Multi-temporal SAR Interferometry Applications for Disaster Mitigation

Organizer
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS)， Wuhan University
Co-organizers
Hi-Target Satellite Navigation Technology Co., Ltd.
Joint International Research Laboratory of GeoInformatics (JIRLG)
UN-GGIM Acedamic Network
GIS Theory and Methodology Working Group, CAGIS
Committee on International Spatial-temproal Information Services, GNSS & LBS Association of China
ISPRS TC III
LiDAR Specialty Committee, Chinese National Committee of the International Society for Digital Earth (ISDE)
LIESMARS
English
GeoScience Cafe MSc Program PhD Program
LIESMARS MSc & PhD Programs Admission: igeo@whu.edu.cn

前言 Preface
2021 年地球空间信息科学国际暑期学校于 2021 年 8 月 23 日 -31 日举行。本次活动共有来自 33 个国
家和地区的 107 名学员参加。从不同时区到同一间线上教室，从理论学习到项目实践，地球空间信息科学
领域的青年学者相聚云端，共同探讨 InSAR、机器学习和地理空间大数据与灾害管理等方向的学术前沿问
题。短短的九天时间，学员们不仅学到新的知识，迸发出思维的火花，更领略了“云端”交流的方便快捷，
不同文化的无限魅力。
The 2021 International GeoInformatics Summer School (Online) was held from August 23rd
to 31st, 2021. There were 107 students from 33 nations and regions attending this school. From
different time zones to a same Zoom class, from the theory to practice, young scholars in the
field of GeoInformatics gathered in this online classroom to study frontier academic issues such
as InSAR, Machine Learning, Geospatial Big Data, and Disaster Management. Over the course
of nine days, students were energized and inspired–to not only learn new things, but also to
appreciate the convenience of online communication and the charm of different cultures.

目录 Contents
Part I 开幕式 Opening Ceremony
Part II 课程简介 Courses
Part III 学术前沿报告 Academic Reports
Part IV 活动与交流 Cultural Exchange Activities
Part V 教师寄语 Teachers' Remarks
Part VI 闭幕式 Closing Ceremony
Part VII 附录 Appendix
优秀课程报告奖 Excellent Participant Award Works
文化交流奖 Cultural Promoter Award works
学员感想 Students Share Impressions
志愿者名单 Volunteers List
学员名单 Students List
Part I
Opening Ceremony 开幕式

测绘遥感信息工程国家重点实验室
(LIESMARS) 是世界著名的地理空间信息科学和
技术机构，这里有优秀的教师团队。他们从事摄影
测量、遥感、地理信息系统、全球导航位置服务、
3S 集成等领域的研究。在当今人们高度依赖的网
络空间，LIESMARS 的教授学者们借助 5G/6G、
云通信和人工智能的手段，通过数字孪生技术，将
物理空间投影到网络空间，并使用更多的技术来帮
助人们管理真实的空间。李德仁院士真诚邀请学员
们在疫情之后，来武汉学习，到武汉大学，看看我
们最好的校园。
LIESMARS is well known worldwide as an institution
specializing in geospatial information science and
technology. There are good teachers here. They work on
photogrammetry, remote sensing, GIS, GNSS, and also the
integration of GNSS, RS, and GIS. Beside physical space,
we also live online in cyberspace. With 5G/6G, cloud
communication technologies and artificial intelligence, we
can make the physical space project into the cyberspace
through Digital Twins techniques. In cyberspace, we can
use digital techniques to help people manage real space.
Prof. Li sincerely invited all the students to come to Wuhan
University for learning, to see our campus in the near
future.
当前全球社会面临深刻挑战，例如、公共卫生
安全、气候变化、疫情防控等。大学作为基础研究、
人才培养和技术创新的结合体，应在科技研发、经
济和社会服务等方面发挥关键作用。
武汉大学历史悠久、学科基础雄厚。近年来，
随着学术、科技的提高，学校正不断在国际舞台上
展现出竞争力和实力。我们始终致力于培养具有国
际视野和实践能力的高层次人才，并呼吁各位优秀
的青年一同迎接这个充满机遇和呼唤行动的时代，
更好地服务国家和社会，构建人类命运共同体。
Currently the global community is facing profound
challenges, such as public health crises, climate change,
epidemic prevention and control. As a site for basic
research, talent cultivation, and technological innovation,
universities play a key role in tackling key problems in
scientific and technological research and development as
well as those in economics and social services.
Wuhan University has a long history with a solid foundation
across many disciplines. In recent years, the university has
demonstrated its competitiveness and competence on the
international stage resulting in a rising academic, scientific,
and technological status. We strive to cultivate high-level
talents with international vision and practical abilities,
hence we welcome all outstanding young people who want
to meet this era full of opportunities and challenges and
seek to better serve their countries and societies, and in
this way, build a “community of common destiny”.
武汉大学副校长唐其柱教授致辞
Speech by Prof. Qizhu Tang，
vice president of Wuhan University
李德仁院士致辞
Keynote Talk by Prof. Deren Li
2 3

十年前，当我们决定组织第一届地球空间信息
科学国际暑期学校时，我们没有想到我们会每年都
举办一次暑期学校。但是，在过去的几天里，当我
回顾这些年来我们一起拍摄的视频和照片时，我不
禁被这些美妙的瞬间感动了。在过去的几十年中，
地理信息学的发展取得了巨大的成就，不仅在学术
界，而且在工业技术方面也取得了巨大的成就，也
在政府部门、公司、个人生活的几乎所有领域都有
越来越多的创新应用。我们呼吁更多优秀的青年，
加入实验室和这一领域，共同建设一个可持续的绿
色地球。
Ten years ago, when we decided to organize the 1st
international summer school of Geoinformatics, we did
not expect that this summer school happen annually.
But, in the last few days, when I reviewed the video and
photos that we had taken over the past years, I can’t
help being moved by these amazing moments. The past
several decades witnessed the great achievements in the
development of GeoInformatics, not only in academia,
but also the technologies in the industry. There are more
and more innovative applications supported by geospatial
technology in almost all fields of government sectors,
companies, and personal life. Prof. Wu called on the young
talents to join LIESMARS and this field for a sustainable
and green planet.
吴华意教授主持
Speech by Prof. Huayi Wu, host of the ceremony
Part II
Courses 课程简介
4

课程简介：
本课程旨在介绍合成孔径雷达干涉测量技术，
以及多时相 SAR 干涉测量技术，
如 PSInSAR 技术的应用。
同时对使用雷达干涉测量在灾害监测中的应用案例进行了展示。包含以下主题：
1. 合成孔径雷达遥感简介
2. 干涉合成孔径雷达简介
3. 利用 D-InSAR 技术进行地表移动估计及相关方法
4. 多时相干涉合成孔径雷达简介
5. 不同方法的比较分析：PS-InSAR，SBAS，SqueeSAR
6. 利用像素偏移量跟踪方法进行地表移动估计
7. 合成孔径雷达在地质灾害与基础设施稳定性监测中的应用
Abstract:
In this course, Synthetic Aperture Radar Interfermetry is introduced and multi-temporal SAR interferometry methods, like
PSInSAR, are introduced. Methods and applications for using SAR interferometry for disaster mitigation are shown. It is
designed for graduate students in Geographic Information Sciences and Remote Sensing. The course includes the following
topics:
1. Introduction to Synthetic Aperture Radar Remote Sensing
2. Introduction into SAR interferometry
3. Surface motion estimation with D-InSAR and derived methods
4. Introduction to multi-temporal SAR interferometry
5.Comparative analysis of different methods, like PSInSAR, SBAS, SqueeSAR, etc.
6. Surface motion estimation with pixel offset tracking
7. Applications of SAR in monitoring geohazards and infrastructure stability
课程一：多时相雷达干涉测量减灾应用
SSI Multi-temporal SAR Interferometry
for Disaster Mitigation
廖明生教授，工学博士（摄影测量与遥感），博士生导师。
2013 年入选武汉大学珞珈杰出学者。国土资源部地面沉降监测
与防治重点实验室学术委员会委员，香港中文大学太空与地球信
息科学研究所客座研究员，中国南极测绘研究中心兼职博导。
长期从事航空航天遥感影像信息分析与应用的理论与方法研
究，主要研究兴趣为雷达干涉测量、极化干涉测量技术及其在
地形测绘、地质灾害监测和基础设施安全等领域的应用。
先后主持了国家自然科学基金重点项目“高分辨率 SAR 图
像城市目标认知解译与动态监测应用研究”和面上项目“从星载
雷达影像提取地面三维信息的研究”、“时间序列雷达干涉影像
中相位信号的分析方法”，863 项目“基于 D － InSAR 点目标
方法的城市地表沉降监测的关键技术”，国家 973 项目课题“多
源观测数据与滑坡机理模型同化理论与方法研究” 和“地表形
变场与地下水热参数探测的理论与方法”等国家级项目。
近几年发表论文百余篇，
被 SCI、
EI 或 ISTP 检索百余篇次，
出版《时间序列 InSAR 技术与应用》、《雷达干涉测量学》等
多部专著。
About the lecturer:
Prof. Mingsheng Liao received the B.S. degree in electronic engineering from Wuhan Technical University of Surveying
and Mapping (WTUSM), Wuhan, China, in 1982, the M.A. degree in electronic and information engineering from Huazhong
University of Science and Technology, Wuhan, China, in 1985, and the Ph.D. degree in photogrammetry and remote sensing
from WTUSM, in 2000. He works at the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote
Sensing (LIESMARS), Wuhan University, Wuhan, where he became a Professor in 1997. He is the principal investigator
of several projects funded by the Ministry of Science and Technology (MOST) China and the Natural Science Foundation
of China. He is also the PI/Co-PI of the ESA-MOST cooperative Dragon I (2004–2008), II (2008–2012), III (2012–2016), IV
(2016– 2020) and V(2020-2024) projects. He has published more than 200 peer-reviewed journal papers and five books as
well as chapters on techniques and applications in synthetic aperture radar interferometry. His research interests include
remote sensing image processing and analysis, algorithms for interferometric synthetic aperture radar, applications of InSAR
/ PS-InSAR in monitoring geohazards.
授课教师简介：
Timo Balz 教授出生于德国斯图加特，于 2001 年及 2007
年分别在斯图加特大学取得地理学本科学位及航空工程及大地
测量学博士学位。2001 年秋季到 2007 年底，在斯图加特大学
摄影测量研究所担任研究助理工作。2004 年至 2005 年，武
汉大学的访问学者。2008 年至 2010 年，担任了武汉大学测绘
遥感信息工程国家重点实验室博士后研究员。2010 年至 2015
年在 LIESMARS 担任雷达遥感副教授。自 2015 年起，他是
LIESMARS 的全职教授。Timo Balz 教授是遥感、IEEE 地球
科学和遥感快报的副主编，也是地理空间信息科学和遥感编辑委
员会的成员。自 2016 年起，他担任 ISPRS 第一委员会 SAR 和
微波传感工作组主席。imo Balz 教授在期刊、书籍和会议记录
上发表了大约 150 篇科学论文。Timo Balz 的研究兴趣包括利
用 SAR 进行地表运动估计、数据可视化、SAR 大地测量以及利
用 SAR 数据支持考古勘探。
6 7

