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| 1 | 3D change detection at street leve! using mobile t aser scanning pointclouds and terrestrial images显示文摘 | Rongjun Qin Armin Gruen | 2014 | ISPRS Journal of Photogrammetry and Remote Sensing2014，，90： | 1 |
| 2 | Investigation of the effects of humic acid and H_(2)O_(2) on the photocatalytic degradation of atrazine assisted by microwave显示文摘A solution of atrazine in a TiO_(2)suspension,an endocrine disruptor in natural water,was tentatively treated by microwave-assisted photocatalytic technique.The effects of mannitol,oxygen,humic acid,and hydrogen dioxide on the photodegradation rate were explored.The results could be deduced as follows:the photocatalytic degradation of atrazine fits the pseudo-first-order kinetic well with k=0.0328 s–1,and·OH was identified as the dominant reactant.Photodegradation of atrazine was hindered in the presence of humic acid,and the retardation effect increased as the concentration of humic acid increased.H_(2)O_(2)displayed a significant negative influence on atrazine photocatalysis efficiency.Based on intermediates identified with gas chromatography-mass spectrometry(GC-MS)and Liquid chromatography-mass spectrometry(LC-MS/MS)techniques,the main degradation routes of atrazine are proposed. | Chao QIN Shaogui YANG Cheng SUN Manjun ZHAN Rongjun WANG Huanxing CAI Jia ZHOU | 2010 | Frontiers of Environmental Science & Engineering2010，4，3： | 1 |
| 3 | Increasing detail of 3D models through combined photogrammetric and procedural modelling显示文摘This study addresses the need of making reality-based 3D urban models more detailed.Our method combines the established workflows from photogrammetry and procedural modelling in order to exploit distinct advantages of both approaches.Our overall workflow uses photogrammetry for measuring geo-referenced satellite imagery to create 3D building models and textured roof geometry.The results are then used to create attributed building footprints,which can be applied in the procedural modelling part of the workflow.Thereby procedural building models and detailed façade structures,based on street-level photos,are created.The final step merges the textured roof geometry with the procedural façade geometry,resulting in an improved model compared with using each technique alone.The article details the individual workflow steps and exemplifies the approach by means of a concrete case study carried out in Singapore's Punggol area,where we modelled a newly developed part of Singapore,consisting mainly of 3D high-rise towers. | Stefan MÜLLER ARISONA Chen ZHONG Xianfeng HUANG Rongjun QIN | 2013 | Geo-Spatial Information Science2013，16，1： | 1 |
| 4 | The role of machine intelligence in photogrammetric 3D modeling-an overview and perspectives显示文摘The process of modern photogrammetry converts images and/or LiDAR data into usable 2D/3D/4D products.The photogrammetric industry offers engineering-grade hardware and software components for various applications.While some components of the data processing pipeline work already automatically,there is still substantial manual involvement required in order to obtain reliable and high-quality results.The recent development of machine learning techniques has attracted a great attention in its potential to address complex tasks that traditionally require manual inputs.It is therefore worth revisiting the role and existing efforts of machine learning techniques in the field of photogrammetry,as well as its neighboring field computer vision.This paper provides an overview of the state-of-the-art efforts in machine learning in bringing the automated and‘intelligent’component to photogrammetry,computer vision and(to a lesser degree)to remote sensing.We will primarily cover the relevant efforts following a typical 3D photogrammetric processing pipeline:(1)data acquisition(2)georeferencing/interest point matching(3)Digital Surface Model generation(4)semantic interpretations,followed by conclusions and our insights. | Rongjun Qin Armin Gruen | 2021 | International Journal of Digital Earth2021，14，1： | 1 |
| 5 | Multi-component system maintenance optimization of a rail transit train based on opportunistic correlations显示文摘ln order to deal with the problems of insufficient or excessive maintenance in the current maintenance activities of China transit trains,this paper develops a novel multi-component system maintenance optimization approach based on an opportunistic correlation model.Based on the minimal reliability and failure rate change rule of each train component,the novel proposed maintenance optimization benefits from an improved opportunistic maintenance model with system structure correlation,fault correlation and reliability correlation under imperfect maintenance.Then,different maintenance modes can be determined by a proposed mainte-nance factor under the different conditions of components.Specifically,the reliability threshold of each component is also considered to optimize the maintenance cost by the system reliability and operational availability of the train.Furthermore,as the mentioned problem belongs to the NP-Hard optimization problems,a modified particle swarm optimization(PSO)with the improvement of inertia weight is proposed to cope with the optimization problem.Based on a specific case under the practical recorded failure data,the analysis shows that the proposed model and approach can effectively cut the maintenance cost. | Jisheng Dai Rongjun Ding Yong Fu Yong Qin | 2023 | Transportation Safety and Environment2023，5，4： | 0 |
| 6 | A volumetric change detection framework using UAV oblique photogrammetry–a case study of ultra-high-resolution monitoring of progressive building collapse显示文摘In this paper,we present a case study that performs an unmanned aerial vehicle(UAV)based fine-scale 3D change detection and monitoring of progressive collapse performance of a building during a demolition event.Multi-temporal oblique photogrammetry images are collected with 3D point clouds generated at different stages of the demolition.The geometric accuracy of the generated point clouds has been evaluated against both airborne and terrestrial LiDAR point clouds,achieving an average distance of 12 cm and 16 cm for roof and façade respectively.We propose a hierarchical volumetric change detection framework that unifies multi-temporal UAV images for pose estimation(free of ground control points),reconstruction,and a coarse-to-fine 3D density change analysis.This work has provided a solution capable of addressing change detection on full 3D time-series datasets where dramatic scene content changes are presented progressively.Our change detection results on the building demolition event have been evaluated against the manually marked ground-truth changes and have achieved an F-1 score varying from 0.78 to 0.92,with consistently high precision(0.92–0.99).Volumetric changes through the demolition progress are derived from change detection and have been shown to favorably reflect the qualitative and quantitative building demolition progression. | Ningli Xu Debao Huang Shuang Song Xiao Ling Chris Strasbaugh Alper Yilmaz Halil Sezen Rongjun Qin | 2021 | International Journal of Digital Earth2021，14，11： | 0 |
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