期刊：
ISPRS International Journal of Geo-Information,2020年9(6):410 ISSN：2220-9964
通讯作者：
Xiao, Jia
作者机构：
[Xiao, Jia; Liu, Pengcheng] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China.;[Xiao, Jia; Liu, Pengcheng] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
通讯机构：
[Xiao, Jia] C;Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
关键词：
level of detail;graphical unit;geographical feature;digital map
摘要：
This paper proposes a method to evaluate the level of detail (LoD) of geographic features on digital maps and assess their LoD consistency. First, the contour of the geometry of the geographic feature is sketched and the hierarchy of its graphical units is constructed. Using the quartile measurement method of statistical analysis, outliers of graphical units are eliminated and the average value of the graphical units below the bottom quartile is used as the statistical LoD parameter for a given data sample. By comparing the LoDs of homogeneous and heterogeneous features, we analyze the differences between the nominal scale and actual scale to evaluate the LoD consistency of features on a digital map. The validation of this method is demonstrated by experiments conducted on contour lines at a 1:5K scale and artificial building polygon data at scales of 1:2K and 1:5K. The results show that our proposed method can extract the scale of features on maps and evaluate their LoD consistency.
作者机构：
[肖天元; 刘鹏程] Key Laboratory for Geographical Process Analysis & Simulation, Central China Normal University, Wuhan;430079, China;School of Urban and Environmental Science, Central China Normal University, Wuhan;[艾廷华; 李精忠] School of Resource and Environmental Sciences, Wuhan University, Wuhan;[肖天元; 刘鹏程] 430079, China <&wdkj&> School of Urban and Environmental Science, Central China Normal University, Wuhan
期刊：
International Journal of Geographical Information Science,2020年34(11):2275-2295 ISSN：1365-8816
通讯作者：
Xiao, Jia
作者机构：
[Xiao, Tianyuan; Xiao, Jia; Liu, Pengcheng] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan, Peoples R China.;[Xiao, Tianyuan; Xiao, Jia; Liu, Pengcheng] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China.;[Ai, Tinghua] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.
通讯机构：
[Xiao, Jia] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Peoples R China.
作者机构：
[刘鹏程; 肖天元; 肖佳] School of Urban and Environmental Sciences, Central China Normal University, Wuhan;430079, China;Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province, Central China Normal University, Wuhan;[艾廷华] School of Resource and Environment Sciences, Wuhan University, Wuhan;[刘鹏程; 肖天元; 肖佳] 430079, China<&wdkj&>Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province, Central China Normal University, Wuhan
通讯机构：
[Xiao, J.] S;School of Urban and Environmental Sciences, China
作者机构：
[刘鹏程; 肖天元] Key Laboratory for Geographical Process Analysis & Simulation of Hubei Prorince, College of Urban and Environmental Science, Central China Normal University, Wuhan;Hubei;430079, China;[艾廷华; 杨敏] School of Resource and Environmental Sciences, Wuhan University, Wuhan;[刘鹏程; 肖天元; 艾廷华; 杨敏] Hubei
作者机构：
[刘鹏程] Key Laboratory for Geographical Process Analysis &, Simulation, College of Urban and Environmental Science, Central China Normal University, Wuhan, Hubei, 430079, China;[艾廷华; 李精忠] School of Resource and Environmental Sciences, Wuhan University, Wuhan, Hubei, 430079, China
通讯机构：
Key Laboratory for Geographical Process Analysis & Simulation, College of Urban and Environmental Science, Central China Normal University, Wuhan, Hubei, China
关键词：
Fourier analysis;Interpolation;Polygons;Geographic information systems;Computer graphics;Experimental design;Ellipses;Algorithms
摘要：
This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features' continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable.
摘要：
The representation and analysis of building patterns are critical for characterizing urban scenes and making decisions in urban planning. The evaluation of building patterns is a difficult spatial analysis problem that exhibits properties of symbolization, homogeneity and regularity. Open issues in this field include the development of approaches for representing building patterns and vector-based methods for computing various pattern metrics. In the image analysis domain, there are many methods for pattern recognition e.g., texture analysis, but there are few corresponding solutions for vector data. The aim of this research is to develop several building pattern metrics and offer a texton co-occurrence matrix TCM-based method to quantitatively evaluate the features of building patterns. The procedure first constructs a spatial field based on a Delaunay triangulation skeleton to partition a set of buildings into a set of tessellation cells. The tessellations of building clusters have a similar structure as image representations, in that each cell corresponds to an image pixel. We then use the texton analysis to establish a matrix to describe the tessellation structure, including the neighboring relationships and individual attribute information. Finally, a set of feature descriptors is obtained from the TCM to capture the texture-related information of building groups. Through experiments on building pattern analysis and spatial queries, we show that the results of TCM-based evaluation of building patterns are consistent with those of human cognition. The representation and analysis of building patterns are critical for characterizing urban scenes and making decisions in urban planning. The evaluation of building patterns is a difficult spatial analysis problem that exhibits properties of symbolization, homogeneity and regularity. Open issues in this field include the development of approaches for representing building patterns and vector-based methods for computing various pattern metrics. In the image analysis domain, there are many methods for pattern recognition e.g., texture analysis, but there are few corresponding solutions for vector data. The aim of this research is to develop several building pattern metrics and offer a texton co-occurrence matrix TCM-based method to quantitatively evaluate the features of building patterns. The procedure first constructs a spatial field based on a Delaunay triangulation skeleton to partition a set of buildings into a set of tessellation cells. The tessellations of building clusters have a similar structure as image representations, in that each cell corresponds to an image pixel. We then use the texton analysis to establish a matrix to describe the tessellation structure, including the neighboring relationships and individual attribute information. Finally, a set of feature descriptors is obtained from the TCM to capture the texture-related information of building groups. Through experiments on building pattern analysis and spatial queries, we show that the results of TCM-based evaluation of building patterns are consistent with those of human cognition.
关键词：
morphing;simulated annealing;detection of characteristic points;matching of characteristic points;continuous generalization
摘要：
This paper presents a new method for use in performing continuous scale transformations of linear features using Simulated Annealing-Based Morphing (SABM). This study addresses two key problems in the continuous generalization of linear features by morphing, specifically the detection of characteristic points and correspondence matching. First, an algorithm that performs robust detection of characteristic points is developed that is based on the Constrained Delaunay Triangulation (CDT) model. Then, an optimal problem is defined and solved to associate the characteristic points between a coarser representation and a finer representation. The algorithm decomposes the input shapes into several pairs of corresponding segments and uses the simulated annealing algorithm to find the optimal matching. Simple straight-line trajectories are used to define the movements between corresponding points. The experimental results show that the SABM method can be used for continuous generalization and generates smooth, natural and visually pleasing linear features with gradient effects. In contrast to linear interpolation, the SABM method uses the simulated annealing technique to optimize the correspondence between characteristic points. Moreover, it avoids interior distortions within intermediate shapes and preserves the geographical characteristics of the input shapes.