课程二：机器学习
SSII Machine Learning
课程简介：
本课程旨在介绍现代机器学习原理和算法，以
及计算机视觉中典型的问题及其应用。包括以下主
题 :
1. 机器学习概述
2. 神经网络与深度学习
3. 支持向量机
4. 谱聚类
5. 计算机视觉应用案例
Abstract:
The course aims to provide an introduction to modern
machine learning principles and algorithms and to describe
their applications to selected problems in computer vision.
The course includes the following topics:
1.Introduction to machine learning
2.Neural networks and deep learning
3.Support vector machines
4.Graph-based clustering
5.Selected computer vision applications
Prof. Timo Balz was born in Stuttgart, Germany. He received the Diploma degree (Dipl.-Geogr.) in geography and the
Doctoral degree (Dr.-Ing.) in aerospace engineering and geodesy from the Universitaet Stuttgart, Stuttgart, in 2001 and
2007, respectively.
From fall 2001 to the end of 2007, he was a Research Assistant with the Institute for Photogrammetry, Universitaet Stuttgart.
Between 2004 and 2005, he was a Visiting Scholar with Wuhan University, Wuhan, China. From 2008-2010, he was a
Postdoctoral Research Fellow with the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote
Sensing (LIESMARS), Wuhan University. From 2010-2015 he was Associate Professor for Radar Remote Sensing with
LIESMARS. Since 2015 he has been a Full Professor with LIESMARS. Since 2021, he has been the Vice-Director of the
International Academy of GeoInformation, Wuhan University.
He serves as Associate Editor for Remote Sensing and he is member of the editorial board of Geo-Spatial Information
Science. Since 2016 he is Chair of the ISPRS Commission I Working Group on SAR and Microwave Sensing. He has
authored and co-authored more than 150 scientific articles in journals, books, and conference proceedings.
Timo Balz’s research interests include surface motion estimation with SAR, data visualization, SAR geodesy, and the use of
SAR data to support archaeological prospecting.
张路，工学博士 , 教授。主要从事雷达遥感数据处理与分析、
遥感影像分类和变化检测等领域的研究。主持国家自然科学基金
2项，
参与承担多项国家自然科学基金、
科技部973项目、
863项目、
香港 RGC 基金项目等国家级和省部级科研课题及 ESA、JAXA、
DLR、ASI 等组织的多个国际合作研究项目，作为核心成员自主
研制开发了 InSAR/D-InSAR 数据处理软件平台，登记软件著作
权三项。近年来公开发表学术论文 40 余篇，包括 SCI 期刊论文
13 篇，并担任 IJRS、PE&RS、ISPRS Journal 等国际学术期刊
审稿人。2010 年 6-12 月，在中欧合作“龙”计划支持下，由国
家遥感中心选派赴欧洲空间局对地观测研究中心（ESRIN）进行
了为期六个月的合作研究。
Prof. Lu Zhang received his Ph.D degree of Photogrammetry and Remote Sensing in 2005. From 2005 to 2007 he has been
a Post-Doctoral Research Fellow at the Institute of Space and Earth Information Science, Chinese University of Hong Kong.
Since 2007, he has worked at the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote
Sensing (LIESMARS), becoming a Full Professor in 2012. During the period from Jun 2010 to Dec 2010, he was a visiting
scholar at the European Space Research Institute (ESRIN), an ESA (European Space Agency) specialized center located
at Frascati, Italy. His research is focused on SAR remote sensing as well as remote sensing classification and change
detection. He is the PI of three research projects funded by the National Natural Science Foundation of China (NSFC). He
was involved in several large research projects funded by the Ministry of Science and Technology (MOST) and NSFC. At the
same time, He is a key team member in the LIESMARS research group for the ESA-MOST cooperative Dragon I (2004-2008),
II (2008-2012), III (2012-2016) and IV (2016-2020) projects under the theme “Terrain Measurement”. Supported by ESA
data under the Dragon programme, in-depth studies have been carried out by the research group in the fields of topographic
mapping, land subsidence, and infrastructure safety monitoring in urban areas, and landslide surface deformation mapping.
. In addition, he also has served as a key member on the research teams for scientific research projects dedicated to DLR’s
TerraSAR-X and JAXA’s ALOS satellites. In recent years, he has published about 50 scientific papers.
8 9

课程三：社会感知和大数据计算在灾害管理中的
应用、挑战和解决方案
SSIII Social Sensing, Geospatial Big Data Computing,
and Disaster Management
Marcello Pelillo 是意大利威尼斯大学计算机科学系资深教授，欧盟人居技术中心和威尼斯大学计算机
视觉与模式识别小组发起人和负责人。
他曾在耶鲁大学
（美国）
、
麦吉尔大学
（加拿大）
、
维也纳大学
（奥地利）
、
约克大学（英国）、伦敦大学学院（英国）、澳大利亚国家信息通信技术学院（NICTA）、武汉大学（中国）、
华中科技大学（中国）、华南理工大学（中国）等担任访问学者 / 客座教授职位。他的研究兴趣集中在计算
机视觉、机器学习和模式识别等领域，已在相关期刊、会议发表了 200 多篇学术论文。
Marcello Pelillo 教授还曾担任包括 ICPR、ECCV、BMVC 等多个会议的轮次主席和区域主席。曾
在 IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Pattern Recognition,
Brain Informatics 等国际期刊任职（副主编），在 International Journal of Machine Learning and
Cybernetics 咨询委员会任职，并担任 EMMCVPR、IWCV、SIMBAD 等国际会议程序委员会主席 (PC
Chair)，ICCV 2017 大会主席。作为 SIMBAD（欧盟 FP7 项目，致力于基于相似性的模式分析和识别）等
多个研究项目的科学协调员，
Pelillo 教授被选为 IEEE Fellow，
IAPR Fellow，
IEEE 杰出讲者
（2016-2017）
。
他的 Erdös 数为 2。
About the lecturer:
Prof. Marcello Pelillo is a Full Professor of Computer Science at Ca’ Foscari
University, Venice, where he leads the Computer Vision and Pattern Recognition
Lab, which he established in 1995. He has been the Director of the European
Centre for Living Technology (ECLT) and has held visiting research/teaching
positions in several institutions including Yale University (USA), University
College London (UK), McGill University (Canada), University of Vienna (Austria),
York University (UK), NICTA (Australia), Wuhan University (China), Huazhong
University of Science and Technology (Wuhan, China), South China University of
Technology (Guangzhou, China). He is also an external affiliate of the Computer
Science Department at Drexel University (USA). His research interests are in the
areas of computer vision, machine learning and pattern recognition where he has
published more than 200 technical papers in refereed journals, handbooks, and
conference proceedings.
He has been General Chair for ICCV 2017 and is Program Chair for ICPR 2020. He has also been Track Chair and Area
Chair for several conferences including ICPR, ECCV, BMVC, etc. He serves or has served on the Editorial Boards of
several journals, including IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Pattern Recognition,
IET Computer Vision, Frontiers in Computer Vision and Image Analysis, Brain Informatics, IEEE Transactions on Neural
Networks and Learning Systems (Guest Editor), Pattern Recognition Letters (Guest Editor), and serves on the Advisory
Board of Springer’s International Journal of Machine Learning and Cybernetics. He is or has been Scientific Coordinator of
several research projects, including SIMBAD, an FP7 FET-Open project devoted to similarity-based pattern analysis and
recognition which resulted in a Springer book, and has been awarded a Samsung Global Research Outreach (GRO) grant.
Prof. Pelillo has been elected Fellow of the IEEE and Fellow of the IAPR and is an IEEE SMC Distinguished Lecturer. His
Erdös number is 2.
课程简介：
本课程旨在总体介绍地理空间大数据的概念
和相关计算技术 , 讨论社会传感和社交媒体数据分
析的概念及其在灾害管理中的应用 , 并运用基本的
编程技术 (Python, JavaScript，web mapping),
从数据收集到在线可视化，对带有地理标记的
Twitter 数据的进行分析。包括以下主题：
1. 社会感知和大数据计算技术在灾害管理中
的应用介绍
2. 空间大数据计算技术
3. 基于 Python 和 Hadoop 的社交媒体
（Twitter）数据收集、分析与实践
4. 基于 JavaScript 和 Leaflet 的社交媒体网
络地图：基本介绍及实践
5. 基于 JavaScript 和 Leaflet 的社交媒体网
络地图：轨迹制图及实践
Abstract:
This short summer school course will 1) provide students
with an overview of the concept of geospatial big data and
relevant computing technologies for handling such data,
2) discuss the concept of social sensing and social media
data analytics as well as its applications with regards
to disaster management, and 3) introduce some basic
and practical steps/programming techniques (Python,
JavaScript, and web mapping) for geotagged Twitter data
analysis from data collection to online visualization (with
hands-on exercises).
The course includes the following topics:
1. Introduction to social sensing and big data computing
for disaster management
2. Geospatial big data and computing techniques
3. Social media (Twitter) data collection and analytics with
Python and Hadoop
4. Web mapping of social media data with JavaScript and
Leaflet: introduction and basics
5. Web mapping of social media data with JavaScript and
Leaflet: trajectory mapping
10 11

Part III
Academic Reports 学术前沿报告
李振龙，博士，美国南卡莱罗纳大学地理系副教授（终身教授），博士生导师，地理信息和大数据研究
实验室创始主任。 2006 年毕业于武汉大学遥感信息工程学院。2015 年获得美国乔治梅森大学地球系统和
地理信息科学博士学位。
致力于在数据和计算密集型地理信息科学领域时空大数据处理和分析，
高性能计算，
CyberGIS 和 GeoAI 的跨学科的教学和研究。
曾任美国地理学家协会（AAG）地学网络空间基础设施 Specialty Group（CISG）主席，美国地球
科学信息联合学会（ESIP）时空云计算联合主席，和国际华人地理信息科学学会（CPGIS）理事。现任
PLOS ONE 、ISPRS International Journal of Geo-Information 、Big Earth Data、和 Geo-spatial
Information Science 编委会成员和 30 余本国际学术期刊审稿人。
曾主持或参与美国国家科学基金
（NSF）
、
美国国立卫生研究院（NIH）、美国航空航天局（NASA）和南卡莱罗纳大学（USC）等资助的多项基金项目。
发表学术论文 80 余篇，其中 SCI 收录 45 篇。参与编写出版学术专著 3 部，主持编写 4 个国际学报专刊。
About the lecturer:
Prof. Zhenlong Li is an Associate Professor in the Department of
Geography at the University of South Carolina (USC), where he
established and leads the Geoinformation and Big Data Research
Laboratory (GIBD). He received B.S. degree in Geographic Information
Science from Wuhan University in 2006 and Ph.D. (with distinction)
in Earth Systems and Geoinformation Sciences from George Mason
University in 2015. He is recognized as a Breakthrough Star by USC in
2020 and is listed as one of the Geospatial World 50 Rising Stars by the
Geospatial Media and Communications in 2021. He is also a Peter and
Bonnie McCausland Faculty Fellow (2020-2023) at the USC College of
Arts and Sciences.
Prof. Li’s primary research field is GIScience with a focus on geospatial big data analytics, high performance computing,
spatiotemporal analysis/modeling, cyberGIS, and geospatial artificial intelligence with applications to disaster management,
climate analysis, human mobility, and public health. He has more than 100 publications including over 60 peer-reviewed
journal articles, 20 articles in books and proceedings, and four edited books. He has received funding support from United
States National Science Foundation (NSF), National Institutes of Health (NIH), and Federation of Earth Science Information
Partners (ESIP) among others. He served as the Chair of the Cyberinfrastructure Specialty Group (CISG) of Association
of American Geographers, Co-Chair of ESIP Cloud Computing Group, and the Board of Director of the International
Association of Chinese Professionals in Geographic Information Sciences (CPGIS). Currently, he sits on the Editorial Board
of four international journals and serves as a peer reviewer for more than 30 journals.
12

