Similarity for spatial directions plays an important role in GIS. In this paper, the conventional approaches are analyzed. Based on raster data areal objects, the authors propose two new methods for measuring similari...Similarity for spatial directions plays an important role in GIS. In this paper, the conventional approaches are analyzed. Based on raster data areal objects, the authors propose two new methods for measuring similarity among spatial directions. One is to measure the similarity among spatial directions based on the features of raster data and the changes of distances between spatial objects, the other is to measure the similarity among spatial directions according to the variation of each raster cell centroid angle. The two methods overcome the complexity of measuring similarity among spatial directions with direction matrix model and solve the limitation of small changes in direction. The two methods are simple and have broader applicability.展开更多
This paper discusses the spatial knowledge related to a line ,and the characteristic points of lines is detected.According to the requirements of line generalization,new algorithms for identifying characteristic line ...This paper discusses the spatial knowledge related to a line ,and the characteristic points of lines is detected.According to the requirements of line generalization,new algorithms for identifying characteristic line points are presented.These characteristic points are used to improve the algorithms of line generalization.An algorithm for identifying bends is shown.In this paper,improved algorithms based on those by Douglas_Peucker,Visvalingam and Whyatt are shown.In this test,the progressive process of line generalization is emphasized.展开更多
文摘Similarity for spatial directions plays an important role in GIS. In this paper, the conventional approaches are analyzed. Based on raster data areal objects, the authors propose two new methods for measuring similarity among spatial directions. One is to measure the similarity among spatial directions based on the features of raster data and the changes of distances between spatial objects, the other is to measure the similarity among spatial directions according to the variation of each raster cell centroid angle. The two methods overcome the complexity of measuring similarity among spatial directions with direction matrix model and solve the limitation of small changes in direction. The two methods are simple and have broader applicability.
文摘This paper discusses the spatial knowledge related to a line ,and the characteristic points of lines is detected.According to the requirements of line generalization,new algorithms for identifying characteristic line points are presented.These characteristic points are used to improve the algorithms of line generalization.An algorithm for identifying bends is shown.In this paper,improved algorithms based on those by Douglas_Peucker,Visvalingam and Whyatt are shown.In this test,the progressive process of line generalization is emphasized.
