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20250805_a

Staff Highlights: Prof. Jianli CHEN

Prof. Jianli Chen is a Chair Professor of Space Geodesy and Earth Sciences in the Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University. He graduated from the University of Science and Technology of China in 1986 with a major in Space Physics. He obtained a Master’s degree in Astrometry from the Shanghai Astronomical Observatory, Chinese Academy of Sciences in 1989, and earned a Ph.D. in Geophysics from the University of Texas at Austin, USA in 1998. After having dedicated nearly 30 years of his academic career at the University of Texas in Austin, he joined the Hong Kong Polytechnic University in 2022 through the Strategic Hiring Scheme.   Prof. Chen is a world-renowned expert in space geodesy and its applications in Earth sciences. He has been working on topics related to global climate change and geophysical applications of space geodetic techniques, including satellite gravimetry, satellite altimetry, and other geodetic measurements for over 30 years. He has been extensively involved in data processing, results validation, and geophysical interpretation of the Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry mission, and is a leading science team PI of both the GRACE and GRACE Follow-On missions. He is a fellow of the American Geophysical Union (AGU) and International Association of Geodesy (IAG), and has severed as the chair of the IERS Special Bureau for Hydrology since 2004, and chair/member of numerous other committees in the geodesy community. A crowning distinction of his decorative career was the prestigious 2005 Presidential Early Career Awards for Scientists and Engineers (PECASE), the highest honor bestowed by the United States government on early career scientists and engineers (he was the first PECASE awardee in the geodesy field).   Prof. Chen’s research spans a wide range of topics, including satellite gravimetry, satellite altimetry, processing and application of Global Navigation Satellite System (GNSS) observational data, as well as global sea-level change, terrestrial water storage variations, melting of polar ice sheets and mountain glaciers, Earth rotation, and surface deformation. He has published more than 160 academic papers in top Earth science journals such as Science, Nature, PNAS, Nature Geoscience, Geophysical Research Letters, Journal of Geophysical Research, etc., with over 60 as the first author. He has led more than 20 research projects funded by governmental agencies such as NASA, NSF, NSFC (China), and RGC (Hong Kong), with total funding exceeding HK$63 million.   Prof. Chen’s impact extends beyond the academic fields and across national boundaries, drawing widespread attention from the global media. His research findings have been reported by many major media outlets, including USA Today, BBC News, The Washington Post, Discovery News, National Geographic, the Australian Broadcasting Corporation (ABC), New Scientist, China Daily, People’s Daily, and China Central Television (CCTV), among others. These reports have played a significant role in enhancing public awareness and understanding of Earth’s environment and climate change.   The following is a list of examples of Prof. Chen’s profound contributions in related research fields:   1. The first detection of accelerated melting of the Greenland Ice Sheet (Chen et al., 2006; Science)   Prof. Jianli Chen led a pioneering study published in Science (Chen et al., 2006) to have successfully detected accelerated ice melting of the Greenland ice sheet using early data from the GRACE satellite gravity observations. The melting of the Greenland Ice Sheet is considered as one of the primary contributors to the global sea level rise. However, accurately determining the rate of melting has been extremely challenging.   The launch of the GRACE (Gravity Recovery and Climate Experiment) satellite mission in 2002, jointly sponsored by NASA (United States) and DLR (Germany), has provided a revolutionary tool to precisely monitor mass redistribution within the Earth system - including the melting of polar ice sheets and mountain glaciers. However, the limited spatial resolution and data noise inherent in GRACE satellite gravity observations posed significant challenges in accurately estimating the melting rate of the Greenland Ice Sheet.   Prof. Chen’s team overcame these obstacles by designing a novel data processing method later known as Forward Modeling (FM). Using this method, they successfully corrected the leakage error in GRACE gravity measurements and estimated the melting rate of the Greenland Ice Sheet between April 2002 and November 2005. Their analysis revealed a clear acceleration in melting beginning in the summer of 2004, and that the melting extent had expanded into higher latitudes in the northeastern region of Greenland.   This pioneering research has had a profound impact. By introducing a completely new satellite gravity observational technique, it significantly enhanced people’s understanding of how climate warming affects polar ice sheet melting and contributes to sea level rise. The study was widely reported by over hundreds of media outlets around the world, including USA Today, The Washington Post, BBC News, China Daily, People’s Daily, and China Central Television (CCTV).   2. Accelerated melting of the Antarctic Ice Sheet (Chen et al., 2009; Nature Geoscience)   The Antarctic Ice Sheet is the largest on Earth, covering nearly 14 million square kilometers (km2). If it were to melt completely, the global mean sea levels would rise by more than 60 meters. However, accurately estimating its melting rate is difficult. On one hand, the West and East Antarctic Ice Sheets exhibit markedly different responses to climate change due to differences in elevation and topography. On the other hand, the tremendous scale and remoteness of the Antarctica make field observations scarce, and satellite remote sensing also faces significant limitations. For a long time, it was even unclear whether the Antarctic Ice Sheet as a whole was gaining or losing mass. Although GRACE satellite gravimetry provided a new approach to quantitatively observe mass changes in the Antarctica, the limited spatial resolution of the GRACE data made it difficult to accurately determine regional glacier mass variations. By applying the innovative Forward Modeling leakage