万物互联时代的地理空间信息学
On Geospatial Information Science in the era
of the Internet of Things
报告人：李德仁院士
Reporter: Prof. Deren Li
摘要：
随着 5G/6G、云计算、物联网和人工智能等新技术的发展，人类已经进入了万物互联的新时代。本报
告对万物互联时代地球空间信息技术的五大特点进行了探讨：卫星定位技术从 GNSS 向服务覆盖范围更广
的 PNT 发展；遥感技术从孤立的卫星观测走向联合的空 - 天 - 地传感网络；地理信息服务从地图数据库走
向真三维实景和数字孪生；3S 集成从移动测量向智能机器人服务发展；地理信息空间学的学科研究范围从
对地观测走向揭示人类与自然关系的人类观测。报告基于这些特点进一步剖析新时代面临的挑战，并提出新
时代学科发展需要解决的三大科学问题：1. 地理信息产品如何同时满足人和机器人的需求？ 2. 遥感影像自
动解译是基于传统的符号化分类还是基于本体的语义网格描述？ 3. 如何利用时空大数据的挖掘来回答人与
自然的关系，从空间感知走向空间认知，推进社会可持续发展。最后提出对于万物互联时代地球空间信息学
的展望：希望学界专家同仁，发挥大智慧，抓住新机遇，努力解决好我们面临的三大科学问题，推动万物互
联时代地球空间信息学的发展，实现万物互联的数字中国和智慧社会。可以在宏观、中观和微观尺度上做出
时空大数据空间感知和认知方面的巨大贡献！
Abstract：
With the development of new technologies such as 5g / 6G, cloud computing, Internet of things and artificial intelligence,
we have entered a new era of the internet of things. This report discussed the five characteristics of geospatial information
technology in the era of the internet of things: the development of satellite positioning technology has changed from GNSS
to PNT with wider service coverage; Remote sensing technology has moved from isolated satellite observation to space-air-
ground wireless sensor network; Geographic information service moves from map database to true 3D realistic scene and
digital twin; 3S integration develops from mobile measurement to intelligent robot service; The research scope of Geospatial
Information Science changes from earth observation to human observation in order to reveal the relationship between
human and environment. Based on these characteristics, the report further analyzes the challenges in the new era, and puts
forward three major scientific issues to be solved: 1. How can geographic information products meet the needs of people
and robots at the same time? 2. Remote sensing image automatic interpretation should be based on traditional symbolic
classification or ontology based semantic grid description? 3. How to use spatio-temporal big data mining to answer the
relationship between human and nature, to realize the leap from spatial perception to spatial cognition, and promote social
sustainable development. Finally, the report puts forward the prospect of geospatial informatics in the era of internet of
things: we hoped that academic experts and colleagues will give full play to their great wisdom, seize new opportunities,
strive to solve the three major scientific problems we face, in order to promote the development of geospatial informatics
science in the era of internet of things, and realize the digital China and intelligent society in the era of internet of things.
We can make great contributions to spatial perception and cognition of spatio-temporal big data on macro, meso and micro
scales!
城市遥感不透水面提取及其在海绵城市中的应用
Urban remote sensing for impervious surface
extraction and its applications in sponge city
报告人：邵振峰教授
Reporter: Prof. Zhenfeng Shao
摘要：
不透水面是城市重要的土地覆盖类型，其面积占比是评价城市生态环境质量的重要指标，能够直观反映
一个地区的城市化进程。随着城市人口和对生活和工作空间需求的不断增加，城市用地面积不断扩大，不透
水面占比逐渐增加。农田、草地、森林等自然用地正在迅速减少。城市不透水面的增加会带来一系列城市
生态问题，例如：城市不透水面的扩张会导致地表径流增加，造成城市内涝频繁；城市不透水面导致自然
地表的减少会加剧城市热岛效应。遥感技术的发展为大面积、多尺度、时序化监测不透水面分布提供了有效
的技术手段。报告首先介绍了城市遥感不透水面提取的研究背景、意义以及相应的制图要求。其次，针对城
市不透水面提取工作中影响精度的云雾遮挡、建筑及树木阴影等固有问题提出了对应的解决方法。此外，还
结合天津、上海、武汉等多地的应用实例介绍了若干种城市不透水面提取方法，为海绵城市的规划建设，老
旧小区改造等提供了决策依据。最后，报告展望了未来的研究方向与国际合作，同时指出城市不透水面提取
将向着多源数据融合的方向发展，例如将光学影像与 LiDAR 影像结合提取不透水面。
Abstract：
Impervious surface area is an important type of urban land cover, which can directly reflect the urbanization process of a
region. Impervious surface area proportion is an important index to evaluate the quality of urban ecological environment.
With the increase of urban population and the increasing demand for living and working space, the urban land area is
expanding, and the proportion of Impervious surface area is gradually increasing. In contrast, farmland, grassland, forest and
other natural land are rapidly decreasing. The increasing proportion of ISA will bring a series of urban ecological problems,
such as: ISA will increase surface runoff, resulting in frequent urban waterlogging; The natural surface substitution effect
brought by the increase of ISA will aggravate the urban heat island. The development of remote sensing technology provides
effective technical means for large-area, multi-scale, and time-series monitoring of impervious surface area distribution. The
report first introduces the research background and significance of impervious surface area extraction and then describes
the impervious surface area mapping requirements. According to the inherent problems in the high-spatial resolution of the
remote sensing image, such as clouds issue, building and tree shadows, which leads to the low accuracy of the impervious
surface extraction, the report introduces some solutions for cloud and shadow detection. In addition, the report also
introduces several impervious surface area extraction methods and monitoring application examples in Tianjin, Shanghai,
Wuhan and other places. These application examples provide a basis for decision-making in the planning and construction
of sponge cities and old communities renewal. Finally, the report not only looks forward to future researches and also
introduces the further cooperation work with international professors and students. Besides, the report points out that the
urban impervious surfaces area extraction will develop in the direction of multi-source data fusion, such as the combination
of optical data and LiDAR, which can improve image classification results.
14 15

Part IV
Cultural Exchange Activities 活动与交流

破冰活动在三个课程微信群里进行，老师、学员
和志愿者各自介绍了自己的国家，大学及家乡美食或
风俗。跨越网络，学员们迅速地了解彼此，建立友谊。
在游戏和欢笑中消除了彼此间的陌生感，友谊也因此
萌芽。
Icebreaking games were held in courses WeChat groups.
Teachers, students and volunteers introduced their
homeland, universities and classic cuisine. Across the virtual
network, the students became familiar with each other and
friendships sprouted.
武汉经典早餐 - 豆皮，开启了整场破冰活动。
Doupi- one of the most classical Wuhan breakfasts started
the whole icebreaking game.
破冰游戏
Icebreaking Games
展示自己的文化并了解其他文化是暑期学校
最重要的出发点之一。今年，学员们通过原创
Vlog, 向大家展示了中国、巴基斯坦、印度、伊
朗、尼日利亚以及坦桑尼亚等国文化。文化交流
让别人了解我们的同时，更让我们看到了世界文
化的各具特色而又紧密相连。
Cultural Exchange provides opportunities to introduce
and learn different cultures, and one of the most
important motivations behind the summer school. This
year, students provided original self-produced cultural
Vlogs . Through the Vlogs, we can see colorful local
cultures from China, Parkistan, India, Iran, Nigeria,
Algeria, and Tanzania.
文化交流晚会
Cultural Exchange Party
18 19

Part V
Teachers’ Remarks 教师寄语

教师寄语
Teachers’ Remarks
Part VI
Closing Ceremony 闭幕式
这是我在地球空间信息科学暑期学校任教的第三年，和过去一样，无可挑剔的组织和高水平的教学人员
给我留下了深刻印象。今年，我有幸向来自世界不同地区的约 40 名优秀学生进行教学，和去年一样，他们
对知识的渴望令我尤为难忘。在课程中，他们努力开发小项目，将在课堂上学到的理论和算法应用于具体问
题。虽然最终只有一个项目获得奖项，但其实所有的项目都具有很高的完成水准。希望我的课堂内容对学员
有所帮助，并希望学员们在个人和职业生涯中一切顺利。
This is the third year I have taught at the GeoInformatics Summer School and, as in previous years, I’ve been impressed
by the impeccable organization and the high-profile of the teaching staff. This year I had the fortune to teach to a group of
about 40 excellent students coming from different areas of the world and, as was the case last year, I was impressed by their
dedication and eagerness to learn. During the course they all worked hard to develop a small project where they could apply
the theory and algorithms learned in the class to a concrete problem. Eventually only one project has been awarded the
prize, and I congratulate the winning team for their achievement, but I was glad to see that all the projects presented were of
the highest standards. I do hope that the things that I taught in my class will be useful, and I would like to wish the students
all the best for their personal and professional careers.
Prof. Marcello Pelillo
”
我有幸再次来到由测绘遥感信息工程国家重点实验室主办地地球空间信息科学国际暑期学校授课。与来
自世界各地的不同背景、积极性高、勤奋的学生一起度过一段精彩的时光。学生们高质量的小组项目再次给
我留下了深刻的印象。在我看来，地球空间信息科学国际暑期学校体现了国际化教育、交流和合作的好处。
I was privileged to lecture again at the 11th International GeoInformatics Summer School, hosted by the prestigious State
Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing at Wuhan University. I had a
wonderful experience knowing and engaging with the diverse, highly motivated, and industrious students from all over
the world, and I was once again impressed by the students’ high-quality group projects. The International GeoInformatics
Summer School, from my perspective, exemplifies the benefits of international education, exchange, and collaboration.
李振龙 Prof. Zhenlong Li
”
暑期学校是学习地理空间信息科学前沿知识的极佳选择。师生之间的互动让暑期学校充满活力，而我十
分荣幸成为其中的一员。期待学员们在未来把所学知识付诸实践。
LIESMARS’ summer school is a great place to learn new trends in geo-spatial information sciences. The interactions
between students and teachers bring the summer school to life and it was a great pleasure to be part of this exerience. I am
looking forward to see our students bringing the knowledge they gained into action in the future.
Prof. Timo Balz
”
22

