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		<title>团队邀请电子科技大学于瀚雯教授开展学术交流</title>
		<link>https://goimage.cn/20250619-2/</link>
		
		<dc:creator><![CDATA[SARLAB]]></dc:creator>
		<pubDate>Thu, 19 Jun 2025 11:59:30 +0000</pubDate>
				<category><![CDATA[News]]></category>
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					<description><![CDATA[团队邀请电子科技大学于瀚雯教授开展学术交流 2025年6月17日下午，应Go-IMAGE团队邀请，电子科技大学 &#8230;<p class="read-more"> <a class="" href="https://goimage.cn/20250619-2/"> <span class="screen-reader-text">团队邀请电子科技大学于瀚雯教授开展学术交流</span> 查看全文 &#187;</a></p>]]></description>
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							<p style="text-indent: 2em;">2025年6月17日下午，应Go-IMAGE团队邀请，电子科技大学资源与环境学院于瀚雯教授在X4520会议室为师生带来题为“解缠绕结果可信度定量评估方法”的专题学术讲座。讲座由西南交通大学地学学院主办，学院相关教师及本硕博学生共计三十余人参加，现场交流热烈。</p>						</div>
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							<p style="text-indent: 2em;">在报告中，于教授围绕相位解缠在InSAR干涉测量技术中的核心地位展开，深入分析了解缠结果可信度评估所面临的技术瓶颈，指出当前高精度测量产品在缺乏外部数据辅助情况下，存在结果难以自洽评估的问题。他系统介绍了在无外部数据辅助条件下，基于单基线（病态）与多基线（非病态）两种情况进行精度定量评估所需满足的充分必要条件，提出了理论创新与工程应用并重的解决路径。</p>						</div>
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							<p style="text-indent: 2em;">报告结束后，于瀚雯教授与在场师生进行了深入的交流互动，就相关技术细节、实际应用场景和研究前沿问题给予了详尽解答。Go-IMAGE团队成员积极提问，现场氛围热烈，思想碰撞频繁。此次讲座不仅加深了师生对InSAR相位解缠精度控制与可信度评估的理解，也为在场师生进一步深入研究SAR干涉测量技术提供了有益参考。</p>						</div>
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							<p style="text-indent: 2em;"><strong>报告人简介</strong>：于瀚雯，IEEE Fellow，电子科技大学资源与环境学院教授，入选国家级人才计划。意大利那不勒斯大学、西安电子科技大学兼职教授。其提出的TSPA-InSAR技术荣获IEEE GRSS 的Transactions Prize Paper Award （2021年，全球每年仅1名）、华为火花奖（2023年），受华为人才基金连续资助。现担任IEEE地球科学与遥感学会执行委员会委员（IEEE GRSS Administrative Committee），国际学术期刊IEEE Journal on Miniaturization for Air and Space Systems首位华人主编，IEEE Geoscience and Remote Sensing Magazine（中科院一区TOP期刊、IF16.2）副主编、IEEE Transactions on Geoscience and Remote Sensing（中科院一区TOP期刊、IF7.5）副主编。</p>						</div>
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							<p>撰稿: 罗研</p><p>审核: 王晓文，罗子豪</p>						</div>
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		<title>Go-IMAGE团队2022级3名硕士生顺通过学位论文答辩</title>
		<link>https://goimage.cn/20250524-2/</link>
		
		<dc:creator><![CDATA[SARLAB]]></dc:creator>
		<pubDate>Sat, 24 May 2025 03:59:33 +0000</pubDate>
				<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://goimage.cn/?p=3355</guid>

