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Comparison of the minimum bounding rectangle and minimum Circumscribed Ellipse of Rain Cells from TRMM

Advances in Atmospheric Sciences 2024年第3期41卷 391-406页

作者： Hongke CAI Yaqin MAO Xuanhao ZHU Yunfei FU Renjun ZHOU Plateau Atmospheric and Environment Laboratory of Sichuan Province School of Atmospheric SciencesChengdu University of Information TechnologyChengdu 610225China School of Earth and Space Sciences University of Science and Technology of ChinaHefei 230026China Center for Atmospheric Optics Anhui Institute of Optics and Fine MechanicsChinese Academy of SciencesHefei 230031China

Based on the TRMM dataset, this paper compares the applicability of the improved MCE(minimum circumscribed ellipse), MBR(minimum bounding rectangle), and DIA(direct indexing area) methods for rain cell fitting. These three methods can reflect the geometric characteristics of clouds and apply geometric parameters to estimate the real dimensions of rain cells. The MCE method shows a major advantage in identifying the circumference of rain cells. The circumference of rain cells identified by MCE in most samples is smaller than that identified by DIA and MBR, and more similar to the observed rain cells. The area of rain cells identified by MBR is relatively robust. For rain cells composed of many pixels(N> 20), the overall performance is better than that of MCE, but the contribution of MBR to the best identification results,which have the shortest circumference and the smallest area, is less than that of MCE. The DIA method is best suited to small rain cells with a circumference of less than 100 km and an area of less than 120 km^(2), but the overall performance is mediocre. The MCE method tends to achieve the highest success at any angle, whereas there are fewer “best identification”results from DIA or MBR and more of the worst ones in the along-track direction and cross-track direction. Through this comprehensive comparison, we conclude that MCE can obtain the best fitting results with the shortest circumference and the smallest area on behalf of the high filling effect for all sizes of rain cells.

关键词： TRMM minimum bounding rectangle minimum circumscribed ellipse

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Helicopter maritime search area planning based on a minimum bounding rectangle and K-means clustering

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Chinese Journal of Aeronautics 2021年第2期34卷 554-562页

作者： Peisen XIONG Hu LIUa Yongliang TIAN Zikun CHEN Bin WANG Hao YANG School of Aeronautic Science and Engineering Beihang UniversityBeijing 100083China Dong Hai No.2 Rescue Flying Service of The Ministry of Transport Xiamen 361006China

Helicopters are widely used in maritime Search and Rescue(SAR) missions. To ensure the success of SAR missions, search areas need to be carefully planned. With the development of computer technology and weather forecast technology, the survivors’ drift trajectories can be predicted more precisely, which strongly supports the planning of search areas for the rescue helicopter. However, the methods used to determine the search area based on the predicted drift trajectories are mainly derived from the continuous expansion of the area with the highest Probability of Containment(POC), which may lead to local optimal solutions and a decrease in the Probability of Success(POS), especially when there are several subareas with a high POC. To address this problem, this paper proposes a method based on a minimum bounding rectangle and Kmeans clustering(MBRK). A silhouette coefficient is adopted to analyze the distribution of the survivors’ probable locations, which are divided into multiple clusters with K-means clustering. Then,probability maps are generated based on the minimum bounding rectangle of each cluster. By adding or subtracting one row or column of cells or shifting the planned search area, 12 search methods are used to generate the optimal search area starting from the cell with the highest POC in each probability map. Taking a real case as an example, the simulation experiment results show that the POS values obtained by the MBRK method are higher than those obtained by other methods,which proves that the MBRK method can effectively support the planning of search areas and that K-means clustering improves the POS of search plans.

关键词： K-means clustering minimum bounding rectangle Mission planning Probability map Search and rescue

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空间数据库中R树索引的设计

空间数据库中R树索引的设计

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第十九届全国数据库学术会议

作者：章秀静谢昆青陈冠华北京大学信息科学中心视觉与听觉信息处理国家重点实验室

1.引言地理信息系统(Geographic Information System——GIS)在许多领域都得到日益广泛的应用。随着以计算机为基础的空间地理信息获取和应用能力的不断提高,人们开始提出创建基于地理数据的空间数据库管理系统。由于地理数据的数据量... 详细信息

1.引言地理信息系统(Geographic Information System——GIS)在许多领域都得到日益广泛的应用。随着以计算机为基础的空间地理信息获取和应用能力的不断提高,人们开始提出创建基于地理数据的空间数据库管理系统。由于地理数据的数据量大、结

关键词： R-tree index minimum bounding rectangle Split node

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