Timo Balz 教授
主持闭幕式，回顾了此
次暑期学校的精彩瞬
间，并宣布优秀课程报
告奖。
Prof. Timo Balz hosted the
ceremony, reviewed the
whole summer school and
announced the Excellent
Participant Award.
中海达国际市场总监魏耀宗向大家
分享了广州中海达卫星导航技术股份有
限公司与实验室共同探索校企合作模
式，
深层次参与实验室人才培养的经历，
同时介绍了中海达近年来在 5G, 自动
驾驶、电力等行业的应用案例。
三门课程的优秀报告奖学员做课程总结报告，展示他们在暑期学校期间的学习成果。
The excellent participants from SSI, SSII and SSIII gave presentations about the courses, showing the
results of their learning in the courses.
紧张而充实的 7 天时间匆匆而去。大家不仅收获了地球空间信息
科学领域前沿知识，更收获了珍贵的友谊！明年见！
Time flies! Over seven days, students not only gained frontier knowledge,
but also harvested precious friendships. See you the next time!
Part VII
Appendix 附录
Stefan Wei,is the marketing director of Hi-Target International shared the talents cultivation cooperation
between LIESMARS and HI-TARGET and the application of the Hi-Target product in 5G, autonomous
driving, electric power, and other industries.
24

Ⅰ 优秀课程报告奖展示
Excellent Participant Award Works
Objective
本研究的目的是通过无人机 (Unmanned Aerial Vehicle, UAV) 影像及时有效地提取地震影响地区的
房屋建筑破损情况。具体来说，拟建立一套完整的无人机在线实时测绘和地震灾情监测与评估系统。其中最
主要的是，实现无人机影像上的高精度、高速度的房屋提取算法。
The research aims to use unmanned aerial vehicle (UAV) images to timely and effectively extract the damage situation of
buildings in earthquake-affected areas.Specifically, we are going to establish a complete online real-time UAV surveying and
mapping and earthquake disaster monitoring and evaluation system. It is most important to realize high-precision and high-
speed house extraction algorithms on UAV images.
Methodology
DirectMap——无人机在线实时测绘及应急灾害地震灾
害监测评估系统
DirectMap——UAV online real-time mapping and
Earthquake disaster monitoring and evaluation
system for emergency disasters
Presented by: Yilin Lin, Yang Liu, Ziyi Zhang, RANA WAQAR ASLAM, BURHAN KHALID
1
本系统的总体思路为，首先在移动终端进行无人机智能航线规划与飞行控制，利用无人机和卫星数据获
取灾区影像与高精度 GNSS 数据，同时通过机载处理器实时生成灾区测绘产品，通过深度学习在该产品上
进行信息提取和分析，从而快速形成灾情专题地图和灾害损失评估报告，以指导科学决策。
The general idea of this system is as below. Firstly, intelligent UAV route planning and flight control are carried out at the
mobile terminal, and then we use UAV to obtain images of disaster areas and get high-precision GNSS data, and at the
same time, a disaster area mapping product is generated in real-time by the on-board processor, and deep learning is used
to the information extraction, then analysis is carried out on this product to quickly form disaster thematic maps and disaster
damage assessment reports to guide scientific decision-making.
针对房屋提取算法，首先利用 Labelme 对 UAV 影像进行标注与分组。基于标注好的数据，进行模型
训练，模型包括 Mask R-CNN, Detectron2, YOLOv4, YOLOv5。再基于模型精度与效率选择最优模型用
于震后破损房屋提取。
For the house extraction algorithm, first we use Labelme to label UAV images and divide them to train data and test data.
With the labeled data, model training is carried out. Models include Mask R-CNN, Detectron2, YOLOv4, YOLOv5. Based
on the accuracy and efficiency of the model, the optimal model is selected for the extraction of damaged houses after the
earthquake.
Results
经过模型训练，得到了 4 种不同模型的提取结果，如图 4 所示。经对比，YOLOv5 的整体效果最好。
After model training, four different model extraction results are obtained, as shown in Fig.4. By comparison, YOLOv5 has
the best overall effect.
Fig.1 Schematic diagram of the research purpose (UAV Image-->Damaged House-->Damage Degree)
Fig.2 The flow chart of the research
Fig.3 The flow chart of the house extraction algorithms
Fig.4 The extraction result of four models
26 27

具体来说，Mask-RCNN 算法提取房屋存在着提取边缘不够准确、白色屋顶误差较大、容易出现房屋
粘连等不足现象。Detectron2 应用于大的卫星遥感影像时训练速度较慢。
Specifically, Mask-RCNN algorithm extracts houses with some shortcomings, such as insufficient accuracy in extracting
edges, large errors in white roofs, and easy house adhesion and other shortcomings. Besides, the training speed of
Detectron2 is slow when applied to large satellite remote sensing images.
所以，本团队倾向于选择 YOLOv4、YOLOv5 算法。其中，YOLOv5 算法对单一图片的推理时间可以
达到 140FPS，且其最小的模型大小仅有 20M，很适合在无人机上部署。
Therefore, our team tends to choose YOLOv4 and YOLOv5 algorithms. Furthermore, the YOLOv5 algorithm can reach 140
frames per second inference time for a single image, and its smallest model size is only 20 mega byte, which is very suitable
for deployment on UAVs.
Conclusion
1. 模型选择
经过多个模型进行对比，YOLOv5 的性能最优，故选择该模型进行破损房屋探测。
2. 未来展望
由于暑期学校时间有限，我们仍有许多工作尚未完成。接下来，针对该项目，我们将从以下方面继续探
索。我们希望改进 YOLOV5 模型，使其识别在线测绘图像的速度和准确度都得以提升，我们也希望逐步完
善系统性能，推出房屋损毁分级、损毁道路提取等功能，以便快速指导救援。
1. Model Selection
After comparison, the performance of YOLOv5 is the best, so this model is selected to detect damaged houses.
2. Future outlook
Due to the limited time of summer school, we still have a lot of work unfinished. Next, for this project, we will continue to
explore the following aspects. We hope to improve the YOLOV5 model so that its speed and accuracy in recognizing online
mapping images can be improved, and we also hope to gradually improve the performance of the system and introduce
features such as house damage classification and damage road extraction to quickly guide rescue.
Fig.5 The result of YOLOv5
Abstract—Christmas is celebrated worldwide, especially in Christian countries, such as U.S, U.K, Germany, etc. But this
tradition was interrupt by the COVID-19 in 2020. Shopping, travelling, and many other commercial and recreational activities
were greatly influenced by the pandemic. In this report, we focus on the human mobility in Christmas Holiday under
COVID-19, using geotagged Tweets to visualize and analyze this trend.
Index Terms—human mobility, COVID-19, twitter
摘要：圣诞节在全世界范围内被广泛庆祝，尤其是基督教国家，如美国、英国、德国等。但这一传统在
2020 年被新冠疫情打破。购物、旅游等诸多商业活动和娱乐活动都受到了影响。在这篇报告中，我们重点
聚焦人口流动，使用带有地理标签的推特信息，对这一趋势进行可视化和分析。
关键字：人口流动，新冠肺炎，推特
I. INTRODUCTION
Christmas holiday is celebrated by Christians and non-Christians on December 25, in many different traditions and ways.
Because of its multi-cultural nature, such customs are similar globally. During this holiday, most of activities such as visiting
relatives, travelling for leisure, going to churches, shopping for food, and exchanging gifts are regarded as family traditions
and cultural heritages. But it is comprehensively interrupted by COVID-19 in different aspects.
This article provides a timely overview of human mobility patterns observed during Christmas Holiday in the United States
of America under COVID-19, using social sensing data, namely, geotagged Tweets to: (i) determine the mobility patterns in
US before and during Christmas holiday in 2019 and 2020; (ii) examine the population inflow and outflow in each state over
the Christmas period; and (iii) analyze the relationship between the human mobility extracted from Twitter data and the real
huaman mobility.
The report is organized as follows. Section II briefly reviews several case studies about COVID-19 and its influence on
human mobility. Section III explains the method and data source we used. Section IV visualizes the human mobility before
and during Christmas Holiday in 2019 and 2020 respectively. Section V is conclusion.
在每年 12 月 25 日，全球的基督徒与非基督徒都会以不同的方式庆祝圣诞节。因其多文化融合的本质，
这些风俗习惯都是相似的。在这个节日里，诸如走亲访友、度假旅游、教堂祷告、购物娱乐、交换礼物等活
动都被视为家庭传统甚至文化传统。但这一传统被新冠疫情打破。
这篇文章非常及时地利用社群感知数据，也就是带有地理标签的推特信息数据，回顾了疫情之下的美国
在圣诞假期的人口流动趋势，实现：1）探索 2019 与 2020 年圣诞节前后的人口流动模式；2）考察每个州
在圣诞节期间的人口流入与流出；3）分析由推特数据得到的人口流动与真实人口流动之间的关系。
这篇报告的结构如下：第二部分回顾了几个关于新冠疫情及其对人口流动影响的案例；第三部分介绍了
研究方法与数据来源；第四部分可视化分析了人口流动的变化；第五部分为总结。
Christmas under COVID-19: Human
Mobility Analysis Based on Geotagged
Twitter Messages
疫情下的圣诞假期：基于地理标签推特信息的人
口流动分析
Presented by: Chongyang Zhang, Neema Sumari, Abdennour ZEKRI, Freeman Ali, Md Mostafizur Rahman
2
28 29