					<description><![CDATA[Go-IMAGE团队2022级3名硕士生顺利通过学位论文答辩 2025年5月20日，Go-IMAGE团队202 &#8230;<p class="read-more"> <a class="" href="https://goimage.cn/20250524-2/"> <span class="screen-reader-text">Go-IMAGE团队2022级3名硕士生顺通过学位论文答辩</span> 查看全文 &#187;</a></p>]]></description>
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							<p><strong>Go-IMAGE团队2022级3名硕士生顺利通过学位论文答辩</strong></p>						</div>
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							<p style="text-indent: 2em;: 2;">2025年5月20日，Go-IMAGE团队2022级硕士研究生杜启航、黄涛、郭鑫三位同学顺利通过学位论文答辩，圆满完成学业。在答辩现场，他们凭借扎实的专业功底、严谨的学术态度以及出色的表达能力，全面展示了硕士阶段的研究成果，赢得了答辩委员会的一致好评。这不仅是对他们三年潜心科研、锐意进取的充分肯定，更彰显了Go-IMAGE团队在培养高水平创新人才方面的卓越成果。</p><p style="text-indent: 2em;">在团队的培养过程中，三位同学始终秉承严谨的学习态度，展现出扎实的专业能力和创新思维。毕业后，杜启航和黄涛两位同学将分别加入中国市政工程华北设计研究总院（天津）和基恩士（中国）有限公司工作，郭鑫同学将赴奥地利格拉茨技术大学(Graz University of Technology)攻读博士学位，师从冰冻圈领域国际著名学者Tobias Bolch教授。Go-IMAGE团队祝愿他们在新的工作岗位上继续发扬拼搏进取精神，勇攀事业高峰，以卓越的表现为社会创造更大的价值。</p>						</div>
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							<p>撰稿: 郭鑫</p><p>审核: 王晓文，罗子豪</p>						</div>
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		<title>团队发布全球石冰川编目数据库和平台</title>
		<link>https://goimage.cn/20250408-2/</link>
		
		<dc:creator><![CDATA[SARLAB]]></dc:creator>
		<pubDate>Tue, 08 Apr 2025 07:04:37 +0000</pubDate>
				<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://goimage.cn/?p=3311</guid>

					<description><![CDATA[团队发布全球石冰川编目数据库和平台(Global Rock Glacier Inventory Map) 日前 &#8230;<p class="read-more"> <a class="" href="https://goimage.cn/20250408-2/"> <span class="screen-reader-text">团队发布全球石冰川编目数据库和平台</span> 查看全文 &#187;</a></p>]]></description>
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							<p><strong><b>团队发布全球石冰川编目数据库和平台</b></strong><br /><strong><b>(Global Rock Glacier Inventory Map)</b></strong></p>						</div>
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">日前，由Go-IMAGE团队研发的全球石冰川编目数据平台(Global Rock Glacier Inventory Map)正式上线。石冰川作为高寒山区常见的一种冰缘地貌，长久以来人们对其分布和认识十分匮乏。近年来，随着遥感观测技术的发展，诸多学者利用遥感影像解译并编目了全球多个高寒地区的石冰川分布。然而，当前还没有一个综合的全球石冰川编目数据库，这也限制了研究人员更为系统地从全球尺度分析石冰川的分布和演化特征。</p>
<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">本团队通过搜集自上世纪90年代以来全球石冰川的研究文献，制作了覆盖高亚洲、欧洲、南美洲和北美洲大陆的141194条石冰川编目数据库，并研发了GIS可视化平台进行数据展示。该数据库记录了每条石冰川的详细地貌属性信息，包括分布位置、海拔、面积、年均气温等、数据来源等关键参数。另外，该平台支持三维地形可视化和多种底图切换。未来，团队将在该数据库的基础上持续更新，例如增加卫星InSAR提取的石冰川的表面流速信息，从而助力揭示石冰川在全球气候变暖背景下的演变规律。</p>						</div>
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							<p align="center">图1. 全球石冰川编目数据集网站</p>						</div>
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">作为一项开源项目，用户可访问网址：https://goimage.cn/rgplatform/ 浏览全球石冰川编目数据。该数据库和平台由课题组成员郭鑫、罗研、蔡佳欣、王强等研究生制作完成，同时在研制过程中香港中文大学刘琳教授，瑞士弗里堡大学胡燕博士、中科院青藏所曹斌研究员等提出了宝贵的意见。</p>						</div>
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							撰稿：郭鑫，罗研，王晓文
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审核：王晓文，罗子豪						</div>
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		<title>团队参与完成青藏高原石冰川编目成果在ESSD发表</title>
		<link>https://goimage.cn/20241226-2/</link>
		
