Estimating Ground‐Level PM        <sub >2.5</sub>2.5        by Fusing Satellite and Station Observations: A Geo‐Intelligent Deep Learning Approach

Li Tongwen; Shen Huanfeng; Yuan Qiangqiang; Zhang Xuechen; Zhang Liangpei

摘要

Abstract > Fusing satellite observations and station measurements to estimate ground‐level PM <sub>2.5</sub> is promising for monitoring PM <sub>2.5</sub> pollution. A geo‐intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM <sub>2.5</sub> . Specifically, it considers geographical distance and spatiotemporally correlated PM <sub>2.5</sub> in a deep belief network (denoted as Geoi‐DBN). Geoi‐DBN can capture the essential features associated with PM <sub>2.5</sub> from latent factors. It was trained and tested with data from China in 2015. The results show that Geoi‐DBN performs significantly better than the traditional neural network. The out‐of‐sample cross‐validation <fi>R</fi> 2 increases from 0.42 to 0.88, and RMSE decreases from 29.96 to 13.03? type="mathematics"> μg/m 3 . On the basis of the derived PM <sub>2.5</sub> distribution, it is predicted that over 80% of the Chinese population live in areas with an annual mean PM <sub>2.5</sub> of greater than 35? type="mathematics"> μg/m 3 . This study provides a new perspective for air pollution monitoring in large geographic regions. </abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> <div class="translation abstracttxt"> <span class="zhankaihshouqi fivelineshidden" id="abstract"> <span>机译：</span><抽象类型= “主要” 的xml：郎= “EN”> <标题类型= “主”>抽象</ TITLE> <P>熔断卫星观测和站的测量来估计地平面PM <子> 2.5 </子>是有希望用于监测PM <子> 2.5 </子>污染。地理智能的方法，其包含的地域相关成智能深学习结构，被显影来估计PM <子> 2.5 </子>。具体而言，它认为地理距离和时空相关PM <子> 2.5 </子>在一个很深的信念网络（表示为的GeOI-DBN）。的GeOI-DBN可以捕捉与PM <子> 2.5 </子>从潜因素相关联的必要的特征。它进行训练，并且在2015年来自中国的数据测试结果表明的GeOI-DBN执行显著优于传统的神经网络。该外的样品交叉验证<音响> - [R </ FI> <SUP> 2 </ SUP>从0.42至0.88的增加，并且RMSE从29.96降低至13.03？ <跨越式= “数学”>微克/米<SUP> 3 </ SUP> </跨度>。在衍生PM <sub>的基础上2.5 </ sub>分布，据预测，超过80％的中国人口居住的地区，年平均PM <sub> 2.5 </ sub>的大于35的？ <跨越式= “数学”>微克/米<SUP> 3 </ SUP> </跨度>。这项研究提供了空气污染的大地理区域监视一个新的视角。 </ p> </ abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> </div> <div class="record"> <h2 class="all_title" id="enpatent33" >著录项</h2> <ul> <li> <span class="lefttit">来源</span> <div style="width: 86%;vertical-align: text-top;display: inline-block;"> <a href='/journal-foreign-23539/'>《Geophysical Research Letters》</a> <b style="margin: 0 2px;">|</b><span>2017年第23期</span><b style="margin: 0 2px;">|</b><span>共9页</span> </div> </li> <li> <div class="author"> <span class="lefttit">作者</span> <p id="fAuthorthree" class="threelineshidden zhankaihshouqi"> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Li Tongwen&option=202" target="_blank" rel="nofollow">Li Tongwen;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Shen Huanfeng&option=202" target="_blank" rel="nofollow">Shen Huanfeng;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Yuan Qiangqiang&option=202" target="_blank" rel="nofollow">Yuan Qiangqiang;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Zhang Xuechen&option=202" target="_blank" rel="nofollow">Zhang Xuechen;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Zhang Liangpei&option=202" target="_blank" rel="nofollow">Zhang Liangpei;</a> </p> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zkzz" style="display: none;">展开▼</span> </div> </li> <li> <div style="display: flex;"> <span class="lefttit">作者单位</span> <div style="position: relative;margin-left: 3px;max-width: 639px;"> <div class="threelineshidden zhankaihshouqi" id="fOrgthree"> <p>School of Resource and Environmental SciencesWuhan UniversityWuhan China;</p> <p>School of Resource and Environmental SciencesWuhan UniversityWuhan China;</p> <p>The Collaborative Innovation Center for Geospatial TechnologyWuhan China;</p> <p>School of Resource and Environmental SciencesWuhan UniversityWuhan China;</p> <p>The Collaborative Innovation Center for Geospatial TechnologyWuhan China;</p> </div> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zhdw" style="display: none;">展开▼</span> </div> </div> </li> <li > <span class="lefttit">收录信息</span> <span style="width: 86%;vertical-align: text-top;display: inline-block;"></span> </li> <li> <span class="lefttit">原文格式</span> <span>PDF</span> </li> <li> <span class="lefttit">正文语种</span> <span>eng</span> </li> <li> <span class="lefttit">中图分类</span> <span><a href="https://www.zhangqiaokeyan.com/clc/163.html" title="地球物理学">地球物理学;</a></span> </li> <li class="antistop"> <span class="lefttit">关键词</span> <p style="width: 86%;vertical-align: text-top;"> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=PM 2.5&option=203" rel="nofollow">PM 2.5;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=deep learning&option=203" rel="nofollow">deep learning;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=geo‐intelligent&option=203" rel="nofollow">geo‐intelligent;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=satellite remote sensing&option=203" rel="nofollow">satellite remote sensing;</a> </p> <div class="translation"> 机译：PM 2.5;深入学习;地理智能;卫星遥感; </div> </li> </ul> </div> </div> <div class="literature cardcommon" id="literaturereference" style="display:none"> <div class="similarity "> <h3 class="all_title" id="enpatent111">引文网络</h3> <div class="referencetab clearfix"> <ul id="referencedaohang"> <li dataid="referenceul">参考文献</li> <li dataid="citationul">引证文献</li> <li dataid="commonreferenceul">共引文献</li> <li dataid="commoncitationul">同被引文献</li> <li dataid="tworeferenceul">二级参考文献</li> <li dataid="twocitationul">二级引证文献</li> </ul> </div> <div class="reference_details" id="referenceList"> <ul id="referenceul"></ul> <ul id="citationul"></ul> <ul id="commonreferenceul"></ul> <ul id="commoncitationul"></ul> <ul id="tworeferenceul"></ul> <ul id="twocitationul"></ul> </div> </div> </div> <div class="literature cardcommon"> <div 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href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=厉青&option=202" target="_blank" rel="nofollow" class="tuijian_auth tuijian_authcolor">,厉青</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=王中挺&option=202" target="_blank" rel="nofollow" class="tuijian_auth tuijian_authcolor">,王中挺</a> <span> <a href="/conference-cn-40113/" target="_blank" rel="nofollow" class="tuijian_authcolor"> . 第十八届中国环境遥感应用技术论坛 </a> <span> <span> . 2015</span> </span> </div> </li> <li> <div> <b>7. </b><a class="enjiyixqcontent" href="/academic-degree-domestic_mphd_thesis/020311548753.html">卫星气溶胶产品评估与融合改进及其在区域PM2.5浓度估算中的应用</a> <b>[A] </b> <span> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=张婕&option=202" target="_blank" rel="nofollow" class="tuijian_auth tuijian_authcolor"> . 张婕</a> <span> . 2018</span> </span> </div> </li> </ul> <ul style="display: none;"> <li> <div> <b>1. </b><a class="enjiyixqcontent" href="/patent-detail/06120113423936.html">一种静止气象卫星观测中获取近地面PM2.5浓度的方法及系统</a> <b>[P]</b> . <span> 中国专利： CN113468799A </span> <span> . 2021-10-01</span> </div> </li> <li> <div> <b>2. </b><a class="enjiyixqcontent" href="/patent-detail/06120112760197.html">一种基于卫星遥感的PM2.5与PM10估算方法</a> <b>[P]</b> . <span> 中国专利： CN112798482A </span> <span> . 2021-05-14</span> </div> </li> <li> <div> <b>3. </b><a class="enjiyixqcontent" href="/patent-detail/06130421411017.html">Satellite ground station in a virtual polar regions for Earth observation satellites of low-orbit based on geostationary satellites that be directed above the polar regions of the earth antenna</a> <b>[P]</b> . <span> 外国专利：  JP2012532547A </span> <span> . 2012-12-13</span> </div> <p class="zwjiyix translation" style="max-width: initial;height: auto;word-break: break-all;white-space: initial;text-overflow: initial;overflow: initial;"> <span>机译：虚拟极地地区的卫星地面站，用于低地球观测卫星，该对地观测卫星基于对地静止卫星，指向地球天线的极区上方 </span> </p> </li> <li> <div> <b>4. </b><a class="enjiyixqcontent" href="/patent-detail/06130406893769.html">Virtual polar satellite ground station for low orbit earth observation satellites based on a geostationary satellite pointing an antenna over an earth pole</a> <b>[P]</b> . <span> 外国专利：  US9929796B2 </span> <span> . 2018-03-27</span> </div> <p class="zwjiyix translation" style="max-width: initial;height: auto;word-break: break-all;white-space: initial;text-overflow: initial;overflow: initial;"> <span>机译：用于低轨道地球观测卫星的虚拟极地卫星地面站，其基于对地静止卫星，其天线指向地极 </span> </p> </li> <li> <div> <b>5. </b><a class="enjiyixqcontent" href="/patent-detail/06130413774963.html">Virtual polar satellite ground station for low orbit earth observation satellites based on a geostationary satellite pointing an antenna over an earth pole</a> <b>[P]</b> . <span> 外国专利：  EP2273692B1 </span> <span> . 2016-08-31</span> </div> <p class="zwjiyix translation" style="max-width: initial;height: auto;word-break: break-all;white-space: initial;text-overflow: 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Estimating Ground‐Level PM 2.52.5 by Fusing Satellite and Station Observations: A Geo‐Intelligent Deep Learning Approach

摘要

Estimating Ground‐Level PM _2.52.5 by Fusing Satellite and Station Observations: A Geo‐Intelligent Deep Learning Approach