II. LITERATURE REVIEW
A. Influence of COVID-19 on Mobility-case studies
The COVID-19 pandemic has spread rapidly around the world and affected many countries since 2019 [1]. Some studies
show that the virus can be conducted by droplet transmission, touching base, and breathing transmission, which has high
infective speed of transmission[2].
Spatial mapping gives us a way to understand and predict human movement, helping government better distribute
resources (e.g. services, infrastructures) [3]. Geographic information systems (GIS) and social sensing data techniques
have made it possible to develop models which measure the influence of COVID-19 on human mobility worldwide[1], [4].
These methods have also been used in other study fields, such as combining remote sensing data with social media data
“Twitter” to determine urban sprawls[5]; monitoring and assessing post-disaster tourism recovery using geotagged social
media data[6] and so on.
2019 年以来，新冠疫情在全球范围内迅速传播，部分研究表明新冠病毒可以通过飞沫传染、接触传染、
呼吸传染，有着极高的传染率。
空间地图技术帮助我们理解并预测人口流动，进而帮助政府更好地分配抗疫物资。地理信息系统与社群
感知技术可以帮助我们分析新冠疫情对全球范围内人口流动情况产生的影响。这些技术同样被应用到很多其
他领域，如：通过结合遥感数据与社群感知数据分析城市扩张；监测灾后旅游业恢复等。
III. METHODOLOGY AND DATA SOURCE
A. Methodology
Twitter users can add geotag to their Tweets. And if a user sends a geotagged Tweet at time i at place i, after moving to time
j at place j, he or she sends another geotagged Tweet. We can calculate this user’s travel distance, human mobility, travel
frequency, etc. With geospatial big data computing cluster, we can process large data stream from Twitter, then calculate the
human mobility of twitter users and predict the real human mobility worldwide.
推特用户可以在消息中添加地理标签，如果一个推特用户在 time i 发送了一条带有位置为 place i 的推特消息，
并在 time j 发送了一条带有位置为 place j 的推特消息。根据地理标签我们就可以计算这个用户的旅行距离、
旅行频率等。在地理大数据计算云平台上，我们可以处理来自推特的大量数据流，并计算推特用户的流动情
况，最终预测全球整体的人口流动情况。
B. Data Source
For data source, we used the website developed by Prof. Li and his team as the data source of this project. We downloaded
data in four periods: 10 days’ human mobility data before and after Christmas in 2019 and 2020, to be specific, is from
December 12 to 21, December 22 to 31, of the year 2019, and from December 12 to 21 and December 22 to 31 of the year
2020. We have two data sources: Safegraph and Twitter. The quality of Safegraph’s data is better and the data is more
close to the real population movement.
我们以李教授及其团队建立的网站作为数据来源，下载了 2019 年与 2020 年圣诞假期前后各 10 天，总
计四段时间的数据。具体时间段为 2019 年 12 月 12 日到 12 月 21 日， 2019 年 12 月 22 日到 12 月 31 日，
2020 年 12 月 12 日到 12 月 21 日，2020 年 12 月 22 日到 12 月 31 日。
IV. RESULTS AND ANALYSIS
A. Human Mobility in the U.S.
In Figure 1 , we cannot see any pattern from 1-(a) to 1-(d). But the last four graphs indicate that the human mobility among
Hawaii, Alaska and the continent of America drops sharply in 2020. After consulting to Prof. Li, we know that the data is poor
and has been removed artificially.
从图 1-(a) 到图 1-(d) 我们很难发现图表的规律。但根据推特数据计算得到的四幅图中，我们可以看到
夏威夷与阿拉斯加同美洲大陆的人口流动在 2020 年急剧下降。咨询李教授之后我们得知由于这部分数据质
量较差，已经被人为剔除了。
B. In-state and Inter-state Human Mobility
Then we calculate the amount of in-state and inter-state human mobility. The in-state human mobility during Christmas is
lower than that before Christmas, but the inter-state mobility rises. That is reasonable because in Christmas people all travel
far away to visit friends or go on holiday. What’s more, the mobility both in-state and inter-state, in 2019 is higher than that
in 2020 because of COVID-19. But twitter data shows a different pattern about the inter-state mobility. The human mobility
remains nearly the same before and after Christmas Holiday. The mobility calculated according to twitter messages may not
be so reliable all the time, see Table 1 below.
之后我们计算了美国各州内部的人口流动与各州之间的人口流动。圣诞节前的州内人口流动比圣诞节后
的州内人口流动高，而州际人口流动与之相反。在圣诞假期人们似乎更倾向于长途旅行去拜访亲人、朋友，
或度假。此外，因为疫情，不论是州内还是州际，2020 年人口流动均低于 2019 年同期。反观推特数据，
见图 2-(b) 与图 2-(d)。圣诞节前后人口流动差别并不明显。可见推特数据计算得到的人口流动情况和真实
情况存在一定出入。
C. Inflow and Outflow Population in Each State
Next is the inflow and outflow of population in each state， as is shown is Figure 3. The darker color indicates higher
mobility. In general, in 2020, the color is lighter than that in 2019. Here we listed the most popular state in Christmas Holiday
in Table 2. And in 2019 and 2020 Florida remains the most popular state. It seems that American people are eager to enjoy
the beach and sunshine in Florida when their states are very cold.
之后我们计算了每个州的流入人口和流出人口，如图 3 所示。颜色越深代表人口流动越大。总体而言
2020 人口流动量小于 2019。我们在表 2 中列出了每年最受欢迎的州。可以看到佛罗里达蝉联两年。美国人
似乎很喜欢在寒冷的冬季去佛罗里达享受阳光和沙滩。
Figure 1: Human mobility before and after Christmas Holiday in 2019 and 2020 according to Safegraph and Twitter
(a) Human mobility in US 12.12 – 12.21 2019 according to Safegraph. (b) Human mobility in US 12.22 – 12.31 2019 according to Safegraph. (c) Human mobility in US 12.12 –
12.21 2020 according to Safegraph. (d) Human mobility in US 12.22 – 12.31 2020 according to Safegraph. (e) Human mobility in US 12.12 – 12.21 2019 according to Twitter. (f)
Human mobility in US 12.22 – 12.31 2019 according to Twitter. (g) Human mobility in US 12.12 – 12.21 2020 according to Twitter. (h) Human mobility in US 12.22 – 12.31 2020
according to Twitter.
Figure 2: In-state and inter-state human mobility before and after Christmas Holiday in 2019 and 2020 according to Safegraph and Twitter
(a) In-state human mobility in US according to Safegraph. (b) Inter-state human mobility in US according to Safegraph. (c) In-state human mobility in US according to Twitter. (d)
Inter-state human mobility in US according to Twitter.
Table 1: IN-STATE AND INTER-STATE HUMAN MOBILITY BEFORE AND AFTER CHRISTMAS IN 2019 AND 2020
30 31

D. Inflow Population in Tourism Cities
Then let’s see the inflow population of Florida in detail. There are many visitors going to Florida in summer and Christmas
Holiday, which is golden time for tourism. But COVID-19, the number of visitors drops sharply. In Hawaii, it is the same, even
worse. After March, visitors disappeared, Figure 4 and Figure 5.
之后我们详细统计了佛罗里达每日的人口流入与流出。
可以看到夏季与圣诞假期是佛罗里达的旅游旺季。
但因为新冠疫情，佛罗里达旅游季的人口流入锐减。夏威夷也面临同样的情况，在美国三月颁布禁足令后，
流入人口急剧下降。
E. Regression Analysis of Twitter data and Safegraph data
At last, we use regression analysis to explore the relationship between real human mobility and Twitter data (here we use
Safegraph data as true value). In Figure 6, the xaxis represents twitter data, and y-axis represents safegraph data. We use
a line to fit the data points and the significance factor is 0.8544. When we clear out the four points which seems abnormal,
and repeat the regression, we get a better result, Figure 7. Significance factor rises to 0.9140. Using this line, we can predict
the real human mobility according to twitter data.
最后，我们使用回归分析来探索推特数据与真实人口流动值之间的关系（这里使用 Safegraph 数据近
似真实人口流动值）。在图 6 中 X 轴代表推特数据，Y 轴代表 Safegraph 数据，我们使用一次函数拟合数
据点，显著因子为 0.8544，剔除部分异常点后拟合结果更好，显著因子为 0.9140。我们可以根据推特数据
来预测真实人口流动。
Figure 3: Inflow and outflow of population during Christmas Holiday in 2019 and 2020 according to Safegraph and Twitter
(a) Inflow population during Christmas Holiday in 2019 according to Safegraph. (b) Outflow population during Christmas Holiday in 2019 according to
Safegraph. (c) Inflow population during Christmas Holiday in 2020 according to Safegraph. (d) Outflow population during Christmas Holiday in 2020 according to Safegraph. (e)
Inflow population during Christmas Holiday in 2019 according to Twitter. (f) Outflow population during Christmas Holiday in 2019 according
to Twitter. (g) Outflow population during Christmas Holiday in 2020 according to Twitter. (h) Inflow population during Christmas Holiday in 2020 according to Twitter.
Table 2: MOST POPULAR STATES IN CHRISTMAS HOLIDAY
Figure 4: Daily inflow and outflow of population of Florida in 2019 and 2020
(a) Daily inflow and outflow of population of Florida in 2019. (b) Daily inflow and outflow
of population of Florida in 2020.
Figure 5: Daily inflow and outflow of population of Hawaii in 2019 and 2020 (a) Daily
inflow and outflow of population of Hawaii in 2019. (b) Daily inflow and outflow of
population of Hawaii in 2020.
Figure 6: Regression between Twitter data and Safegraph data Figure 7: Regression between Twitter data and Safegraph data after
clearing out the abnormal points
V. CONCLUSION
A. Conclusion
1.COVID-19 greatly influences the human mobility both instate and inter-state on Christmas Holiday in US.
2.COVID-19 greatly influences the inflow population in tourist attractions, thus affecting tourism in US.
3.Human mobility extracted from Twitter messages may not be reliable all the time, but it can be modelled and we can use it
to predict real human mobility.
新冠疫情显著影响了美国圣诞假期内的州内与州际人口流动。
新冠疫情极大影响了旅游城市的人口流入，进而影响旅游业发展。
从推特数据提取人口流动值存在较大偏差，但我们可以对其进行建模从而预测真实人口流动值。
B. Future Work
1.Explore the relationship between the Twitter based human mobility and real human mobility using deep learning method.
2.Try to extract data from raw Twitter messages and analyze the relationship between text, pictures and location.
我们将使用深度学习等方法进一步探索推特数据和真实人口流动值之间的关系。
我们将尝试从原始推特数据中提取文字、图片与位置，进一步分析他们之间的关系。
APPENDIX
We have upload our project onto GitHub. You can visit https://github.com/ChongyangZhang1027/Humany_Mobility_COVID19_IGSS and view the raw data, source code and
results.
我们将整个项目上传 GitHub，您可以访问链接来查看原始数据、程序源码以及结果展示。
REFERENCES
[1] N. Medimorec, A. Enriquez, E. Hosek, and K. Peet, “Impacts of COVID-19 on Mobility on urban mobility: Preliminary analysis of regional trends on urban mobility,” no.
May, pp. 1–23, 2020.
[2] M. S. Hosseini and A. Masterangelo Gittler, “Factors Influencing Human Mobility during the COVID-19 Pandemic in Selected Countries of Europe and North America,”
Proc. - 2020 IEEE Int. Conf. Big Data, Big Data 2020, pp. 4866–4872, 2020, doi: 10.1109/BigData50022.2020.9377932.
[3] N. Xia, L. Cheng, and M. C. Li, “Mapping urban areas using a combination of remote sensing and geolocation data,” Remote Sens., vol. 11, no. 12, Jun. 2019, doi:
10.3390/rs11121470.
[4] J. Zhang, B. Feng, Y. Wu, P. Xu, R. Ke, and N. Dong, “The effect of human mobility and control measures on traffic safety during COVID-19 pandemic,” PLoS One, vol.
16, no. 3 March 2021, pp. 1– 9, 2021, doi: 10.1371/journal.pone.0243263.
[5] Z. Shao, N. S. Sumari, A. Portnov, F. Ujoh, W. Musakwa, and P. J.
Mandela, “Urban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data,” Geo-Spatial Inf. Sci., vol. 00, no. 00, pp.
1–15, 2020, doi: 10.1080/10095020.2020.1787800.
32 33