		<dc:creator><![CDATA[SARLAB]]></dc:creator>
		<pubDate>Thu, 26 Dec 2024 13:30:12 +0000</pubDate>
				<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://goimage.cn/?p=3296</guid>

					<description><![CDATA[团队参与完成青藏高原石冰川编目成果在ESSD发表 石冰川(Rock Glaciers)是高寒山区常见的一种多年 &#8230;<p class="read-more"> <a class="" href="https://goimage.cn/20241226-2/"> <span class="screen-reader-text">团队参与完成青藏高原石冰川编目成果在ESSD发表</span> 查看全文 &#187;</a></p>]]></description>
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							<strong>团队参与完成青藏高原石冰川编目成果在ESSD发表
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">石冰川(Rock Glaciers)是高寒山区常见的一种多年冻土地貌，开展石冰川编制是监测其长期演化特征和了解气候变化下高山多年冻土退化规律的基础。诸多学者针对青藏高原石冰川已编制了多个数据集，但是这些编目均是针对局部山区开展，而且不同地区采用的编目方法各异。当前，面向整个青藏高原仍然缺乏一个系统、全面、编目规则一致的数据集，这进而限制了人们利用石冰川探究高山多年冻土的分布特征、水文效应、以及灾害风险。</p>						</div>
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">近日，香港中文大学LIU Lin (刘琳)教授课题组基于Planet Basemap光学影像，利用深度学习方法编制了首个青藏高原全域石冰川分布数据集TPRoGI [V1.0]，该数据集包含了44273个石冰川的分布位置和对应的地貌气候参数信息。通过分析石冰川编目结果显示：(1) 深度学习方法在探测石冰川和绘制其边界方面具有良好的能力，可以作为清查大区域石冰川分布的重要工具；(2)青藏高原石冰川集中分布在高原西北和东南部，特别是在西帕米尔和念青唐古拉地区分布较密，而高原内陆则分布稀少；(3)大多数石冰川发育海拔届于4,000至5,500米之间，坡度处于10°～25°，朝向主要为北向和西向；(4) 所有石冰川总面积约6000平方公里，平均面积约0.14 平方公里，其中高原西部的石冰川面积要大于其他地区。</p>						</div>
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							<p align="center">图1. 青藏高原石冰川分布图</p>						</div>
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							<p style="text-align: left;">图2. 青藏高原石冰川地貌特征统计结果，分别为编目石冰川的面积(a)、最低海拔(b)、坡度(c)、朝向分布(d)、年平均气温(e)、年平均地温(f)、年降水量(g)和年均潜在太阳辐射(h)分布统计。</p>
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							<p align="center">图3. 青藏高原石冰川数目(a)和主要地貌参数(b面积、c最低海拔、d平均坡度)的空间分布特征。</p>						</div>
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">该成果日前以“TPRoGI: a comprehensive rock glacier inventory for the Tibetan Plateau using deep learning”为题发表于地学领域顶级期刊《Earth System Science Data》，该期刊是地球科学领域的顶级综合性期刊，也是中科院一区TOP期刊，2023年影响因子为11.2。</p>
<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">香港中文大学地球与环境科学系博士研究生Sun Zhangyu(孙章宇)为第一作者，Hu Yan(胡燕)研究员为通讯作者；Go-IMAGE团队王晓文、蔡佳欣、郭鑫、何昱君、员海轮等师生参与了该数据集的制作；论文其他合作方包括来自于法国Université Grenoble Alpes和英国University of Exeter大学的研究人员。</p>
</p><strong>论文详细信息：Zhangyu Sun, Yan Hu*, Adina Racoviteanu, Lin Liu, Stephan Harrison, Xiaowen Wang, Jiaxin Cai, Xin Guo, Yujun He, and Hailun Yuan. TPRoGI: a comprehensive rock glacier inventory for the Tibetan Plateau using deep learning. Earth Syst. Sci. Data, 16, 5703–5721, 2024.</strong>

