Code and Data for Linear Building Pattern Recognition

The Code is developed to support the findings of our submitted paper entitled "Linear building pattern recognition in topographical maps using convex polygon decomposition" The tools were implemented in C# on ArcGIS 10.2 software (ESRI, USA), each tool has a separate form to set the input, output and parameters for the algorithms. The tool for linear pattern recognition, and 4 tools are included. As follows (1) Tool for proximity graph generation based on CDT and skeletons considering roads, including CDT, DT like proximity graph, GG, RNG, MST and NNG. (2) Tool for parameter computation for building characteristics, including 24 parameters of building polygons. Details for the proximity graphs and parameters of buildings' characteristics refer to: Wei Z, Guo Q, Wang L, et al. On the spatial distribution of buildings for map generalization[J]. Cartography and Geographic Information Science, 2018, 45(6): 539-555. https://www.tandfonline.com/doi/abs/10.1080/15230406.2018.1433068?casa_token=R-2k-CETpaoAAAAA:sLyJdI_1DB-Tz848gPjgwX24byKF6tyBF5mWSL-PXXw-9Z4JXgkIXexwyKdKtEufcZfQdqskoG_wbWA 郭庆胜, 魏智威, 王勇, 王琳. 特征分类与邻近图相结合的建筑物群空间分布特征提取方法[J]. 测绘学报, 2017, 46(5): 631-638.（GUO Qingsheng, WEI Zhiwei, WANG Yong, WANG Lin. The Method of Extracting Spatial Distribution Characteristics of Buildings Combined with Feature Classification and Proximity Graph[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(5): 631-638.）http://xb.sinomaps.com/CN/10.11947/j.AGCS.2017.20160374 (3) Tool for convex building polygon decomposition.Details for building decomposition, refer to: 顾及结构特征的建筑物图形迭代凸分解方法-An iterative approach for building convex decomposition considering their shape characteristics，upcoming in 测绘科学 (4) Tool for linear pattern recognition, including collinear and curvilinear patterns.本代码旨在支撑已投稿的题为"基于凸多边形分解的地形图线状建筑格局识别"（Linear building pattern recognition in topographical maps using convex polygon decomposition）的论文的研究结论。 本工具集基于C#语言在ArcGIS 10.2软件（美国ESRI公司）中开发，每个工具均配备独立的配置界面，用于设置算法的输入项、输出路径与运算参数。 本工具集包含线状建筑格局识别工具，共计4款工具，详情如下：(1) 基于约束德劳内三角网（Constrained Delaunay Triangulation, CDT）与考虑道路要素的骨架线生成邻近图工具，支持约束德劳内三角网、类德劳内邻近图、加布里埃尔图（Gabriel Graph, GG）、相对邻近图（Relative Neighborhood Graph, RNG）、最小生成树（Minimum Spanning Tree, MST）以及最近邻图（Nearest Neighbor Graph, NNG）的生成。(2) 建筑特征参数计算工具，可提取建筑多边形的24项特征参数。有关邻近图与建筑特征参数的详细说明，请参阅：Wei Z, Guo Q, Wang L, et al. On the spatial distribution of buildings for map generalization[J]. Cartography and Geographic Information Science, 2018, 45(6): 539-555. https://www.tandfonline.com/doi/abs/10.1080/15230406.2018.1433068?casa_token=R-2k-CETpaoAAAAA:sLyJdI_1DB-Tz848gPjgwX24byKF6tyBF5mWSL-PXXw-9Z4JXgkIXexwyKdKtEufcZfQdqskoG_wbWA 郭庆胜, 魏智威, 王勇, 王琳. 特征分类与邻近图相结合的建筑物群空间分布特征提取方法[J]. 测绘学报, 2017, 46(5): 631-638.（GUO Qingsheng, WEI Zhiwei, WANG Yong, WANG Lin. The Method of Extracting Spatial Distribution Characteristics of Buildings Combined with Feature Classification and Proximity Graph[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(5): 631-638.）http://xb.sinomaps.com/CN/10.11947/j.AGCS.2017.20160374 (3) 建筑凸多边形分解工具，有关建筑图形分解的详细方法，请参阅《顾及结构特征的建筑物图形迭代凸分解方法》（An iterative approach for building convex decomposition considering their shape characteristics），该文已被《测绘科学》录用待刊。(4) 线状建筑格局识别工具，可识别共线型与曲线型建筑格局。