Delineating tree crowns from airborne laser scanning point cloud data using Delaunay triangulation

Most algorithms for delineating trees from laser scanning data are pixel‐based region growing methods. The algorithm presented in this letter makes use of the original laser points to avoid errors introduced by interpolation. Three different scales are used to identify the seed points or the local maxima at that scale. The seed points are considered to be the estimated tree tops, and are used for growing regions or tree crowns around the seed points. For a test dataset from a Finnish mixed forest and point density of approximately 2 points m^?2, up to 75% of the reference trees could be identified. At the coarser scales, fewer trees were identified, but the crowns were less fragmented. Further work is required to determine how far the method is applicable in other forest conditions and data with other point densities.     

添加剂对鳞片石墨在水介质中分散性能的影响

以鳞片石墨在水介质中的沉降率和分散率作为评价指标,研究了7种添加剂单独以及复合添加对鳞片石墨在水介质中分散性能的影响。结果表明:十二烷基苯磺酸钠和十二烷基硫酸钠对石墨在液相中的分散效果显著,分散率分别为97.8%和80.0%,0.5h时的沉降率分别为92.0%和94.0%,但稳定性不好;通过正交试验方法得出最佳添加剂配方,即十二烷基硫酸钠添加量为4.7%(质量分数,下同),N-乙酰-L-脯氨酸添加量为3.7%和磷酸三丁酯添加量为2.6%,按该最佳配方添加时鳞片石墨在水介质中的分散率达到99.2%,1h时的沉降率为92.0%;在用最佳配方制备的银-石墨复合镀层中,鳞片石墨已被均匀分散在银层中。     

An approach to classification of airborne laser scanning point cloud data in an urban environment

Digital topographic data, including detailed maps required for urban planning, are still unavailable in many parts of the world. Airborne laser scanning (ALS) has the unique ability to provide geo-referenced three-dimensional data useful for the mapping of urban features. This article examines the performance of decision tree classifiers on two ALS data sets, collected in different seasons from different flying heights with different scanners using laser beams at different wavelengths – 1550 and 1064 nm – for the same study area. Classification was undertaken on the point clouds based on attributes derived from the triangulated irregular network (TIN) triangles attached to a point, as well as attributes of the individual points. Classification accuracies of 0.68 and 0.92 (kappa coefficient) could be achieved for the two data sets. Decision tree seems to be a classification method that is particularly suitable for geographic information system (GIS), as it can be converted to ‘if–then’ rules that can be implemented fully within a GIS environment. Grass and paved areas could be distinguished better using intensity from one data set than the other, which could be related to the wavelengths of the lasers, and need to be explored further.     

Computer Reliability Optimization System

The short electronic system development time, the acute competitiveness, the emphasis on lower costs, and the insistence upon high reliability has fostered practical computerization of the manager's and designer's reliability function. This computerization attempts to achieve feasible system optimization. The Computerized Reliability Optimization System (CROS) was developed by Hoffman Electronics Corporation's Computer-Aided-Design, Analysis, and Reliability Group to provide an optimum solution to the present system reliability methods. CROS is a comprehensive set of computer programs and a complementary design and management method for handling the total reliability function from proposal effort through the production and field-data analysis. The organization, application, feasibility, and results of CROS are discussed.