</p><strong>论文链接：https://doi.org/10.5194/essd-16-5703-2024</strong>

</p><strong>数据集下载链接：https://doi.org/10.5281/zenodo.10732042</strong>						</div>
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							<p>撰稿：郭鑫，王晓文</p><p>审核：王晓文，罗子豪</p>						</div>
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		<title>中科院青藏高原研究所曹斌博士(副研究员)到访Go-IMAGE课题组</title>
		<link>https://goimage.cn/20241031-2/</link>
		
		<dc:creator><![CDATA[SARLAB]]></dc:creator>
		<pubDate>Thu, 31 Oct 2024 02:11:49 +0000</pubDate>
				<category><![CDATA[News]]></category>
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					<description><![CDATA[中科院青藏高原研究所曹斌博士(副研究员)到访Go-IMAGE课题组 10月28日，中科院青藏高原研究所曹斌博士 &#8230;<p class="read-more"> <a class="" href="https://goimage.cn/20241031-2/"> <span class="screen-reader-text">中科院青藏高原研究所曹斌博士(副研究员)到访Go-IMAGE课题组</span> 查看全文 &#187;</a></p>]]></description>
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							<p><strong>中科院青藏高原研究所曹斌博士(副研究员)到访Go-IMAGE课题组</strong></p>						</div>
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">10月28日，中科院青藏高原研究所曹斌博士(副研究员)到访Go-IMAGE课题组，并做了《多尺度冻土过程模拟》的学术报告。</p>						</div>
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															<img loading="lazy" decoding="async" width="1024" height="768" src="https://goimage.cn/wp-content/uploads/2024/10/多尺度冻土过程模拟-1024x768.jpg" class="attachment-large size-large wp-image-3276" alt="" />															</div>
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">多年冻土约占北半球陆地面积的20%，是地球冰冻圈的重要组成部分，也是当前气候评估中重要的不确定要素。然而，当前的陆面模式对于多年冻土表征能力有限，适用于全球尺度的独立多年冻土模型缺乏。针对该问题，曹斌博士展示了“全球-区域-景观”不同尺度下的多年冻土过程模拟成果，阐述了气候变化背景下青藏高原和极地多年冻土的演化特征和规律。在问答环节，曹博士与团队成员进行了深入的探讨和交流，并探讨了未来双方在青藏高原和极地多年冻土领域的合作计划。</p>						</div>
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							<p>撰稿：何昱君</p><p>审核：王晓文，罗子豪</p><p> </p>						</div>
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		<title>团队在遥感领域国际顶级期刊RSE发表学术论文</title>
		<link>https://goimage.cn/20240815-2/</link>
		
		<dc:creator><![CDATA[SARLAB]]></dc:creator>
		<pubDate>Thu, 15 Aug 2024 09:09:42 +0000</pubDate>
				<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://goimage.cn/?p=3199</guid>

					<description><![CDATA[团队在遥感领域国际顶级期刊RSE发表学术论文 近日，团队在遥感领域国际顶级期刊Remote Sensing o &#8230;<p class="read-more"> <a class="" href="https://goimage.cn/20240815-2/"> <span class="screen-reader-text">团队在遥感领域国际顶级期刊RSE发表学术论文</span> 查看全文 &#187;</a></p>]]></description>
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							<strong>团队在遥感领域国际顶级期刊RSE发表学术论文
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">近日，团队在遥感领域国际顶级期刊Remote Sensing of Environment发表题为“Characterizing the kinematics of active rock glaciers in Daxue Shan, southeastern Tibetan plateau, using SAR interferometry and generalized boosted modeling”的学术论文。课题组2022级博士研究生蔡佳欣为第一作者，王晓文副教授为通讯作者。</p>

