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Zhao H.-J.,Key Laboratory of Coastal Disasters and Defence | Zhao H.-J.,Hohai University | Song Z.-Y.,Key Laboratory of Virtual Geographic Environment | Song Z.-Y.,Nanjing Normal University | And 6 more authors.
China Ocean Engineering | Year: 2016

This paper presents a universal fifth-order Stokes solution for steady water waves on the basis of potential theory. It uses a global perturbation parameter, considers a depth uniform current, and thus admits the flexibilities on the definition of the perturbation parameter and on the determination of the wave celerity. The universal solution can be extended to that of Chappelear (1961), confirming the correctness for the universal theory. Furthermore, a particular fifth-order solution is obtained where the wave steepness is used as the perturbation parameter. The applicable range of this solution in shallow depth is analyzed. Comparisons with the Fourier approximated results and with the experimental measurements show that the solution is fairly suited to waves with the Ursell number not exceeding 46.7. © 2016, Chinese Ocean Engineering Society and Springer-Verlag Berlin Heidelberg.


Shen C.,Nanjing Normal University | Shen C.,Jiangsu Center for Collaborative Innovation in Geographical Information Resource | Shen C.,Key Laboratory of Virtual Geographic Environment | Li C.,Nanjing Normal University | Si Y.,Nanjing Normal University
Physics Letters, Section A: General, Atomic and Solid State Physics | Year: 2016

In order to measure the spatio-temporal autocorrelation's degree for spatio-temporal nonstationary series, the new temporally detrended global and local spatio-temporal Moran's indexes (TDGSTI and TDLSTI) are proposed. The implementation of the new Moran's indexes is illustrated through artificial and real examples. Analyses of the influencing factors on TDGSTI are performed. A statistical test of TDGSTI is taken. The Moran's scatter plot, which discloses the spatio-temporal cluster pattern's characteristics and pattern's change, is extended. TDGSTI is found to reveal the autocorrelation level of spatio-temporal objects. For a positive TDGSTI, the higher the TDGSTI, the higher the autocorrelation level, and vice versa. TDGSTI is closely related to time-scale s, time-lag h and spatio-temporal weight matrix. For s∼h, TDGSTI is significant, while for s∼h and s


Qin C.-Z.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research | Qin C.-Z.,Jiangsu Center for Collaborative Innovation | Qin C.-Z.,University of Chinese Academy of Sciences | Wu X.-W.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research | And 6 more authors.
Hydrology and Earth System Sciences | Year: 2016

Application of digital terrain analysis (DTA), which is typically a modeling process involving workflow building, relies heavily on DTA domain knowledge of the match between the algorithm (and its parameter settings) and the application context (including the target task, the terrain in the study area, the DEM resolution, etc.), which is referred to as application-context knowledge. However, existing DTA-assisted tools often cannot use application-context knowledge because this type of DTA knowledge has not been formalized to be available for inference in these tools. This situation makes the DTA workflow-building process difficult for users, especially non-expert users. This paper proposes a case-based formalization for DTA application-context knowledge and a corresponding case-based reasoning method. A case in this context consists of a series of indices that formalize the DTA application-context knowledge and the corresponding similarity calculation methods for case-based reasoning. A preliminary experiment to determine the catchment area threshold for extracting drainage networks has been conducted to evaluate the performance of the proposed method. In the experiment, 124 cases of drainage network extraction (50 for evaluation and 74 for reasoning) were prepared from peer-reviewed journal articles. Preliminary evaluation shows that the proposed case-based method is a suitable way to use DTA application-context knowledge to achieve a marked reduction in the modeling burden for users. © 2016 Author(s).


