Approach to calculating spatial similarity degrees of the same river basin networks on multi-scale maps

Obtaining spatial similarity degrees among the same objects on multi-scale maps is of importance in map generalization. This paper firstly defines the concepts of ‘map scale change’ and ‘spatial similarity degree’; then it proposes a model for calculating the spatial similarity degree between a river basin network at one scale and its generalized version at another scale. After this, it validates the new model and gets 16 points in the model validation process. The x-coordinate and y-coordinate of each point are map scale change and spatial similarity degree, respectively. Last, a formula for calculating spatial similarity degree taking map scale change as the only variable is obtained by the curve fitting method. The formula along with the model can be used to automate the algorithms for simplifying river basin networks.

[1]  Haowen Yan Quantitative relations between spatial similarity degree and map scale change of individual linear objects in multi-scale map spaces , 2015 .

[2]  Rupert Brooks,et al.  Exploiting Perceptual Grouping for Map Analysis, Understanding and Generalization: The Case of Road and River Networks , 2001, GREC.

[3]  I. A. Chaikovsky,et al.  Terminology for model credibility , 1979 .

[4]  P. Hofstaetter [Similarity]. , 2020, Psyche.

[5]  Haowen Yan,et al.  Fundamental theories of spatial similarity relations in multi-scale map spaces , 2010 .

[6]  Robert G. Sargent,et al.  Verification and validation of simulation models , 2013, Proceedings of Winter Simulation Conference.

[7]  Max J. Egenhofer,et al.  Determining Semantic Similarity among Entity Classes from Different Ontologies , 2003, IEEE Trans. Knowl. Data Eng..

[8]  Jonathan Li,et al.  An approach to computing direction relations between separated object groups , 2013 .

[9]  M. Egenhofer,et al.  Point-Set Topological Spatial Relations , 2001 .

[10]  Donald E. Knuth,et al.  The Art of Computer Programming, Volume I: Fundamental Algorithms, 2nd Edition , 1997 .

[11]  Arthur B. Markman,et al.  Constraints on Analogical Inference , 1997, Cogn. Sci..

[12]  Jack P. C. Kleijnen,et al.  EUROPEAN JOURNAL OF OPERATIONAL , 1992 .

[13]  A. Krall Applied Analysis , 1986 .

[14]  Thomas H. Naylor,et al.  Verification of Computer Simulation Models , 1967 .

[15]  Saul I. Gass,et al.  Model accreditation: A rationale and process for determining a numerical rating , 1993 .

[16]  Gunnar Abrahamson,et al.  Terminology for model credibility , 1980 .

[17]  Renzo Rosso,et al.  Fractal relation of mainstream length to catchment area in river networks , 1991 .

[18]  Shihong Du,et al.  Reasoning about topological relations between regions with broad boundaries , 2008, Int. J. Approx. Reason..

[19]  Zhang Qing-nian Generalization of Drainage Network with Density Differences , 2006 .

[20]  Jung-Hong Hong,et al.  Qualitative distance and direction reasoning in geographic space , 1995 .

[21]  Donald E. Knuth The art of computer programming: fundamental algorithms , 1969 .

[22]  J.S. Carson,et al.  Model verification and validation , 2002, Proceedings of the Winter Simulation Conference.

[23]  Osman Balci,et al.  How To Assess The Acceptability And Credibility Of Simulation Results , 1989, 1989 Winter Simulation Conference Proceedings.

[24]  R. Horton EROSIONAL DEVELOPMENT OF STREAMS AND THEIR DRAINAGE BASINS; HYDROPHYSICAL APPROACH TO QUANTITATIVE MORPHOLOGY , 1945 .

[25]  Robert G. Sargent,et al.  A New Statistical Procedure for Validation of Simulation and Stochastic Models , 2010 .

[26]  Haowen Yan,et al.  A Quantitative Description Model for Direction Relations Based on Direction Groups , 2006, GeoInformatica.

[27]  R. K. Goyal,et al.  Similarity assessment for cardinal directions between extended spatial objects , 2000 .

[28]  Max J. Egenhofer,et al.  Comparing geospatial entity classes: an asymmetric and context-dependent similarity measure , 2004, Int. J. Geogr. Inf. Sci..

[29]  Lawrence V. Stanislawski,et al.  Feature pruning by upstream drainage area to support automated generalization of the United States National Hydrography Dataset , 2009, Comput. Environ. Urban Syst..

[30]  Robert A. Wilson,et al.  Book Reviews: The MIT Encyclopedia of the Cognitive Sciences , 2000, CL.

[31]  Frederico T. Fonseca,et al.  TDD - A Comprehensive Model for Qualitative Spatial Similarity Assessment , 2005 .

[32]  J. Banks,et al.  Discrete-Event System Simulation , 1995 .

[33]  R. Rosso,et al.  On the fractal dimension of stream networks , 1989 .

[34]  B. Serres,et al.  FLOW DIRECTION AND BRANCHING GEOMETRY AT JUNCTIONS IN DENDRITIC RIVER NETWORKS , 1990 .