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															<img loading="lazy" decoding="async" width="926" height="403" src="https://goimage.cn/wp-content/uploads/2024/08/论文照片.png" class="attachment-large size-large wp-image-3192" alt="" />															</div>
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							<p align="center">图1 论文首页</p>						</div>
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">该论文针对高寒山区一种特殊的冰缘地貌“石冰川”展开了运动特征和环境控制机理研究。石冰川常发育于高寒山区的多年冻土环境，并在重力作用下沿坡向运动。监测石冰川运动可为区域多年冻土的变化规律提供重要证据，也是了解全球气候暖化条件下石冰川灾害效应的重要手段。由于针对大范围石冰川高时、空分辨率运动观测资料的匮乏，控制石冰川运动的关键环境因素目前还不明确。该研究提出联合升、降轨时序InSAR和表面平行流假设模型的三维时序形变解算方法，以准确获取藏东南大雪山地区超过1000条石冰川的时空运动特征；在此基础上，论文利用梯度推进机模型(GBM)定量评估了控制石冰川运动的主要环境因素。结果显示研究区大部分石冰川的运动速率具有明显的季节性波动规律，而降水和积雪融水是驱动石冰川运动的主要环境因素。论文首次定量揭示了石冰川运动速度对环境因子变化的非线性响应特征，凸显了联合利用多维地表形变观测和高级统计学习模型解析复杂地表运动过程的重要性，对研究高寒山区其它地貌类型如冻融泥流、热融滑塌、冻土滑坡的运动机理具有启发意义。</p>						</div>
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							<p align="center">图2 研究区典型石冰川的年均运动速率</p>						</div>
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							<p align="center">图3 (a) 不同环境因子控制石冰川运动的相对重要程度。(b)–(f) 石冰川运动速率对不同环境因子变化的响应曲线。</p>						</div>
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">Remote Sensing of Environment为中科院一区TOP期刊，其2023年影响因子 (IF) 为11.1，在全球遥感类SCI学术期刊中长期排名第一，具有广泛而深远的国际影响力。该研究得到了国家自然科学基金面上项目(42071410, 42371458)和区域联合基金重点项目(U22A20565)的支持。</p>
<strong>论文详细信息：Cai Jiaxin, Wang Xiaowen*, Wu Tinging, Wu Renzhe, Liu Guoxiang. Characterizing the kinematics of active rock glaciers in Daxue Shan, southeastern Tibetan plateau, using SAR interferometry and generalized boosted modeling. Remote Sensing of Environment, 2024, 313: 114352.</strong>

<strong>论文链接：https://www.sciencedirect.com/science/article/abs/pii/S003442572400378X</strong>						</div>
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							<p>撰稿：蔡佳欣</p><p>审核：王晓文，罗子豪</p>						</div>
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		<title>Go-IMAGE团队顺利完成2024年度贡嘎山石冰川考察与数据采集</title>
		<link>https://goimage.cn/20240804-2/</link>
		
		<dc:creator><![CDATA[SARLAB]]></dc:creator>
		<pubDate>Sun, 04 Aug 2024 07:26:24 +0000</pubDate>
				<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://goimage.cn/?p=3145</guid>