Overview of Synthetic Aperture Radar and its
Applications
Presented by: Uqba Ramzan[1]*, Rida Fatima[1], Muhammad Ali[1], Zohre Hashemi[2], Narangua Batdorj[3]
[1] State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing; Wuhan University; China
[2] School of Surveying and Geospatial Engineering; Tehran University; Iran
[3] Centre of Environmental Sciences; Eötvös Loránd University; Hungary
3
Abstract
The basics of SAR (Synthetic Aperture Radar) technique, data acquired by satellite and applications of SAR by usage of
PS-INSAR technique is shown in this project. After the launch of Sentinel 1A and 1B in 2014 and 2016, respectively we get
freely available data. This technology uses active sensors and can synthetically produce higher resolution images even in
the presence of clouds or at night. The InSAR technique have also unique application of monitoring ground deformation
in geothermal fields. Both optical and radar images can be utilized for geological and mineral mapping as well as surface
deformation. Two-year data of Sentinel-1 was acquired and processed to evaluate the depth analysis, afterward 2D and 3D
maps were also generated for better interpretation of the results.
1. Introduction
Synthetic aperture radar is a technique of acquiring images using radio waves. The satellite sends microwave pulses
to Earth they bounces back to the satellite in the form of echoes. The radio waves used in SAR typically range from
approximately 3 cm up to a few meters in wavelength, which is much longer than the wavelength of visible light, used in
making optical images [1]. These wavelengths are described below in Figure 1:
Polarization refers to the orientation of the radar wave from the SAR antenna. Both electric and magnetic fields are
perpendicular but the electric field determines the direction of polarization of the wave. Synthetic Aperture Radar uses an
antenna that can transmit in either the horizontal (H) or vertical (V) polarization. [3]
For single-polarization, these are typical transmit and receive pairs.
HH – for horizontal transmit and horizontal receive
VV – for vertical transmit and vertical receive
HV – for horizontal transmit and vertical receive
VH – for vertical transmit and horizontal receive
1.1 Applications of SAR
InSAR can be a useful tool at geothermal fields: track regional and localized fluid movements, to discriminate between
natural or anthropogenic deformation, to better understand fluid loss, delay in reservoir replenishment, to anticipate any
critical deformation stage before the damage occurs. [4]
Pressure changes in the subsurface can induce surface deformation [5] for this reason fluid extraction is likely to cause
subsidence and fluid injection usually causes uplift any other fluid flows might also produce a surface deformation signature.
In Radar, these wavelengths are grouped into bands. X-Band monitor the top of the forest canopy, C-band monitor the forest
midlevel (under canopy) leaves and branches, and the L-band monitor the different level of the forest stand and can get
deeper into forest including trunks as shown in figure. 4(b) [6]. Actually, longer wavelengths can also penetrate clouds better
and even the ground. For example, L-band (~24 cm) radar has longer wavelengths than C-band (~6 cm) and X-band (~3cm).
As shown in figure 4(a) [3].
2. Methodology
2.1 Data Acquiring
The two years Sentinel 1-A data from July 27, 2017 to July 29, 2019 was acquired. Sentinel-1A data was assimilated from
ASF data search, which is further used for PS-InSAR analysis in SARPROZ software.
The window of SARPROZ software is shown in the figure 6 for the time series module. Ascending data was utilized for our
time series deformation analysis and exported the results in Comma Separated Values (.CSV) file format, which is further
processed in ArcMap Software.
The graphical representation of the .csv data is shown in the figure 7. The ups and downs from September 01, 2017 to
Figure 1: Comparison of wavelength, frequency, and energy for the electromagnetic spectrum. [2]
Figure 2: Both electric and magnetic lines of force are at right angles to each other. [3]
Figure 3: Pressure changes in the subsurface can induce surface deformation [4]
Figure 4: (a) SAR penetrates through clouds; (b) Demonstration of X,C,L-Bands by taking forest as Example [7].
34 35

July 16, 2018 clearly demonstrates the changes in the study area. The highest peak comes at February 16, 2018 and the
maximum dip came at October 31,2017 as shown in the orange box in figure 7.
Moreover, the data was imported in ArcMap by using its longitude and latitude for depth analysis. For creating 2D map
in ArcMap, Base map was added with its legend showing the intensity of points with colors. Figure 8 also shows the
topographic base map from the ArcGIS database.
Surfer Software was used for creating 3D maps. The red region show the depth analysis in the 3D image. The 3-D
visualization could also be helpful in better interpretation of the study area with highlighted region showing depth,
Figure 5: Sentinel-1A data downloaded from ASF data search vertex.
deformation and subsidence occurred.
Conclusion
The basics of Synthetic Aperture Radar with its application and processing was explained in this project. The application in
geothermal fields of SAR was also enlightened. Moreover, time series data of two-years (July 27, 2017 to July 29, 2019) of
Sentinel-1A was used for PS-INSAR processing as an case study for this project. The graphs, 2D and 3D maps were gener-
ated by using different software. The whole project was also explained through the video whose link is attached below:
Video Link: https://www.youtube.com/watch?v=9DrWjShAvT4
Figure 8: PS-InSAR data processed in ArcMap
Figure 6: Processed SAR data exported in csv. file format.
Figure 7: X-Y graph created in Excel from SAR processed data to show depth analysis
Figure 9: SAR data processed for Depth analysis in Surfer Software
REFERENCES
[1] https://www.capellaspace.com/sar-101-an-introduction-to-synthetic-aperture-radar/
[2] Imagine the Universe – NASA, https://imagine.gsfc.nasa.gov/
[3] https://gisgeography.com/synthetic-aperture-radar-examples/
[4] Earth Observation Open Science by ESA- http://eoopenscience.esa.int/
[5] Derek Elsworth, Kyungjae Im: “Surface and Subsurface Geodesy Combined with Active Borehole Experimentation for the Advanced Characterization of Egs Reservoirs”
[6] ICEYE: https://www.iceye.com
[7] http://www.researchgae.net/figure/Wavelength-illustration-of-multi-frequency-radar-through-vegetation Source-fig2-330465403
36 37

Ⅱ 文化交流奖优秀作品
Cultural Promoter Award works
神奇香港
Magic of Hongkong
by Zherong WU
马来西亚文化
Malaysian Cultures
by CHAN FONG CHI
坦桑尼亚日常生活
Daily Routine after
the Work in Tanzania
by Calvin Samwel Swai
中巴友谊
Chinese-Parkistan
Group Culture Vlog
by Ahmad Muhamad Nasar;
Sackdavong MANGKHASEUM;
Xiong Qiang;
WANG Zhikai;
Zhiyuan Chen
尼日利亚约鲁巴文化
Yoruba Culture in Nigeria
by Adewale Adekunle
38 39

Ⅲ 学员感想
Students' Impressions
LIESMARS laboratory in Wuhan university is ranked among the top laboratories in the world in term of remote
sensing. My experience in 2021 Online Summer School was amazing and a unique one.
Thanks for all the professors and teachers in IGSS 2021, it was a wonderful experience.
I participated before also in 2017 and 2018 LIESMARS summer school. We visited Hubei Province Museum,
and we took a campus tour. It was a fantastic experience given for us from Wuhan university by LIESMERS
laboratory. Thanks Wuhan for everything!
The following pictures summarizes my experience in the previous LIESMARS summer schools in 2017 and 2018.
Contributions in IGSS 2021
I attended IGSS for the first time and participated in SS-II Machine learning course. I found it very useful in term
of knowledge and research techniques. I also met, people from diverse culture and backgrounds. I encourage
everyone to participate in coming summer schools held at LIESMARS.
1.Participated in Project Presentation in group for Machine Learning Course
2.Prepared Vlog Video and participated in Cultural Vlog competition
3.Recorded Video of my summer school experience for teacher.
4.Recorded video of Machine learning lecture
5.Made a Vlog for my culture representation
6.Active student
7.Attended all the meetings from 23rd August to 31st.
Contact information:
Email: mnasarahmad@whu.edu.cn
WeChat ID: mnasarahmad
WhatsApp: +923224919552
Mainland: +8615623157709
Mobile: +923334919552
Ahmad, Muhammad Nasar
Ph.D. Photogrammetry & Remote Sensing.
State Key Laboratory of Information Engineering in Surveying, Mapping and
Remote Sensing, Wuhan University,
I received my Master degree in Earth System Sciences from Chinese University
of Hong Kong, Hong Kong. Currently, I am a PhD scholar at LIESMARS.
2021 LIESMARS GEOINFORMATICS
SUMMER SCHOOL
Name: Abdennour ZEKRI
Country: Algeria
E-mail: abdennour.zekri@yahoo.fr; azekri@cds.asal.dz
I graduated recently from Shanghai Jiao Tong University as a
PhD student in Computer Science and Technology.
40 41

