武测译文 Pub Date : 2023-03-02 DOI: 10.1080/10095020.2022.2155255

Haerani Haerani, A. Apan, Thong Nguyen-Huy, B. Basnet

引用次数: 3

Geometric positioning integrating optical satellite stereo imagery and a global database of ICESat-2 laser control points: A framework and key technologies 基于光学卫星立体影像与ICESat-2激光控制点全球数据库的几何定位:框架与关键技术

武测译文 Pub Date : 2023-03-02 DOI: 10.1080/10095020.2022.2159885

Mi Wang, Yu Wei, Y. Pi

{"title":"Geometric positioning integrating optical satellite stereo imagery and a global database of ICESat-2 laser control points: A framework and key technologies","authors":"Mi Wang, Yu Wei, Y. Pi","doi":"10.1080/10095020.2022.2159885","DOIUrl":"https://doi.org/10.1080/10095020.2022.2159885","url":null,"abstract":"ABSTRACT Block Adjustment (BA) is one of the essential techniques for producing high-precision geospatial 3D data products with optical stereo satellite imagery. For block adjustment with few ground-control points or without ground control, the vertical error of the model is the decisive factor that constrains the accuracy of 3D data products. The elevation data obtained by spaceborne laser altimeter have the advantages of short update periods, high positioning precision, and low acquisition cost, providing sufficient data support for improving the elevation accuracy of stereo models through the combined BA. This paper proposes a geometric positioning model based on the integration of Optical Satellite Stereo Imagery (OSSI) and spaceborne laser altimeter data. Firstly, we elaborate the principle and necessity of this work through a literature review of existing methods. Then, the framework of our geo-positioning models. Secondly, four key technologies of the proposed model are expounded in order, including the acquisition and management of global Laser Control Points, the association of LCPs and OSSI, the block adjustment model combining LCPs with OSSI, and the accuracy estimation and quality control of the combined BA. Next, the combined BA experiment using Ziyuan-3 (ZY-3) OSSI and ICESat-2 laser data was carried out at the testing site in Shandong Province, China. Experimental results prove that our method can automatically select LCPs with high accuracy. The elevation deviation of the combined BA eventually achieved the Mean Error (ME) of 0.06 m and the Root Mean Square Error (RMSE) of 1.18 m, much lower than the ME of 13.20 m and the RMSE of 3.88 m before the block adjustment. A further research direction will be how to perform more adequate accuracy analysis and quality control using massive laser points as checkpoints.","PeriodicalId":58518,"journal":{"name":"武测译文","volume":"26 1","pages":"206 - 217"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49192785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Determining the new height of Mount Qomolangma based on the International Height Reference System 基于国际高度参考系统确定珠穆朗玛峰新高度

武测译文 Pub Date : 2023-02-23 DOI: 10.1080/10095020.2022.2128901

Y. Dang, T. Jiang, Chunxi Guo, Bin Chen, Chuanyin Zhang, Qiang Yang, Zhengtao Wang

引用次数: 0

LuoJiaAI: A cloud-based artificial intelligence platform for remote sensing image interpretation 罗家爱:基于云的遥感图像解译人工智能平台

武测译文 Pub Date : 2023-02-23 DOI: 10.1080/10095020.2022.2162980

Zhang Zhang, Mi Zhang, J. Gong, Xiangyun Hu, Hanjiang Xiong, H. Zhou, Zhipeng Cao

{"title":"LuoJiaAI: A cloud-based artificial intelligence platform for remote sensing image interpretation","authors":"Zhang Zhang, Mi Zhang, J. Gong, Xiangyun Hu, Hanjiang Xiong, H. Zhou, Zhipeng Cao","doi":"10.1080/10095020.2022.2162980","DOIUrl":"https://doi.org/10.1080/10095020.2022.2162980","url":null,"abstract":"ABSTRACT The rapid processing, analysis, and mining of remote-sensing big data based on intelligent interpretation technology using remote-sensing cloud computing platforms (RS-CCPs) have recently become a new trend. The existing RS-CCPs mainly focus on developing and optimizing high-performance data storage and intelligent computing for common visual representation, which ignores remote sensing data characteristics such as large image size, large-scale change, multiple data channels, and geographic knowledge embedding, thus impairing computational efficiency and accuracy. We construct a LuoJiaAI platform composed of a standard large-scale sample database (LuoJiaSET) and a dedicated deep learning framework (LuoJiaNET) to achieve state-of-the-art performance on five typical remote sensing interpretation tasks, including scene classification, object detection, land-use classification, change detection, and multi-view 3D reconstruction. The details of the LuoJiaAI application experiment can be found at the white paper for LuoJiaAI industrial application. In addition, LuoJiaAI is an open-source RS-CCP that supports the latest Open Geospatial Consortium (OGC) standards for better developing and sharing Earth Artificial Intelligence (AI) algorithms and products on benchmark datasets. LuoJiaAI narrows the gap between the sample database and deep learning frameworks through a user-friendly data-framework collaboration mechanism, showing great potential in high-precision remote sensing mapping applications.","PeriodicalId":58518,"journal":{"name":"武测译文","volume":"26 1","pages":"218 - 241"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46735646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Evaluating COVID-19’s impacts on Puerto Rican’s travel behaviors 评估COVID-19对波多黎各旅行行为的影响

武测译文 Pub Date : 2023-02-21 DOI: 10.1080/10095020.2022.2161426

Lauren Carter, Ran Tao

引用次数: 2

Lockdown lifted: measuring spatial resilience from London’s public transport demand recovery 解除封锁：从伦敦公共交通需求复苏中衡量空间弹性