					<description><![CDATA[Go-IMAGE团队顺利完成2024年度贡嘎山石冰川考察与数据采集 位于四川省西部的大雪山是我国横断山脉众多山 &#8230;<p class="read-more"> <a class="" href="https://goimage.cn/20240804-2/"> <span class="screen-reader-text">Go-IMAGE团队顺利完成2024年度贡嘎山石冰川考察与数据采集</span> 查看全文 &#187;</a></p>]]></description>
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							<strong>Go-IMAGE团队顺利完成2024年度贡嘎山石冰川考察与数据采集
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">位于四川省西部的大雪山是我国横断山脉众多山脉之一，其中主峰贡嘎山海拔7556米，是川西高原最高点。受气候，降雨以及高海拔等因素影响，大雪山地区发育有众多的石冰川，然而这些石冰川的分布、运动和地貌特征长期以来鲜为人知。2024年7月25日至7月28日，西南交通大学Go-IMAGE团队王晓文老师带领研究生何昱君、罗子豪，开展了大雪山石冰川的野外调查工作，并重点对贡嘎山子梅垭口附近的石冰川进行实地考察与数据采集。本次科考的工作内容主要包含:
<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">(1) 实地考察和验证实验室通过卫星遥感影像获取的石冰川编目成果；</p>
<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">(2) 通过考察典型石冰川，选取特定目标进行长期观测；</p>
<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">(3) 利用无人机获取石冰川DSM，解析其精细地貌特征。						</div>
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															<img loading="lazy" decoding="async" width="768" height="1024" src="https://goimage.cn/wp-content/uploads/2024/08/贡嘎考察合影-1-768x1024.jpg" class="attachment-large size-large wp-image-3185" alt="" />															</div>
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							<p align="center">图1. 科考工作掠影.</p>						</div>
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															<img loading="lazy" decoding="async" width="1018" height="1024" src="https://goimage.cn/wp-content/uploads/2024/08/贡嘎山石冰川-1018x1024.png" class="attachment-large size-large wp-image-3177" alt="" />															</div>
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							<p align="center">图2. (a) 现场拍摄的石冰川照片；(b)石冰川前缘照片； (c) 石冰川正射影像；</p>						</div>
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							<p>撰稿：何昱君</p><p>审核：王晓文，罗子豪</p><p> </p>						</div>
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		<title>Go-IMAGE团队圆满完成天⼭乌鲁⽊⻬河源冰川与冰缘地貌考察</title>
		<link>https://goimage.cn/20240718-2/</link>
		
		<dc:creator><![CDATA[SARLAB]]></dc:creator>
		<pubDate>Thu, 18 Jul 2024 02:03:52 +0000</pubDate>
				<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://goimage.cn/?p=3001</guid>

					<description><![CDATA[Go-IMAGE团队圆满完成天山乌鲁木齐河源冰川与冰缘地貌考察 在全球气候变暖背景下，世界各地的冰川大多处于消 &#8230;<p class="read-more"> <a class="" href="https://goimage.cn/20240718-2/"> <span class="screen-reader-text">Go-IMAGE团队圆满完成天⼭乌鲁⽊⻬河源冰川与冰缘地貌考察</span> 查看全文 &#187;</a></p>]]></description>
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							<p><strong>Go-IMAGE团队圆满完成天山乌鲁木齐河源冰川与冰缘地貌考察<br /></strong></p>						</div>
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							<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">在全球气候变暖背景下，世界各地的冰川大多处于消融状态，冰川水资源的消逝严重威胁下游居民的生产生活、经济发展乃至生态环境。石冰川是冰、岩混杂堆积形成的典型冰缘地貌，其内部富含的冻结冰是干旱/半干旱地区重要的淡水资源库（Barsch, 1996; Wang et al,. 2017）。中国新疆天山地区发育有大量冰川和石冰川，监测它们的变化对探究气候变暖背景下该地区水资源变化响应和潜在影响意义重大。</p>
<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">2024年7月4日至7月11日，西南交通大学Go-IMAGE团队研究生何昱君、罗子豪联合香港中文大学、中科院天山站的研究团队，开展了新疆天山乌鲁木齐河源冰川与冰缘地貌野外考察。本次科考主要工作内容包括以下四个方面：</p>
<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">(1) 通过实地考察并探索路线，筛选后续可持续观测的典型石冰川；</p>
<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">(2) 实地观测朱诚等（Zhu et al., 1996）在大西沟地区记录的石冰川，观察石冰川的地貌特征；</p>
<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">(3) 利用无人机进行航测与建模，用于后续研究长时序下天山石冰川的形态和形变；</p>
<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">(4) 考察天山河源-1号冰川，并现场判识不同地貌单元，加深对冰缘地貌的理解。</p>
<p style="margin-top: 0.3em; margin-bottom: 0.3em; text-indent: 2em;">本次野外考察工作区海拔高达4000m，团队成员翻山越岭、爬山涉水，圆满完成了上述预定的科考目标。同时，本次科考作业加深了本团队与香港中文大学、中科院西北院之间的合作，为后续针对天山地区地区石冰川和冰川持续联合研究奠定了基础。</p>						</div>
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															<img loading="lazy" decoding="async" width="1024" height="833" src="https://goimage.cn/wp-content/uploads/2024/07/图片1-1024x833.png" class="attachment-large size-large wp-image-3004" alt="" />															</div>
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							<p align="center">图1.  科考工作掠影. 其中，(a-c) 为天山河源-1号冰川；(d) 为朱诚于1996年拍摄的2号石冰川；(e) 为本次UAV所拍摄的2号石冰川；(f) 为2号石冰川现场环境实拍；(g-j) 为现场工作照片</p>
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							参考文献