PARTICIPATION EXPERIENCE REPORT
ON INTERNATIONAL GEOINFORMATICS
SUMMER SCHOOL, 2021
ADAMU BALA
B.Eng. Geomatics Engineering, (2009, ABU Zaria); PGD Education, (2014, NTI, Kaduna);
MSc Geomatics, (2018, ABU Zaria); PGD Mining Engineering (2020, NIMG, Jos);
Certificate in GIS and Geovisualization (2021, ITC Faculty, Enschede)
1.0 PARTICIPANT’S BIODATA AND CONTACT
INFORMATION
I am Mr. Adamu Bala, a Nigerian. My contact address is
the Department of Geomatics, Faculty of Environmental
Design, Ahmadu Bello University, Samaru Campus,
Zaria, Kaduna State, Nigeria and I can be reached
through these telephone numbers: +2348065651016;
+2347080269158 and E-mail Ids: abala@abu.edu.ng
and adamubala09@gmail.com. I am a prospective PhD
candidate and also work for Ahmadu Bello University,
Zaria, Nigeria as a young Lecturer in the Geomatics
Department of the University. I have attended and fully
participated at numerous national and international
conferences; and I have authored and published
peer reviewed research papers at several local and
international journals. Professionally, I am Registered/
Licensed as a Surveyor with the Surveyors Council of
Nigeria and a member of some professional bodies
such as the Pan-African Scientific Research Council,
FIG Young Surveyors Network (YSN), Nigerian
Institution of Surveyors (NIS), National Association of
Surveying & Geoinformatics Lecturers (NASGL), etc. I
won FIG Foundation grant and OKP Netherlands short
course scholarships this year 2021.
Survey Field School with A.B.U. Geomatics Students Using Hi-Target V90 GNSS
2.0 BRIEF INTRODUCTION ABOUT THE 2021
SUMMER SCHOOL
This summer school titled “International Geoinformatics
Summer School ( IGSS)” is organized annually by
the famous State Key Laboratory of Information
Engineering in Surveying, Mapping and Remote
Sensing (LIESMARS) of the prestigious Wuhan
University, since 2011. The aim of the summer school
training is to share knowledge, skills and experience
relating to surveying profession among the participants
who are largely young students researchers and
professionals in the geospatial science disciplines.
In addition, this training provided for both social
and technical interactions amongst young students
researchers and professionals from different countries
and continents at large. It was also a platform to share
and learn different cultures, make new friends and win
different awards.
The theme of this year 2021 training is on disaster
mitigation and management, which was taught in three
different courses simultaneously. The choice of the
topics was influenced by the fact that geomatics and
geospatial science are essential for early detection
and effective management of natural and manmade
disasters in all ramifications.
3.0 COURSE CONTENT
In this summer school three (3) different courses were
taught simultaneously by competent and excellent
resources persons. These topics are:
SSI: Multi-temporal SAR Interferometry for Disaster
Mitigation by Prof. Timo Balz; Prof. Mingsheng Liao
and Prof. Lu Zhang.
Lecture Day 1: Introduction to Synthetic Aperture Radar
Lecture Day 2: Surface motion estimation with SAR
Lecture Day 3: Advanced InSAR processing methods
Lecture Day 4: Permanent & Distributed Scatterer
Interferometry
Lecture Day 5: InSAR for monitoring landslides
SSII: Machine Learning; and
SSII: Machine Learning by Prof. Marcello Pelillo
Lecture Day 1: Introduction to machine learning
Lecture Day 2: Neural networks and deep learning
Lecture Day 3: Support vector machines
Lecture Day 4: Graph-based clustering
Lecture Day 5: Selected computer vision applications
SSIII: Social Sensing, Geospatial Big Data Computing,
and Disaster Management by Prof. ZhenLong Li
Lecture Day 1: Introduction to social sensing and big
data computing for disaster management
Lecture Day 2: Geospatial big data and computing
techniques
Lecture Day 3: Social media (Twitter) data collection
and analytics with Python and Hadoop
Lecture Day 4: Web mapping of social media data with
JavaScript and Leaflet: introduction and basics.
Lecture Day 5: Web mapping of social media data with
JavaScript and Leaflet: trajectory mapping.
The summer school topics also included academic
research reports, project presentation competitions,
cultural vlog and ice breaks. The 9-days summer
school training commenced on 23rd November through
Friday, 31st August, 2021.
4.0 SCHEDULE OF EVENTS
Since I followed SSI: SSI: Multi-temporal SAR
Interferometry for Disaster Mitigation, most of my
reports will be based on activities/lectures conducted in
the SSI.
4.1 Day One Events of SSI Course, 23rd. August,
2021:
This is the opening day for the summer school,
therefore brief introduction about the aim and history
of the summer school was highlighted. Later on, Prof.
Timo Balz started the lecture by explaining the format
and specifications of videos for project presentation.
He mentioned the videos should talk on either on SAR
teaching and or application of SAR especially related to
participants country of origin/residence.
Prof. Timo then delivered to us lectures on introduction
and history of SAR Microwave Remote Sensing.
Some of the questions raised by the participants
were: Whether any software was going to be used
in the course of the work? What are differences of
polarization and direction? unlike other optical satellites
which are sunlight dependent for capturing optical
imagery, are Radar satellites Sunlight dependent or
can they work in night? Prof. Timo answered all the
questions to the satisfaction of the participants.
At the end of the day one lecture, a screenshot of all
the participants was taken as attached below:
4.2 Day Two Events of SSI Course, 24th. August,
2021:
Prof. Timo talked on the SAR image geometry and
Stereo SAR especially on the Radar reflection, Range
geometry, SAR modes, speckles statistics, Temporal
multi looking, microwave penetration, offset tracking,
and also talked on TSX ST WUHAN 2015/02/14
experiment on top of his office building. 1st experiment
included GPS measurements as ground truth, no
correction for TSX, very high precision in azimuth, etc.
Some of the questions raised to Prof. during day 2
lecture were: (i) whether a software is needed for direct
practice of what was taught? (ii) more explanation
about corner reflectors needed; (iii) whether resolutions
of all SAR modes are the same? Prof. answered all the
questions raised.
At the end of the day two lecture, a screenshot of all
the participants was taken as attached below:
4.3 Day Three Events of SSI Course, 25rd. August,
2021:
On day three, Prof. Timo talked on the InSAR geometry,
InSAR Overview, image registration, Resampling,
Flat Earth Removal, Height ambiguity, Error sources,
Coherence maps, Phase unwrapping, Spotlight InSAR
and SRTM amongst other interesting subjects. He also
talked on InSAR on Mount Song, TanDEM-X, TSX Las
Vegas, differential InSAR and concluded the day`s
lecture with InSAR Phase Components.
Some of the questions raised were: more explanation
about the decorrelation needed; whether or not there
will be practice session about input image, registration
and the final processed SAR image? Whether multi
looking causes have general view instead of going
to details? should we not prefer Coherence maps for
agriculture, forest and water change detection? Which
software is considered to be most suitable and stable
for the processing of InSAR data? Is the volumetric
coherence related to one pixel? what does the phase
STD indicate? How long is the best time difference of
1st and 2nd image to achieve good interferogram?
Some scrrenshots from day three lectures
4.4 Day Four Events of SSI Course, 26th. August,
2021:
Prof. Timo talked on D-InSAR, Displacement maps,
Along track interferometry, how to overcome the main
limit of InSAR using PS InSAR, PS InSAR techniques
and identification, PS values estimation, multi orbit PS-
InSAR, etc. Also, application of High resolution of PS
InSAR in subway development in Shanghai, and time
series reservoir monitoring, linear infrastructure, etc.
He gave examples of Tidal current measurement with
SRTM/X-SAR ATI and vehicle velocity estimation using
along track phase difference and azimuth displacement
in Autostrada del sole south of Rome.
Some questions asked were: whether the much
difference of velocities between ascending and
descending tracks is okay; whether it is okay if
descending track show uplifting and ascending tracks
show subsidence in the same area? Prof. Timo
responded to the questions raised.
At the end of the day four lecture, a screenshot of
some of the participants was taken as attached below:
4.5 Day Five Events of SSI Course 27th. August,
2021:
On day five, application of InSAR on disaster mitigation
were discussed. Prof. Mingsheng Liao and Prof. Lu
Zhang presented some of the excellent researches they
conducted and published in these areas of disaster
mitigation especially within China. Specifically, Prof. Lu
Zhang talked on applications of SAR Imaging Geodesy
in Landslide Investigation with examples such as: Case
1: Xinmo landslide disaster on 24 Jun 2017; Case 2:
Jiaju landslide in Danba, Sichuan; Case 3: Sunkoshi
landslide in Nepal, etc.
Some questions asked include: viability of InSAR and
GNSS for continental deformation motining especially
in coastal areas; whether InSAR if opensource and
data availability in Nigeria and Africa, etc. Prof.
42 43

Timo, Liao and Prof Lu responded to the questions
appropriately.
4.6 Day Six Events of Summer School, 29th.
August, 2021:
A combined class for the participants of all the three
courses was organized by LIESMARS where excellent
academic reports were presented by competent
resources persons. Prof. Daren Li, an alumnus of
University of Stuttgart, presented research outputs on
the topic “Geospatial Information Science in the era
of IOT”. Likewise, Prof. Zhenfeng Shao, an alumnus
of Wuhan University, discussed on “Urban Remote
Sensing for Impervious Surface Extraction and its
application on Sponge city”.
Prof. Zhenfeng Shao played a video recording with a
woman voice in the recording explaining the meaning
of 3D model in Chinese language.
A participant made an enquire about grant/fellowship
available at Wuhan University especially for students
from developing countries? Another participant asked
about possibility of sharing Wuhan/China satellite
images with other students outside Africa and other
countries; possility of future research collaboration with
Prof. Zhenfeng concerning QB + Lidar data fusion?
The discussions were fruitful as participants were
attentive and developed interest in some of the
research areas discussed.
4.7 Day Seven Events of SSI School, 30th. August,
2021:
On day seven, project presentations were made by
three group of SSI course, under the moderation/
chairmanship of Prof. Timo Balz.
Below are some of the screenshots by various
participants. Questions and observations were
attended by Prof. Timo. He commended all the three
groups of SSI for doing excellent projects but declined
to announce the winner until the closing day of the
event.
SSI Group 1 Project Presentation
5.0 ANNOUNCEMENT OF EXCELLENT PROJECT
WINNERS AND CLOSING CEREMONY, 31st.
AUGUST, 2021
Three winners emerged from the three courses offered
as shown in the figures below:
Above Figure shows a reasonable number of
participants at the closing ceremony.
There was a brief speech by Stefan, the Marketing
Director of Hi-Target about their products and company.
6.0 ICE BREAK
On 26th August, 2021, there was an ice break where
particiapnts shared dishes from their various countires
of origin and or residence. There was also pictures of
their various campuses shared to each other. Below
are some of the cuisines and university campuses
shared.
7.0 CULTURE VLOG COMPETITION
To promote understanding of participants culture,
submissions of short videos were made by fourteen (14)
participants. Each of the particpants, volunteers and
faculty members was given an option to choose best
three of the videos and the winners will be given an
award. Below are some screenshots from some culture
vlog submissions.
8.0 EXPERINCE GAINED AND CONCLUTION
All the aspects of the summer school course contents
were well treated extensively by resources persons
who are expert in courses allocated to them for the
lectures. The whole summer school was worthwhile
and time of refreshing and broadening the horizon on
the topics treated. Every detail of the subject matter
was treated down to earth for deeper understanding to
enhance a more appreciable and result-orientating in
geomatics. Sessions on application of SAR, Machine
learning and Social Sensing for disaster mitigation were
excellently taught. I also enjoyed the academic report
sessions. Culture vlog afforded me an opportunity
of different cultures, thereby appreciate everyone’s
cultural background. The summer school is useful to
build up individual experience and knowledge.
9.0 RECOMMENDATIONS
The summer school has not just afforded me a
wider experience on a personal ground, but has also
equipped me with the wherewithal required for effective
performance on trending research areas in geomatics
and geospatial science. I am therefore determined to
make good use of what I learnt to be more productive,
in all ramifications.
The following recommendations are hereby suggested
to improve subsequent summer schools.
●Standby list from the applicant should be made ready
to replace those who abandoned the course at the
beginning.
●More hands-on practicals should be incorporated
in the subsequent summer school courses to better
understand the theories taught.
●All lectures sessions should be recorded and
send together with lecture presentation slides to all
participants.
●Zoom hosts/admins should have total control of the
apps by muting the distracting participants.
●There seems to be misunderstanding of time
difference by some participants, therefore, time
conversion chart may be provided especially for
international participants to idea of the actual time of
the lectures.
●Information shared on WeChat platform can also
be send to the participants email addresses because
some participants had issues downloading the WeChat
app, therefore could not get latest info about the
summer school as it is when posted.
44 45

NAME: ADEWALE ADEKUNLE
CONTACT INFO:
TELEPHONE:+234 8149025938
adewaleadekunle439@gmail.com
Who am I?
My name is Adewale Adekunle. I am a student completing my Bachelor’s degree in Electronic and Electrical
Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria.
I was born in Abeokuta, Ogun state, Nigeria. I am from a family of five with three children and I’m the first child of my
parents.
I attended St.Birgitta Nursery and Primary School, Abeokuta, Ogun State, Nigeria for my elementary education
between September, 2003 and July, 2010 and Emmanuel college, Abeokuta, Nigeria for my junior high school
between September 2010 and July, 2013 and Police Secondary school Akure, Nigeria for my Senior High school,
from September, 2013 to July, 2016.
I have participated in different competitions representing my school, one of which includes Cowbell Mathematics
competition where varieties of schools across the country also competed.
I completed my senior high school education with good grades and awards of being the best student in subjects like
Mathematics, Further Mathematics, Physics and Geography along with good grades in WAEC 2016 examination.
I am currently a BSc Electronic and Electrical Engineering student at Obafemi Awolowo University, Nigeria. I
have a published book on Distance measurement for energy conservation, as I am currently working on my next
publications.
As a young boy, I grew up with much interest in the way computer systems function, programming computer
systems, a lover of mathematics and very hardworking. I’ve learnt to persist even in times of doubts. I gain
pleasure when I program to infer solutions to problems. I enjoy reading books relating to computer systems design,
inspirational books by experts in the industry, I enjoy games like Badminton and table tennis. Most of all I greatly
enjoy working in a team. Collaborative learning is one of my best forms of learning.
I’d be sharing some of my great experiences so far in the International Geoinformatics Summer School 2021.
I had a splendid time during the lectures anchored by Prof. Zhenlong Li, where he discussed some of the challenges
of social media big data computing for disaster management along with some feasible solutions.
Below are the lessons I learnt from the class:
The challenges or characteristics of big data include Big Volume, Big Velocity, Big Variety, and Big Veracity.
Some major solutions to these challenges are using a Hadoop based big data computing for Historical data, AI
based big data computing for real time data analysis for rapid response, visual textual fused CNN to identify disaster
related tweets.
M Y M E M O R A B L E
EXPERIENCES
MY EXPERIENCES AT THE INTERNATIONAL
GEOINFORMATICS SUMMER SCHOOL 2021
We were also taken through the applications of these solutions for big data computing and disaster management,
which includes rapid flood mapping, hurricane evacuation analysis.
We were also lectured social media big data for COVID-19 (public health disaster): Measuring human mobility,
where we made use of data mapping tools like Kepler.gl for our hands-on exercise, twitter data collection process
using the twitter API, JSON and GeoJSON, WebGIS, Mapping GeoJSON with Leaflet, Mapping Geotagged tweets
with leaflet.
A shot from one of our lectures where we made use of a mapping tool for human mobility analysis A shot from one of our zoom meetings
Relationship with colleagues
I personally got to interact with some of my colleagues at the Summer school through the WeChat platform. One
of my contributions was creating a general group chat for the SS III class (Social sensing, big data computing and
disaster management), where everyone of the participants who enrolled for the Social sensing class could have
assess to other participants.
We had an Ice-breaking session on the WeChat groups where I and fellow colleagues got to share ideas, traditions,
values from our various cultures, countries from all over the world. It was a great experience because I was
enlightened on what the world looks like at large.
Below are some of the images shared during the Ice-breaking cultural exchange session.
46 47