武测译文 Pub Date : 2023-02-21 DOI: 10.1080/10095020.2022.2156300

Chen Zhong, Divya Sharma, H. Wong

{"title":"Lockdown lifted: measuring spatial resilience from London’s public transport demand recovery","authors":"Chen Zhong, Divya Sharma, H. Wong","doi":"10.1080/10095020.2022.2156300","DOIUrl":"https://doi.org/10.1080/10095020.2022.2156300","url":null,"abstract":"The disruptive effects of the COVID-19 pandemic has rapidly shifted how individuals navigate in cities. Governments are concerned that travel behavior will shift toward a car-driven and homeworking future, shifting demand away from public transport use. These concerns place the recovery of public transport in a possible crisis. A resilience perspective may aid the discussion around recovery – particularly one that deviates from pre-pandemic behavior. This paper presents an empirical study of London’s public transport demand and introduces a perspective of spatial resilience to the existing body of research on post-pandemic public transport demand. This study defines spatial resilience as the rate of recovery in public transport demand within census boundaries over a period after lockdown restrictions were lifted. The relationship between spatial resilience and urban socioeconomic factors was investigated by a global spatial regression model and a localized perspective through Geographically Weighted Regression (GWR) model. In this case study of London, the analysis focuses on the period after the first COVID-19 lockdown restrictions were lifted (June 2020) and before the new restrictions in mid-September 2020. The analysis shows that outer London generally recovered faster than inner London. Factors of income, car ownership and density of public transport infrastructure were found to have the greatest influence on spatial patterns in resilience. Furthermore, influential relationships vary locally, inviting future research to examine the drivers of this spatial heterogeneity. Thus, this research recommends transport policy-makers capture the influences of homeworking, ensure funding for a minimum level of service, and advocate for a polycentric recovery post-pandemic.","PeriodicalId":58518,"journal":{"name":"武测译文","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43212252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Estimating China’s poverty reduction efficiency by integrating multi-source geospatial data and deep learning techniques 基于多源地理空间数据和深度学习技术的中国减贫效率估算

武测译文 Pub Date : 2023-02-15 DOI: 10.1080/10095020.2023.2165975

Yao Yao, J. Zhou, Zhenhui Sun, Qingfeng Guan, Zhiqiang Guo, Yin Xu, Jinbao Zhang, Ye Hong, Yuyang Cai, Ruoyu Wang

引用次数: 1

Untangling the association between urban mobility and urban elements 解开城市交通与城市要素之间的联系

武测译文 Pub Date : 2023-02-15 DOI: 10.1080/10095020.2022.2157761

Jinzhou Cao, Wei Tu, Rui Cao, Qili Gao, Guanzhou Chen, Qingquan Li

引用次数: 0

Epidemiological-survey-based multidimensional modeling for understanding daily mobility during the COVID-19 pandemic across urban-rural gradient in the Chinese mainland 基于流行病学调查的多维模型，用于理解新冠肺炎大流行期间中国大陆城乡梯度的日常流动性

武测译文 Pub Date : 2023-01-24 DOI: 10.1080/10095020.2022.2156821

Feng Zhao, Z. Dai, Wenyu Zhang, Yiting Shan, Cheng Fu

引用次数: 1

Fully automatic DOM generation method based on optical flow field dense image matching 基于光流场密集图像匹配的全自动DOM生成方法

武测译文 Pub Date : 2023-01-24 DOI: 10.1080/10095020.2022.2159886

W. Yuan, Xiuxiao Yuan, Yang Cai, R. Shibasaki

{"title":"Fully automatic DOM generation method based on optical flow field dense image matching","authors":"W. Yuan, Xiuxiao Yuan, Yang Cai, R. Shibasaki","doi":"10.1080/10095020.2022.2159886","DOIUrl":"https://doi.org/10.1080/10095020.2022.2159886","url":null,"abstract":"ABSTRACT Automatic Digital Orthophoto Map (DOM) generation plays an important role in many downstream works such as land use and cover detection, urban planning, and disaster assessment. Existing DOM generation methods can generate promising results but always need ground object filtered DEM generation before otho-rectification; this can consume much time and produce building facade contained results. To address this problem, a pixel-by-pixel digital differential rectification-based automatic DOM generation method is proposed in this paper. Firstly, 3D point clouds with texture are generated by dense image matching based on an optical flow field for a stereo pair of images, respectively. Then, the grayscale of the digital differential rectification image is extracted directly from the point clouds element by element according to the nearest neighbor method for matched points. Subsequently, the elevation is repaired grid-by-grid using the multi-layer Locally Refined B-spline (LR-B) interpolation method with triangular mesh constraint for the point clouds void area, and the grayscale is obtained by the indirect scheme of digital differential rectification to generate the pixel-by-pixel digital differentially rectified image of a single image slice. Finally, a seamline network is automatically searched using a disparity map optimization algorithm, and DOM is smartly mosaicked. The qualitative and quantitative experimental results on three datasets were produced and evaluated, which confirmed the feasibility of the proposed method, and the DOM accuracy can reach 1 Ground Sample Distance (GSD) level. The comparison experiment with the state-of-the-art commercial softwares showed that the proposed method generated DOM has a better visual effect on building boundaries and roof completeness with comparable accuracy and computational efficiency.","PeriodicalId":58518,"journal":{"name":"武测译文","volume":"26 1","pages":"242 - 256"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43557456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

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