relational database to HBase. Secondly, MapReduce parallel computing framework was introduced to divide the IC card data into multiple Map tasks in the light of region numbers in HBase to calculate origins. The origins are grouped and stored into HDFS by user in the Reduce function. Thirdly, the destinations are estimated by origins in parallel which are divided into multiple Map tasks according to block numbers stored in HDFS. According to the travel record of each passenger, destinations can be accurately calculated by the means of public transit chain method and history similarity. In the end, taking IC card data and GPS bus data in Xiamen from June 13 to 26, 2015 as the example, which has 295 bus lines, 16 879 661 bus records, and 14 410 058 complete OD pairs which accounted for 78.9% of IC card data. Comparing with the traditional method, the computational efficiency has substantially improved. The results illustrate that the parallel method can not only calculate bus passenger OD accurately, but also has higher computational efficiency.

  • ZHAO Zhiyuan,YIN Ling,HU Jinxing,FENG Shengzhong,HUANG Silin
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    The origin-destination (OD) information of motor vehicles serves an important foundation in urban traffic analysis and intelligent transport system management. Currently, most of the location-allocation algorithms of traffic detectors in transportation system focus on detecting traffic conditions (e.g., travel speed) at major junctions of road networks. However these algorithms fail to completely monitor the OD information of motor vehicle travels. This study proposes an algorithm to select the road sections where traffic detectors should be installed for the purpose of monitoring the OD information of motor vehicles traveling between regions of interest (ROIs) (e.g., residential communities and shopping malls). Two methods are adopted in this algorithm to maximize the usability of the detectors. First, since the demand of the detectors relies on the number of the road sections connected to the ROIs and the spatial resolutions of the ROIs affect the volume of connected road sections, the spatial resolutions of the ROIs are adjusted according to the closeness between the ROIs by a hierarchical clustering algorithm. During this process, special ROIs, for which the ODs need to be monitored independently, can be set to avoid being merged with other ROIs. Second, the redundantly monitored road sections are detected based on the conservation law of the traffic flows at a crossroad. This algorithm was examined in the area of Dapeng, Shenzhen. Specifically, we first used a museum and a road entrance to test the effectiveness of the special ROIs setting. Then we compared the outcomes of the hierarchical clustering algorithm using three different distance measurements between clusters, namely single linkage, complete linkage and average linkage. Third, the effectiveness of the redundant monitor road sections was examined at a crossroad. Last, we tested the effectiveness of the proposed algorithm when the supply of cameras were limited to 10 and 20, respectively, based on the simulation result of ODs between different locations. The results suggest that the proposed algorithm can effectively support the policy-making of selecting the target road sections to monitor the OD information of vehicle travels when the supplies of the detectors are limited under different situations.

  • YANG Mingyuan,LIU Haiyan,ZHU Xinming,SU Chenchen
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    Management mode of relational database and file type database is difficult to support the data of Argo floats data. Because Argo buoy floats freely with sea current and data volume is huge in scale as the mobile object. In view of the quasi-real-time, massive nature, spatio-temporal variation and other characteristics of Argo ocean buoy data, as well as multiple query application requirements, the advantages and disadvantages of the current space-time indexing method are analyzed. The deficiencies of current spatio-temporal indexing method include: (1) The Argo buoy data has large volume and are observed over a long time span. When a STR-tree index is established on the trajectory of a buoy, the over-long trajectory tends to lead to a high overlap ratio between the MBB of the STR-tree, which further leads to the reduction of search efficiency. (2) The Argo floats data are sampled at different frequencies and with relatively stable frequency, but the influence of the update frequency on index structure optimization is often ignored. Therefore, a hybrid index structure called MFSTR-tree with multi-frequency STR-tree index and grid index is proposed. First, the dynamic trajectory beam is used as the leaf node to generate the STR-tree structure in the trajectory beam layer, taking advantage of the flexibility and the less data redundancy of the STR-tree index structure. Then, the improvement of query efficiency is realized by use of the multiple frequencies of the track beam at the sampling point layer according to the construction grid index. The corresponding interpolation algorithm and query algorithm are described in this paper. To verify the construction and query efficiency of MFSTR-tree, a comparison experiment was conducted with HR-tree and STR-tree for Argo floats in 2015 from China Argo real-time data center. The experimental results show that under the premise of guaranteeing construction time efficiency and storage efficiency, HR-tree still maintains natural advantages in single-time query and is much more efficient than the other two. After optimization, the MFSTR-tree had efficiency of 40% higher than the general STR-tree. The query efficiency of the HR-tree decreases significantly with the query window size expanded to 4% of the total range. MFSTR-tree is further optimized on the basis of the original STR-tree, which improves the efficiency of the sampling point selection process in the trajectory bundle. Therefore, the advantage is more obvious, and the verification of the algorithm is realized.

  • YANG Genyun,ZHOU Wei,FANG Jiaoyong
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    This paper used an information quantity model and four normalized models to assess earthquake-induced shallow landslide susceptibility in a geographic information system environment. Four normalized models are Min-Max normalization, the zero-mean normalization, the logarithmic logistic normalization and the arc-tangent function normalization. The approach was applied to the Qushan-Leigu area in the Beichuan County, Sichuan Province, where many co-seismic landslides were triggered by the Wenchuan earthquake in May 2008. Seven impact factors, the slope angle, slope aspect, geology, elevation, distance to faults, distance to rivers and distance to roads, were selected as the most important conditioning factors. To assess the shallow landslide susceptibility, a spatial database of conditioning factors and a landslide inventory map were compiled in ArcGIS using data from a topographic map, a geological map and Spot-5 imageries. The information quantity values of the conditioning factors were computed and normalized based on four normalized models. The weighted values of assessment factors were determined using the analytic hierarchy process. Five landslide susceptibility maps were developed. The performance was evaluated using the receiver operating characteristic (ROC) curve. The values of the area under the curve (AUC) for four normalized models and the information quantity model are 0.807, 0.672, 0.592, 0.615 and 0.684, respectively. A comparison of the results of the landslide susceptibility assessment and the landslide inventory indicates that the Min-Max normalization had the highest predictive performance (AUC=0.807). The landslide susceptibility index values were reclassified into five susceptibility classes using the Natural Breaks approach, namely very high, high, medium, low and very low susceptibility. The results show that the very high susceptibility zone obtained using the Min-Max normalization covers about 20% of the study area. Landslides distributed in the very high susceptibility zone are close to faults and rivers. The final landslide susceptibility map has the potential to the regional landslide risk assessment and geohazard mitigation.

