激光雷达处理管道(LPP)的协同开发

IF 1.8 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Geoscientific Instrumentation Methods and Data Systems Pub Date : 2022-12-19 DOI:10.5194/gi-2022-19
Juan V. Pallotta, Silvania Carvalho, Fabio J. S. Lopes, Alexandre Cacheffo, Eduardo Landulfo, Henrique M. J. Barbosa
{"title":"激光雷达处理管道(LPP)的协同开发","authors":"Juan V. Pallotta, Silvania Carvalho, Fabio J. S. Lopes, Alexandre Cacheffo, Eduardo Landulfo, Henrique M. J. Barbosa","doi":"10.5194/gi-2022-19","DOIUrl":null,"url":null,"abstract":"<strong>Abstract.</strong> Lidars can simultaneously measure clouds and aerosols with high temporal and spatial resolution and hence help understand their interactions, which are the source of the largest uncertainties in current climate projections. However, lidars are typically custom-built, so there are significant differences between them. In this sense, lidar networks play a crucial role as they coordinate the efforts of different groups, providing the guidelines for quality-assured routine measurements aiming to homogenize the physical retrievals. With that in mind, this work describes an ongoing effort to develop a lidar processing pipeline (LPP) collaboratively. The LPP is a collection of tools developed in C/C++, python, and Linux script that handle all the steps of a typical lidar analysis. The first publicly released version of LPP produces data files at levels 0 (raw and metadata), 1 (averaging and layer-mask), and 2 (aerosol optical properties). We discussed the application of LPP for two case studies for Sao Paulo and Amazon, which shows the capabilities of the current release but also highlights the need for new features. From this exercise, we developed and presented a roadmap to guide future development, accommodating the needs of our community.","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Collaborative development of the Lidar Processing Pipeline (LPP)\",\"authors\":\"Juan V. Pallotta, Silvania Carvalho, Fabio J. S. Lopes, Alexandre Cacheffo, Eduardo Landulfo, Henrique M. J. Barbosa\",\"doi\":\"10.5194/gi-2022-19\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Abstract.</strong> Lidars can simultaneously measure clouds and aerosols with high temporal and spatial resolution and hence help understand their interactions, which are the source of the largest uncertainties in current climate projections. However, lidars are typically custom-built, so there are significant differences between them. In this sense, lidar networks play a crucial role as they coordinate the efforts of different groups, providing the guidelines for quality-assured routine measurements aiming to homogenize the physical retrievals. With that in mind, this work describes an ongoing effort to develop a lidar processing pipeline (LPP) collaboratively. The LPP is a collection of tools developed in C/C++, python, and Linux script that handle all the steps of a typical lidar analysis. The first publicly released version of LPP produces data files at levels 0 (raw and metadata), 1 (averaging and layer-mask), and 2 (aerosol optical properties). We discussed the application of LPP for two case studies for Sao Paulo and Amazon, which shows the capabilities of the current release but also highlights the need for new features. From this exercise, we developed and presented a roadmap to guide future development, accommodating the needs of our community.\",\"PeriodicalId\":48742,\"journal\":{\"name\":\"Geoscientific Instrumentation Methods and Data Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2022-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geoscientific Instrumentation Methods and Data Systems\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.5194/gi-2022-19\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoscientific Instrumentation Methods and Data Systems","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/gi-2022-19","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

摘要。激光雷达可以同时以高时间和空间分辨率测量云和气溶胶,因此有助于了解它们之间的相互作用,这是当前气候预测中最大的不确定性来源。然而,激光雷达通常是定制的,因此它们之间存在显着差异。从这个意义上说,激光雷达网络发挥着至关重要的作用,因为它们协调不同小组的努力,为旨在均匀化物理检索的质量保证常规测量提供指导。考虑到这一点,这项工作描述了协同开发激光雷达处理管道(LPP)的持续努力。LPP是一个用C/ c++、python和Linux脚本开发的工具集合,用于处理典型激光雷达分析的所有步骤。第一个公开发布的LPP版本产生的数据文件级别为0(原始和元数据)、1(平均和层掩膜)和2(气溶胶光学特性)。我们在Sao Paulo和Amazon的两个案例研究中讨论了LPP的应用,它们展示了当前版本的功能,但也强调了对新特性的需求。透过这项工作,我们制定并提出了指引未来发展的路线图,以配合社会的需要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Collaborative development of the Lidar Processing Pipeline (LPP)
Abstract. Lidars can simultaneously measure clouds and aerosols with high temporal and spatial resolution and hence help understand their interactions, which are the source of the largest uncertainties in current climate projections. However, lidars are typically custom-built, so there are significant differences between them. In this sense, lidar networks play a crucial role as they coordinate the efforts of different groups, providing the guidelines for quality-assured routine measurements aiming to homogenize the physical retrievals. With that in mind, this work describes an ongoing effort to develop a lidar processing pipeline (LPP) collaboratively. The LPP is a collection of tools developed in C/C++, python, and Linux script that handle all the steps of a typical lidar analysis. The first publicly released version of LPP produces data files at levels 0 (raw and metadata), 1 (averaging and layer-mask), and 2 (aerosol optical properties). We discussed the application of LPP for two case studies for Sao Paulo and Amazon, which shows the capabilities of the current release but also highlights the need for new features. From this exercise, we developed and presented a roadmap to guide future development, accommodating the needs of our community.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Geoscientific Instrumentation Methods and Data Systems
Geoscientific Instrumentation Methods and Data Systems GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
3.70
自引率
0.00%
发文量
23
审稿时长
37 weeks
期刊介绍: Geoscientific Instrumentation, Methods and Data Systems (GI) is an open-access interdisciplinary electronic journal for swift publication of original articles and short communications in the area of geoscientific instruments. It covers three main areas: (i) atmospheric and geospace sciences, (ii) earth science, and (iii) ocean science. A unique feature of the journal is the emphasis on synergy between science and technology that facilitates advances in GI. These advances include but are not limited to the following: concepts, design, and description of instrumentation and data systems; retrieval techniques of scientific products from measurements; calibration and data quality assessment; uncertainty in measurements; newly developed and planned research platforms and community instrumentation capabilities; major national and international field campaigns and observational research programs; new observational strategies to address societal needs in areas such as monitoring climate change and preventing natural disasters; networking of instruments for enhancing high temporal and spatial resolution of observations. GI has an innovative two-stage publication process involving the scientific discussion forum Geoscientific Instrumentation, Methods and Data Systems Discussions (GID), which has been designed to do the following: foster scientific discussion; maximize the effectiveness and transparency of scientific quality assurance; enable rapid publication; make scientific publications freely accessible.
期刊最新文献
Comparing triple and single Doppler lidar wind measurements with sonic anemometer data based on a new filter strategy for virtual tower measurements Managing Data of Sensor-Equipped Transportation Networks using Graph Databases Airborne electromagnetic data levelling based on the structured variational method A multiplexing system for quantifying oxygen fractionation factors in closed chambers Development of an integrated analytical platform of clay minerals separation, characterization and 40K/40Ar dating
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1