<p style="margin-top: 0.3em; margin-bottom: 0.3em;">[1] Barsch D. 1996. Rockglaciers: Indicators for the Present and Former Geoecology in High Mountain Environments. Berlin: Springer-Verlag.

<p style="margin-top: 0.3em; margin-bottom: 0.3em;">[2] Wang X W, Liu L, Zhao L, et al. 2017. Mapping and inventorying active rock glaciers in the northern Tien Shan of China using satellite SAR interferometry. The Cryosphere, 11(2): 997-1014.
<p style="margin-top: 0.3em; margin-bottom: 0.3em;">[3] Zhu C, Zhang J, Cheng P. 1996. Rock glaciers in the Central Tianshan Mountains, China. Permafrost and Periglacial Processes, 7(1): 69–78.						</div>
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							<p>撰稿：何昱君</p><p>审核：王晓文，罗子豪</p><p> </p>						</div>
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		<title>Go-IMAGE团队参加第一届雷达干涉测量学术研讨会</title>
		<link>https://goimage.cn/20240627-2/</link>
		
		<dc:creator><![CDATA[SARLAB]]></dc:creator>
		<pubDate>Thu, 27 Jun 2024 04:59:26 +0000</pubDate>
				<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://goimage.cn/?p=2940</guid>

					<description><![CDATA[Go-IMAGER团队参加第一届雷达干涉测量学术研讨会 2024年6月15日，第一届雷达干涉测量学术研讨会在武 &#8230;<p class="read-more"> <a class="" href="https://goimage.cn/20240627-2/"> <span class="screen-reader-text">Go-IMAGE团队参加第一届雷达干涉测量学术研讨会</span> 查看全文 &#187;</a></p>]]></description>
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							<strong>Go-IMAGER团队参加第一届雷达干涉测量学术研讨会</strong>						</div>
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							<p style="text-indent: 2em;">2024年6月15日，第一届雷达干涉测量学术研讨会在武汉召开。本次研讨会以“感知地球脉动，赋能新质生产力”为主题，针对国家对地观测重大任务和全球可持续发展目标等迫切需求，对雷达干涉测量技术 ( InSAR ) 新理论、新方法、新技术开展研讨，分享前沿研究成果、共议未来发展方向。Go-IMAGE团队负责人王晓文带领团队众多硕博研究生参会。</p>						</div>
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															<img loading="lazy" decoding="async" width="1024" height="752" src="https://goimage.cn/wp-content/uploads/2024/06/Go-IMAGE团队参会人员合影-1024x752.png" class="attachment-large size-large wp-image-2941" alt="" />															</div>
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							<p align="center">图1. Go-IMAGE团队参会人员合影</p>						</div>
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							<p style="text-indent: 2em;">王晓文老师于16日在本次大会“地震与火山”专题作了题为“联合卫星 InSAR 和多源DEM的Usu火山大尺度地形变化估计与分析”的口头报告。报告介绍了使用InSAR技术测量日本Usu火山多次喷发导致的地形变化，并分析了该火山内部岩浆补给速率和潜在喷发危险。同日，团队师悦龄博士和毛文飞博士分别在“冰冻圈变化与过程”专题和“时序InSAR理论与方法进展”专题作了题为“SAR PO-SBAS技术估计冰湖对藏南对压冰川运动的影响”和“联合时序InSAR和IRI模型的高分辨率电离层总电子含量制图”的口头汇报。</p>						</div>
