With the rapid development of reality capture methods,such as laser scanning and oblique photogrammetry,point cloud data have become the third most important data source,after vector maps and imagery.Point cloud data ...With the rapid development of reality capture methods,such as laser scanning and oblique photogrammetry,point cloud data have become the third most important data source,after vector maps and imagery.Point cloud data also play an increasingly important role in scientific research and engineering in the fields of Earth science,spatial cognition,and smart cities.However,how to acquire high-quality three-dimensional(3D)geospatial information from point clouds has become a scientific frontier,for which there is an urgent demand in the fields of surveying and mapping,as well as geoscience applications.To address the challenges mentioned above,point cloud intelligence came into being.This paper summarizes the state-of-the-art of point cloud intelligence,with regard to acquisition equipment,intelligent processing,scientific research,and engineering applications.For this purpose,we refer to a recent project on the hybrid georeferencing of images and LiDAR data for high-quality point cloud collection,as well as a current benchmark for the semantic segmentation of high-resolution 3D point clouds.These projects were conducted at the Institute for Photogrammetry,the University of Stuttgart,which was initially headed by the late Prof.Ackermann.Finally,the development prospects of point cloud intelligence are summarized.展开更多
Professor Emeritus of Photogrammetry and Surveying and Former Director of the Institute for Photogrammetry at the University of Stuttgart We mourn the loss of our dear colleague and institute founder Friedrich(Fritz)A...Professor Emeritus of Photogrammetry and Surveying and Former Director of the Institute for Photogrammetry at the University of Stuttgart We mourn the loss of our dear colleague and institute founder Friedrich(Fritz)Ackermann,who passed away on 4 December 2021.He founded the Institute for Photogrammetry with his appointment to the University of Stuttgart on 1 April 1966,and was its director until 31 March 1992.With his research and development work in the field of analytical and digital photogrammetry,he significantly influenced the developments and progress in these two fields and helped the Institute of Photogrammetry to achieve a worldwide reputation.For many younger photogrammetrists he was always a role model and stood for the close connection between basic research and application.With the software developments he initiated with his spin-off inpho GmbH,Stuttgart(today Trimble),he was able to drive very successful technology transfer from research to practice.展开更多
This paper presents an innovative method to facilitate making such a plan. Using an algorithm to schedule the starting time of each evacuation group, the method guarantees that the time of completing a large-scale eva...This paper presents an innovative method to facilitate making such a plan. Using an algorithm to schedule the starting time of each evacuation group, the method guarantees that the time of completing a large-scale evacuation is very close to its theoretically shortest evacuation time. Meanwhile, unlike a simultaneous evacuation, during a staged evacuation planned with the proposed method, all evacuees can take the shortest path to a safe exit. Once evacuees start off, they will not suffer any traffic congestion. The above advantages of this innovative method are achieved by using an algorithm with three nested loops. Experiments have been conducted, and their results have validated the proposed method.展开更多
基金supported by the National Natural Science Foundation Project(No.42130105)Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in_Megacities,MNR(No.KFKT-2022-01).
文摘With the rapid development of reality capture methods,such as laser scanning and oblique photogrammetry,point cloud data have become the third most important data source,after vector maps and imagery.Point cloud data also play an increasingly important role in scientific research and engineering in the fields of Earth science,spatial cognition,and smart cities.However,how to acquire high-quality three-dimensional(3D)geospatial information from point clouds has become a scientific frontier,for which there is an urgent demand in the fields of surveying and mapping,as well as geoscience applications.To address the challenges mentioned above,point cloud intelligence came into being.This paper summarizes the state-of-the-art of point cloud intelligence,with regard to acquisition equipment,intelligent processing,scientific research,and engineering applications.For this purpose,we refer to a recent project on the hybrid georeferencing of images and LiDAR data for high-quality point cloud collection,as well as a current benchmark for the semantic segmentation of high-resolution 3D point clouds.These projects were conducted at the Institute for Photogrammetry,the University of Stuttgart,which was initially headed by the late Prof.Ackermann.Finally,the development prospects of point cloud intelligence are summarized.
文摘Professor Emeritus of Photogrammetry and Surveying and Former Director of the Institute for Photogrammetry at the University of Stuttgart We mourn the loss of our dear colleague and institute founder Friedrich(Fritz)Ackermann,who passed away on 4 December 2021.He founded the Institute for Photogrammetry with his appointment to the University of Stuttgart on 1 April 1966,and was its director until 31 March 1992.With his research and development work in the field of analytical and digital photogrammetry,he significantly influenced the developments and progress in these two fields and helped the Institute of Photogrammetry to achieve a worldwide reputation.For many younger photogrammetrists he was always a role model and stood for the close connection between basic research and application.With the software developments he initiated with his spin-off inpho GmbH,Stuttgart(today Trimble),he was able to drive very successful technology transfer from research to practice.
基金supported by the National Natural Science Foundation of China under Grant No.40730526Scientific Research Starting Foundation for Returned Overseas Chinese Scholars(Ministry of Education,China)+2 种基金 the Key Lab of Geographical Information Science under Grant No.KLGIS2011C01Shanghai Natural Science Foundation under Grant No.11ZR1410100Open Grant from Shanghai Key Lab for Urban Ecology and Sustainability(SHUES)
文摘This paper presents an innovative method to facilitate making such a plan. Using an algorithm to schedule the starting time of each evacuation group, the method guarantees that the time of completing a large-scale evacuation is very close to its theoretically shortest evacuation time. Meanwhile, unlike a simultaneous evacuation, during a staged evacuation planned with the proposed method, all evacuees can take the shortest path to a safe exit. Once evacuees start off, they will not suffer any traffic congestion. The above advantages of this innovative method are achieved by using an algorithm with three nested loops. Experiments have been conducted, and their results have validated the proposed method.