People I met during the summer school
Meet Siriwat Seechana, from Thailand. She is an
officer in the royal Thai Airforce, and currently a
geoinformatics and remote sensing student at the
Burapha University, Thailand and Wuhan University
China. She decided to enroll in this program because
she is interested in big data and needs to apply
techniques to her research.
Meet Muhammad Shariff Haider from Afghanistan.
He is currently a teaching assistant in the information
Technologies (IT) department with Masters in ICT from
Asian Institute of Technology, Thailand. He loves to
make new friends.
I also met Wu Yue from China. He just received his Bachelor’s degree in applied physics and is going to be a
postgraduate student of Hong Kong Polytechnic University in GIS. He enrolled in this program to prepare for his
study in the upcoming semester. He also loves to make new friends.
There were several others I met, some of which includes, Jiaqi (A teaching assistant), David Ayariga, Schneider
Djossou, David Mihigo, Neema, Yi Wang, Adamu Bala, Zheng Minxuan, Chan.
It is without doubt that the Geoinformatics Summer school was indeed a fascinating experience, I hope to see
more of this kind of program in the nearest future. Kudos to the organizers, sponsors, facilitators, instructors,
teaching assistants. Keep the good work up.
Regards,
Adewale Adekunle.
Meet Akshay Kumar from India. I got to know him
when we were regrouped, he became one of my group
members as a result. He is always willing to learn,
provide assistance where needed. I was surprised at
his name because there is an Indian star I love who
has that exact name, this made me want to interact
with him.
Hello world.
My name is Calvin Samwel Swai from the United
Republic of Tanzania. I am a graduate student from
Sokoine University of Agriculture (SUA). Currently, I
am an environmental and geospatial analyst as Aquila
Eyes Group. I hold a BSc in Environmental Science
and Management, from the Sokoine University of
Agriculture (SUA) in Morogoro, Tanzania.
It is my first time to hear about GeoInformatics Summer School from my supervisor Dr. Neema Sumari, the year
2021. I was very happy and excited about having an opportunity in learning different concepts in Geospatial
technology. After the application, I received and email says that, I was one of other few selected students to join an
online summer school.
Unfortunately, due to the epidemic, this year’s summer school was held online just like the one in the former year.
But this did not upset this platform from providing an exceptional course that covered phenomenon concepts and
technologies in GeoInformatics to the 143 students from 35 countries, in which I was so blessed to be one of them.
We are grateful for your efforts to prepare for this magnificent event.
In this summer school, I participated in the SS II Machine Learning group. Our classes began from 09:00 am to
12:00 pm local time (East Africa Time) from Aug 23 – 31, 2021. We had an amazing teacher on this group, Professor
Marcello Pelillo from the University of Venice, Italy who is also IAPR, IEEE, and AAIA fellow. It was easy to pay
attention to his teachings because of his methods, they are exceptional, and he taught us very well from the history
of machine learning and early works to the modern sophisticated algorithms and all in the most sophisticated way
of teaching. I didn’t know a thing about machine learning before this summer school but now my career will never
be the same again and I am looking forward to applying different Machine learning algorithms to Environmental
analysis and predictions to help and improve my community. Thanks to Professor Marcello Pelillo.
On 29th August, I and other students had an opportunity to attend the presentation of the academic report from the
two well-established and distinguished scientists in the field of GeoInformatics, Professor Deren Li and Professor
Zhenfeng Shao. Professor Li is very good he was awarded a Brock medal in 2020 as recognition for his contribution
to photogrammetry. We had the pleasure to attend his presentation on his work On Geospatial Information Science
in the era of IoT, it was original and informative. Professor Shao is just awesome, he has over 50 peer-reviewed
articles in international journals. During the academic presentation of this year’s summer school, he presented his
work on Urban Remote Sensing for the Impervious Surface Extraction and its Applications on Sponge City. The
works and presentations of these professors are inspiring and amazing, I am thankful for the chance to learn from
them.
Later towards the end of the course, we had arranged into groups of 4 to five students for the group projects. I was
on the group with four outstanding students Andaleeb Yaseen a Ph.D. candidate at Wuhan University, Nahed Osama
a Ph.D. candidate at Wuhan University, Li Shulin a Ph.D. candidate at Wuhan University, and XIAO Zhouxuan a
Ph.D. candidate at Sun Yat-sen University, China. We prepared our project on Flood Susceptibility Mapping through
Multi-Layer Perceptron. the combination was just perfect in this group number 4, I did enjoy everything with this
I’m Off to a Great Place
The Journey Has Just Began to the Geospatial Era
48 49

group, from our first meeting, during our virtual meetings for the preparation of the project to the presentation day on
30th August and we are grateful it went well. It feels amazing to work with them, and the connection is endearing.
Over this summer school, students were asked to take chance to participate in culture vogue. I had the best
experience during this time, it feels nice to share my culture with unfamiliar people and it feels better to learn
from the culture of other people from Nigeria, Pakistan, India, China, and others from other corners of the world. I
participated in this culture vogue presenting the norms of Tanzania men, how we spend time with our elders after
the working hour and before retreating to our families at night. I learned a lot from the writing of the script, recording,
and editing of my vlog. It is a very meaningful experience.
Lastly, I would like to thank the teacher, volunteers, and students for their cooperation. To everyone who participated
in the preparation of this amazing summer event, we are thankful for your efforts hope to meet you in the future.
Welcome to TANZANIA! Stay Blessed.
“We’re off to a great place, today is our day, our mountain is waiting, so we get on our way.”
Below are the pictures of the amazing moments I had during this summer school.
Emails for my application and acceptance to the 11th summer school My Group Members (number 03: Calvin Swai – me)
The closing academic reports presentation by Professor Deren Li
and Professor Zhenfeng Shao
Homework and group projects
Exposures and new friends on WhatsApp from the 11th summer school Exposures and new friends on WeChat from the 11th summer school.
Hi, greetings from Malaysia!! 你们好 , Assamualaikum Selamat sejahtera !!!
I am Chan Fong Chi from Malaysia. I am currently 23 years old and fresh graduated from Bachelor of Geomatics
Engineering under Universiti Teknologi Malaysia.
Aside from being a junior in this surveying world mainly in geoinformatics field, I am also aligning myself as one
of the advocates for SDGs, enhancing related skills in order to create a more sustainable environment by scientific
research, and societal endeavours.
I can be reached by following email address or phone number.
Email: fong1997@graduate.utm.my or fong.acad@gmail.com
Phone no. (Malaysia) : (+60)1110539434
Well, imagine that we could have some discussion about the group assignment face to face and exchange our
opinion about what we had learned in the lectures. How about we could enjoy every meal or China’s gourmet with
our teammates, or having a casual outing together after the lectures, we could introduce our background, our
country, and our cultures to every new friend that comes from different countries. How exciting it is?!
Yup, I know it is just an IMAGINATION. During our ice breaking session in WeChat, I imagined about we could have
done that if the IGSS event being held physically. Study is supposed to be fun, and I know IGSS 2021 is on the way
to create such a platform for us even under this global pandemic.
As every one of us is from different education background — there are Ph.D. candidates from GIS, research
assistants in machine learning and fresh graduates from Geology, etc. — and I am a fresh graduate from Geomatics
Engineering, but the professors are kind and thoughtful as they always emphasize it is ok to be confused and
encouraging us to ask questions, and they never failed to solve our puzzles. I enjoyed the academic report very
much as we have had a short glimpse of current research in this field.
Besides that, I appreciate the effort from the kind teaching assistants, Ms. Jiaqi, Ms. Ma Le, and Mr. Jin Long. They
had constantly connected with us via email and WeChat regardless of the various time zone of all the participants
from 35 countries. The learning materials and meeting link had been shared with us again and again just to ensure
we never miss it. They even take the initiatives in conducting the ice breaking session among us. The result was
we know each other better! We know the university of every participant and the gourmets from their respective
hometown Algeria traditional couscous, nasi biryani from Pakistan, Wuhan doupi, ofada rice from Nigeria, mango
sticky rice from Thailand, spicy hotpot from Chongqing and so on.
Before the event, I thought it is going to be an online learning program with no interaction with others. But now
that’s totally out of my expectation. It is an amazing and fruitful learning experience even under this pandemic. I
had enjoyed a lot from these outstanding academic lectures and able to explore innovative ideas. Besides that, the
sharing and invitation fro experience sharing from the moderator and staff, Ms. He Jinglin had also made this IGSS
more interesting.
Other than gaining fundamental concepts and technologies in Multi-temporal SAR Interferometry, Machine Learning
& Social Sensing, Geospatial Big Data Computing and Disaster Management throughout this 9-day event, we
managed to meet other energetic talents from all over the world, to be exact —143 participants from 35 countries.
These 143 participants had been selected among the 400 applications, and we are blessed enough to be one of the
selected participants and study together. I thank profusely to all the staff from IGSS2021 for your strong enthusiasm
in educating younger generation parallel with the technology development and update rather than only let us
concentrate in fundamental concept.
Lastly, I am CHAN FONG CHI from Malaysia. Thank you for having me in this summer school, and nice to meet
every one of you. Looking forward to having further learning opportunities from LIEMARS and hope next time we
could see each other face to face.
50 51

Multi-temporal SAR Interferometry Applications for Disaster Mitigation

Multi-temporal SAR Interferometry Applications for Disaster Mitigation

Recommended

Recommended

More Related Content

Similar to Multi-temporal SAR Interferometry Applications for Disaster Mitigation

Similar to Multi-temporal SAR Interferometry Applications for Disaster Mitigation (20)

More from Nathan Mathis

More from Nathan Mathis (20)

Recently uploaded

Recently uploaded (20)

Multi-temporal SAR Interferometry Applications for Disaster Mitigation