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							<p align="center">图2. Go-IMAGE团队负责人王晓文作口头汇报</p>						</div>
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							<p align="center">图3. Go-IMAGE团队其他成员作口头汇报</p>						</div>
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							<p style="text-indent: 2em;">此外，团队博士研究生蔡佳欣、吴婷婷和硕士研究生郭鑫在15日下午的快播报告会场进行了快播报告。蔡佳欣博士所作题为“基于三维时序InSAR的大雪山石冰川运动特征与环境控制机制分析”的报告得到了会场专家的一致认可，获评为“优秀快播报告”。在本次大会的闭幕式上，蔡佳欣博士被授予了优秀快播报告荣誉证书。</p>						</div>
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							<p align="center">图4. 蔡佳欣博士被授予优秀快播报告的荣誉证书</p>						</div>
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							<p>撰稿：吴婷婷</p>
<p>审核：王晓文，罗子豪</p>						</div>
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		<title>团队参加第一届中国冰冻圈遥感与大数据学术研讨会</title>
		<link>https://goimage.cn/20240603-2/</link>
		
		<dc:creator><![CDATA[SARLAB]]></dc:creator>
		<pubDate>Mon, 03 Jun 2024 07:17:49 +0000</pubDate>
				<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://goimage.cn/?p=2906</guid>

					<description><![CDATA[团队参加第一届中国冰冻圈遥感与大数据学术研讨会 2024年5月23日至25日，第一届中国冰冻圈遥感与大数据学术 &#8230;<p class="read-more"> <a class="" href="https://goimage.cn/20240603-2/"> <span class="screen-reader-text">团队参加第一届中国冰冻圈遥感与大数据学术研讨会</span> 查看全文 &#187;</a></p>]]></description>
										<content:encoded><![CDATA[		<div data-elementor-type="wp-post" data-elementor-id="2906" class="elementor elementor-2906">
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							<p><strong>团队参加第一届中国冰冻圈遥感与大数据学术研讨会</strong></p>						</div>
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							<p style="text-indent: 2em;">2024年5月23日至25日，第一届中国冰冻圈遥感与大数据学术研讨会在长沙召开。来自全国各地69家单位的专家学者和研究生代表近200人齐聚一堂，以“冰冻圈遥感与大数据—智能化的新未来”为主题，分享交流最新遥感与大数据的理论技术方法、数据产品与应用。</p>

<p style="text-indent: 2em;">Go-IMAGE团队负责人王晓文在大会“冰缘地貌遥感”专题作了题为“基于卫星 InSAR 的藏东南石冰川运动特征与环境控制机理分析”的口头报告。报告介绍了中国西部石冰川的研究现状和最新进展，并重点介绍了团队针对藏东南石冰川运动特征和机理所做的工作和发现。与会期间，王晓文老师同时和中科院西北院、以及香港中文大学的同行交流了暑期针对青藏高原石冰川的联合考察计划。</p>						</div>
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															<img loading="lazy" decoding="async" width="658" height="438" src="https://goimage.cn/wp-content/uploads/2024/06/冰冻圈论坛.jpg" class="attachment-large size-large wp-image-2909" alt="" />															</div>
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							<p>撰稿: <span style="color: var( --e-global-color-astglobalcolor2 ); background-color: var(--ast-global-color-5);">王晓文</span></p><p>审核：王晓文，任旭</p>						</div>
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