An Intelligent Cartographic Generalization Algorithm Selecting Mode Used in Multi-scale Spatial Data Updating Process

Author(s):  
Junkui Xu ◽  
Dong Li ◽  
Longfei Cui ◽  
Xing Zhang
2019 ◽  
Vol 8 (2) ◽  
pp. 72 ◽  
Author(s):  
Yi Qiang ◽  
Nico Van de Weghe

The representations of space and time are fundamental issues in GIScience. In prevalent GIS and analytical systems, time is modeled as a linear stream of real numbers and space is represented as flat layers with timestamps. Despite their dominance in GIS and information visualization, these representations are inefficient for visualizing data with complex temporal and spatial extents and the variation of data at multiple temporal and spatial scales. This article presents alternative representations that incorporate the scale dimension into time and space. The article first reviews a series of work about the triangular model (TM), which is a multi-scale temporal model. Then, it introduces the pyramid model (PM), which is the extension of the TM for spatial data, and demonstrates the utility of the PM in visualizing multi-scale spatial patterns of land cover data. Finally, it discusses the potential of integrating the TM and the PM into a unified framework for multi-scale spatio-temporal modeling. This article systematically documents the models with alternative arrangements of space and time and their applications in analyzing different types of data. Additionally, this article aims to inspire the re-thinking of organizations of space, time, and scales in the future development of GIS and analytical tools to handle the increasing quantity and complexity of spatio-temporal data.


Author(s):  
Huijun Gao ◽  
Hao Zhang ◽  
Daosheng Hu ◽  
Ran Tian ◽  
Dazhi Guo

2018 ◽  
Vol 22 (2) ◽  
pp. 435-454 ◽  
Author(s):  
Min Yang ◽  
Tinghua Ai ◽  
Xiongfeng Yan ◽  
Yuanyuan Chen ◽  
Xiang Zhang

2013 ◽  
Vol 659 ◽  
pp. 118-122
Author(s):  
Lu Kong ◽  
Ying Zi Song ◽  
Da Ming You

Meteorological and hydrological data has the feature of multi-semantic space, multi-space-time, multi-scale and it has a diversed means to be acquired and storaged, which brings the diversity of multi-origin characteristics. This paper will adopt the method of data assimilation to study a variety of data models with different scales and the key technology the grid resolution spatial data integration in order to establish a meteorological and hydrological model of multi-source spatial data assimilation.


Author(s):  
Han Yue ◽  
Xinyan Zhu ◽  
Di Chen ◽  
Lingjia Liu

Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.


Author(s):  
Han Yue ◽  
Xinyan Zhu ◽  
Di Chen ◽  
Lingjia Liu

Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.


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