基于地面大气高光谱探测结果和人工神经网络模型的森林生态系统二氧化碳通量估算值

IF 0.9 Q4 OPTICS Atmospheric and Oceanic Optics Pub Date : 2024-07-03 DOI:10.1134/S1024856024700246
A. P. Rozanov, I. V. Zadvornykh, K. G. Gribanov, V. I. Zakharov
{"title":"基于地面大气高光谱探测结果和人工神经网络模型的森林生态系统二氧化碳通量估算值","authors":"A. P. Rozanov,&nbsp;I. V. Zadvornykh,&nbsp;K. G. Gribanov,&nbsp;V. I. Zakharov","doi":"10.1134/S1024856024700246","DOIUrl":null,"url":null,"abstract":"<p>The results of hyperspectral sounding of the atmosphere at the Ural Atmospheric Station in Kourovka from 2012–2022 are presented. It is shown that the average rate of carbon dioxide growth in the atmosphere of this region is about 2.5 ppm per year. The amount of carbon dioxide absorbed from the atmosphere by the forest ecosystem per unit area during the growing season (April–September) in the vicinity of the carbon site in Kourovka is estimated using two independent methods. One method is based on the data on the CO<sub>2</sub> total column obtained from sounding the atmosphere with a ground-based high-resolution infrared Fourier spectrometer. The second method is based on the use of an artificial neural network with data from spectral channels of the MODIS satellite sensor as input. The results obtained by both methods have good agreement: the amount of CO<sub>2</sub> absorbed from the atmosphere by the forest ecosystem in the vicinity of the carbon site during the growing season of 2022 is ~1.5 t/ha according to the first method and ~1.3 t/ha according to the second method.</p>","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimates of Carbon Dioxide Flux into the Forest Ecosystem Based on Results of Ground-Based Hyperspectral Sounding of the Atmosphere and an Artificial Neural Network Model\",\"authors\":\"A. P. Rozanov,&nbsp;I. V. Zadvornykh,&nbsp;K. G. Gribanov,&nbsp;V. I. Zakharov\",\"doi\":\"10.1134/S1024856024700246\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The results of hyperspectral sounding of the atmosphere at the Ural Atmospheric Station in Kourovka from 2012–2022 are presented. It is shown that the average rate of carbon dioxide growth in the atmosphere of this region is about 2.5 ppm per year. The amount of carbon dioxide absorbed from the atmosphere by the forest ecosystem per unit area during the growing season (April–September) in the vicinity of the carbon site in Kourovka is estimated using two independent methods. One method is based on the data on the CO<sub>2</sub> total column obtained from sounding the atmosphere with a ground-based high-resolution infrared Fourier spectrometer. The second method is based on the use of an artificial neural network with data from spectral channels of the MODIS satellite sensor as input. The results obtained by both methods have good agreement: the amount of CO<sub>2</sub> absorbed from the atmosphere by the forest ecosystem in the vicinity of the carbon site during the growing season of 2022 is ~1.5 t/ha according to the first method and ~1.3 t/ha according to the second method.</p>\",\"PeriodicalId\":46751,\"journal\":{\"name\":\"Atmospheric and Oceanic Optics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2024-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric and Oceanic Optics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1134/S1024856024700246\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"OPTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric and Oceanic Optics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1134/S1024856024700246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPTICS","Score":null,"Total":0}
引用次数: 0

摘要

摘要 介绍了库洛夫卡乌拉尔大气站 2012-2022 年大气高光谱探测结果。结果表明,该地区大气中二氧化碳的平均增长速度约为每年 2.5 ppm。库洛夫卡碳站点附近的森林生态系统在生长季节(4 月至 9 月)单位面积从大气中吸收的二氧化碳量是用两种独立方法估算的。一种方法是基于使用地面高分辨率红外傅里叶光谱仪探测大气层获得的二氧化碳总柱数据。第二种方法基于使用 MODIS 卫星传感器光谱通道数据作为输入的人工神经网络。两种方法得出的结果具有很好的一致性:在 2022 年的生长季节,碳站点附近森林生态系统从大气中吸收的二氧化碳量,第一种方法为 ~1.5 吨/公顷,第二种方法为 ~1.3 吨/公顷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

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
Estimates of Carbon Dioxide Flux into the Forest Ecosystem Based on Results of Ground-Based Hyperspectral Sounding of the Atmosphere and an Artificial Neural Network Model

The results of hyperspectral sounding of the atmosphere at the Ural Atmospheric Station in Kourovka from 2012–2022 are presented. It is shown that the average rate of carbon dioxide growth in the atmosphere of this region is about 2.5 ppm per year. The amount of carbon dioxide absorbed from the atmosphere by the forest ecosystem per unit area during the growing season (April–September) in the vicinity of the carbon site in Kourovka is estimated using two independent methods. One method is based on the data on the CO2 total column obtained from sounding the atmosphere with a ground-based high-resolution infrared Fourier spectrometer. The second method is based on the use of an artificial neural network with data from spectral channels of the MODIS satellite sensor as input. The results obtained by both methods have good agreement: the amount of CO2 absorbed from the atmosphere by the forest ecosystem in the vicinity of the carbon site during the growing season of 2022 is ~1.5 t/ha according to the first method and ~1.3 t/ha according to the second method.

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
CiteScore
2.40
自引率
42.90%
发文量
84
期刊介绍: Atmospheric and Oceanic Optics  is an international peer reviewed journal that presents experimental and theoretical articles relevant to a wide range of problems of atmospheric and oceanic optics, ecology, and climate. The journal coverage includes: scattering and transfer of optical waves, spectroscopy of atmospheric gases, turbulent and nonlinear optical phenomena, adaptive optics, remote (ground-based, airborne, and spaceborne) sensing of the atmosphere and the surface, methods for solving of inverse problems, new equipment for optical investigations, development of computer programs and databases for optical studies. Thematic issues are devoted to the studies of atmospheric ozone, adaptive, nonlinear, and coherent optics, regional climate and environmental monitoring, and other subjects.
期刊最新文献
The Superresonance: The Discovery That Was Not Done More Than One Hundred Years Ago Spatial Distribution of Potential Sources of Carbonaceous Aerosols in Central Siberia The Effect of Electronic Halos on the Scattering Properties of Solid Particles in the Microwave Range Aerosol Sounding of the Troposphere and Stratosphere by Lidar and Aerological Technologies Optical and Geometrical Characteristics of High-Level Clouds from the 2009–2023 Data on Laser Polarization Sensing in Tomsk
×
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