Lu J.,Key Laboratory of Virtual Geographic Environment | Tang G.-A.,Key Laboratory of Virtual Geographic Environment
2011 International Conference on Multimedia Technology, ICMT 2011 | Year: 2011

Based on the geographically weighted regression (GWR) model, carries a cause analysis for the spatial distribution of theft crime rate. There is a negative correlation between population density and theft crime rate, but the correlation is not significant; the theft crime rate has a positive correlation with road network and police intensity, and the correlation is significant in most streets; there are negative and positive correlation between theft crime rate and average land price, but negative correlation is in most streets and the correlation is not significant. It shows that many social factors have some influence upon the spatial distribution of theft crime rate, and the GWR model is indeed able to analysis the cause of crime rate spatial distribution. © 2011 IEEE.


Lu G.,Key Laboratory of Virtual Geographic Environment | Lu G.,State Key Laboratory Cultivation Base of Geographic Environment Evolution Jiangsu Province | Lu G.,Nanjing Normal University | Yu Z.,Key Laboratory of Virtual Geographic Environment | And 14 more authors.
Environmental Earth Sciences | Year: 2015

Virtual geographic environment (VGE) aims to express the real-world naturally, and support the complex geographic analysis. The data environment, fundamental of VGE, is expected to support the data management, analysis, sharing and application requirements of the massive complex geographic spatio-temporal data. In this paper, we summarized the key problems in the construction of the data environment of VGE. The unified spatio-temporal data model and a new data structure were developed according to the geographic rules. The organization and compress storage mechanism of massive spatio-temporal data were also developed. With these foundations, case studies, which integrate the global, regional and city scale data to operate complex data modeling and analysis, are performed. The results showed that the construction of the integrated data environment of VGE can largely improve the efficiency of GIS analysis, which also provides a potential new tool to support the complex geographic analysis. © 2015, Springer-Verlag Berlin Heidelberg.


Zhang X.,Key Laboratory of Virtual Geographic Environment | Zhu S.,Key Laboratory of Virtual Geographic Environment
2010 2nd IITA International Conference on Geoscience and Remote Sensing, IITA-GRS 2010 | Year: 2010

Place names have been one of the most commonly-preferred georeferencing systems used to communicate geographically-specific information in our daily lives. Gazetteers as specialized geographical information systems bridge the gap between textual place names and geospatial locations. Most place names in gazetteers are thought of as administrative regions and described with official names. However, a place name could also be a thematic region, a functional region or a cognitive region. There is hence a need to enrich gazetteers with such vague place names and extend their applications. Geospatial location and boundary of vague place names can be induced based on the descriptions of its referred geographical entities and spatial relations in context. Here an approach is proposed to approximately model vague place names based on contextual spatial relations. Computational models for qualitative spatial relations are identified to model single spatial relations and a layer-overlapping method is presented to compute composed spatial relations. A few typical examples further explore the detailed processing tasks and performance. Finally, an application case is illustrated and various aspects of the approach are discussed. © 2010 IEEE.


Yuan L.,Key Laboratory of Virtual Geographic Environment | Yuan L.,Nanjing Normal University | Yu Z.,Key Laboratory of Virtual Geographic Environment | Yu Z.,Nanjing Normal University | And 4 more authors.
Computers and Geosciences | Year: 2013

Vector field segmentation is gaining increasing importance in geophysics research. Existing vector field segmentation methods usually can only handle the statistical characteristics of the original data. It is hard to integrate the patterns forced by certain geophysical phenomena. In this paper, a template matching method is firstly constructed on the foundation of the Clifford Fourier Transformation (CFT). The geometric meanings of both inner and outer components can provide more attractive information about the similarities between original vector field and template data. A composed similarity field is constructed based on the coefficients fields. After that, a modified spatial consistency preserving K-Means cluster algorithm is proposed. This algorithm is applied to the similarity fields to extract the template forced spatial distribution pattern. The complete algorithm for the overall processing is given and the experiments of ENSO forced global ocean surface wind segmentation are configured to test our method. The results suggest that the pattern forced segmentation can extract more latent information that cannot be directly measured from the original data. And the spatial distribution of ENSO influence on the surface wind field is clearly given in the segmentation result. All the above suggest that the method we proposed provides powerful and new thoughts and tools for geophysical vector field data analysis. © 2013 Elsevier Ltd.

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