  • XIANG Chao,ZHU Xiang,HU Deyong,QIAO Kun,CHEN Shanshan
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    Impervious surface refers to the surface unable to allow water to percolate through, such as pavements that are covered by impenetrable materials and rooftops. Increased impervious surface area is a consequence of urbanization. Impervious surface percent (ISP) is an indicator to quantify the urbanization level. Therefore, accurate mapping and estimation of ISP in Beijing-Tianjin-Tangshan urban agglomeration are significant for multi-city coordinated development and urban layout. Based on classification and regression tree (CART) algorithm, a technical scheme of extracting ISP which is suitable for Beijing-Tianjin-Tangshan urban agglomeration was constructed in this paper. High-resolution remote sensing data (i.e. QuickBird images), medium-resolution remote sensing data (i.e. Landsat TM images in leaf-on and leaf-off seasons), and nighttime light data were used as basic data in this scheme. Five-year ISP results from 1995 to 2016 were estimated to analyze the spatial-temporal evolution patterns of ISP using this scheme. The main conclusions are as follows: (1) The optimal input variables are the Landsat TM images in leaf-on and leaf-off seasons and the corresponding nighttime light data. Since the number of Landsat TM images in leaf-off season is less in line with the quality requirements, the alternative choice is to use the Landsat TM images in leaf-on season and the corresponding nighttime light data as the input variables. After the accuracy verification, the correlation coefficient (R) is about 0.85, which can meet the need of the comparison of ISP results between different years. (2) During 1995 to 2016, the total impervious surface area increased gradually in Beijing-Tianjin-Tangshan urban agglomeration. Within the period, the most dramatic growth was between the year 2011 and 2016. (3) ISP results were divided into areas with high-, medium- and low-density impervious cover. During 1995 to 2016, the high-density and medium-density impervious cover increased gradually in Beijing-Tianjin-Tangshan urban agglomeration, while the low-density impervious cover decreased slightly. The changes of ISP results in each stage were significantly different among cities of Beijing, Tianjin and Tangshan. It shows that the spatial-temporal evolution patterns are different in the process of urban expansion of each city.

  • WANG Xuefeng,FENG Xue,SU Fenzhen,WANG Wuxia,ZHANG Yu,JIANG Huiping
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    Aquaculture land has become widely distributed in recent years. It's difficult to extract aquaculture land for its complexity and inhomogeneity, especially from the medium spatial resolution satellite images. In this paper, we present an automated method containing three main steps to extract aquaculture land from medium spatial resolution images. First, the texture entropy and Normalized Difference Water Index(NDWI) were used to extracted aquaculture land initially. Then, the interrelations of neighboring objects were utilized to merge objects. Finally, a relative new feature called relative width was proposed, and the NDWI was used again to separate the aquaculture land accurately. This method was applied to Van fong Bay, Vietnam using Landsat-8 images whith pixel size of 15m after image fusion. Manual interpretation was conducted in the same region to support and validate our results of the minimum distance method. The result shows that the precision of the proposed method is 91.13%, which is far higher than the traditional object-oriented method. And the missing rate and false rate of the proposed method are 0.09% and 8.87%, respectively, indicating that the proposed method is reliable. This method provides an accurate and efficient means for fast land use mapping from medium resolution imagery.

  • SONG Xiaoyang,HUANG Yaohuan,DONG Donglin,ZHANG Fei
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    Urban land use is a key issue of urban ecology. It is of great significance to understand the urban land use for planning urban functional zones, improving land use efficiency, estimating human population, analyzing urban landscape and promoting regional economic and environmental development. Therefore, urban land use classification research has been one of the core contents of urban planning and urban geography. With the rapid development of Unmanned Aerial Vechicle (UAV) technology, rich UAV data have widely been used in different kinds of fields, especially in the urban land use classification. Digital surface model (DSM) and digital orthophoto map (DOM) obtained from UAV remote sensing images can effectively improve the accuracy of urban land use classification. In order to make full use of the rich information of UAV remote sensing images, an urban land use classification method is proposed using high-resolution DOM and DSM. In this study, the composite bands of DOM and DSM were used as data source. Considering the characteristics of urban land use, the object-oriented classification method was optimized by combining DOM spectral information with DSM, which is used as the final threshold of the pixel merge in multi-resolution segmentation and as height feature in objects classification, respectively. The method was validated in Jingjinxincheng located in Baodi District, Tianjin City. The results showed that, comparing with the initial multi-resolution segmentation method, all of the segmentation quality rate (QR), over-segmentation rate (OR), under-segmentation rate (UR) and comprehensive rate (CR) of optimized multi-resolution segmentation method were reduced, and the effects of image segmentation has been improved significantly. The optimized object-oriented classification method improved the classification accuracy, especially for the extraction of roads, buildings and other constructions. The overall accuracy of the classification results increased from 85% to 87.25% and the Kappa coefficient also increased from 0.79 to 0.82. Therefore, the optimized object-oriented classification method can be used for urban land use study more effectively.