correction method, Prof. Chen’s team was able to overcome the challenge and successfully estimate the melting rates of different regions of the Antarctic Ice Sheet between April 2002 and January 2009 using GRACE satellite gravity observations. Their analysis revealed that during this nearly 7-year period, the Antarctic Ice Sheet was losing ice at a rate of 190 ± 77 km³ per year (equivalent to 190 billion metric tons of water annually). The majority of this loss, about 132 ± 26 km³ per year, came from coastal glaciers in West Antarctica. Moreover, the melting rate in these areas increased significantly starting in 2006. Another groundbreaking finding was the first detection of notable glacier mass loss in parts of East Antarctica, previously thought to be relatively stable. This breakthrough studywas published in Nature Geoscience (Chen et al., 2009), and it drew widespread attention from news media around the world as well.   3. Closing the global sea level rise budget (Chen et al., 2013; Nature Geoscience)   Accurate observation and interpretation of global sea level rise are key topics in climate change research. Since the early 21st century, the development of satellite altimetry, satellite gravimetry (GRACE), and the global ocean float network (ARGO) has brought a completely new era for studying sea level change. In theory, after accounting for solid Earth deformation, the observed global sea level change should equal the sum of the ocean mass change (from GRACE) and steric sea level change (from ARGO). However, for a period of time, the altimeter-based global sea level rise rate did not match the sum of mass and steric components, creating what is known as the “sea level budget closure problem”. Prof. Chen’s team reprocessed the GRACE data using the innovative Forward Modeling method, and found that earlier GRACE solutions had significantly underestimated the ocean mass increase due to inadequate treatment of leakage errors. By systematically reanalyzing satellite altimetry, GRACE gravimetry, and ARGO float observations, they demonstrated that between 2005 and 2011, the observed global sea level rise rate of 2.39 ± 0.48 mm/year was fully consistent with the sum of the GRACE-based ocean mass increase (1.80 ± 0.47 mm/year) and the ARGO-based steric change (0.60 ± 0.27 mm/year), totaling 2.40 ± 0.54 mm/year.   4. Pioneering Global Sea Level Budget Analysis (Chen et al., 1998; GRL)   With the launch of the first modern altimetry satellite TOPEX/Poseidon in the early 1990s, scientists were able to accurately monitor global mean sea level change. However, understanding the mechanisms driving sea level change remained in its infancy. During his Ph.D. studies (1994–1998), Prof. Chen carried out a pioneering analysis of the global sea level change budget closure. Due to the limited availability of ocean mass and temperature/salinity observations at the time, his early work focused on seasonal changes in the global mean sea level. To address the lack of ocean mass observations, Prof. Chen innovatively proposed using climate model outputs of land water storage and atmospheric water vapor to estimate ocean mass changes through a global water mass balance approach. He also used limited traditional ocean temperature and salinity data from the World Ocean Atlas to calculate potential steric sea level changes, and then compared these with altimetry data from TOPEX/Poseidon. At the seasonal scale, the results from the three methods agreed remarkably well, demonstrating for the first time that global sea level change could be quantitatively explained through budget closure analysis.   5. Global warming shifted the Earth’s rotation pole (Chen et al., 2013; GRL)   With the advancement of modern space geodetic technologies, Earth’s rotation has become one of the most precisely observed geodetic variables. Variations in Earth’s rotation are closely linked to mass redistribution within the Earth system. Accurate measurements of Earth rotation parameters, including Length-of-Day (LOD) and polar motion provide an independent tool for studying global climate change and large-scale mass transport processes. Length-of-Day reflects changes in the rotational speed of the Earth, while polar motion describes the movement of the Earth’s rotational pole, i.e. the rotational axis’ intersection with the Earth’s surface near the North Pole. Long-term changes in Earth rotation, such as the secular drift of the rotational pole (typically toward the south), are primarily driven by solid Earth processes, including the Post-Glacial Rebound (also-called Glacial Isostatic Adjustment) and plate tectonics. However, seasonal and interannual variations in Earth rotation are mainly caused by mass redistribution within the climate system. By analyzing long-term polar motion data, Prof. Chen’s team was the first to have detected a shift in the direction of the Earth’s rotational pole drift—from southward to eastward—starting around 2005. Using GRACE satellite gravity data, the team found that this shift was directly linked to accelerated melting of polar ice sheets and rising global sea level driven by global warming. This major discovery was published in the Geophysical Research Letters (Chen et al., 2013). The study received wide media attention worldwide, including coverage by CBS, New Scientist, Physics Today, Scientific American, Daily Mail, The Guardian, Inverse, Xinhua News Agency, Reference News, and others. Nature published a special commentary as a “Breaking News” item, and both NASA and the U.S. National Science Foundation (NSF) listed the study among their Research Highlights of 2013.   6. Discovery of subglacial lakes in Greenland using GNSS data (Ran et al., 2024; Nature)   The Greenland Ice Sheet is currently the largest single contributor to global sea level rise, with the potential to raise the mean sea level by up to seven meters if completely melted. While scientists have long studied the melt processes of the ice sheet, one crucial question has remained unanswered: how does meltwater storage evolve within the ice sheet throughout the summer melt season? Prof. Chen and a team of international experts from  Hong Kong, mainland China, U.S., Netherlands, Denmark and Belgium, led by Dr. Jiangjun Ran at the Southern University of Science and Technology, used a network of GNSS (Global Navigation Satellite System) stations—called the Greenland GNSS Network—to observe bedrock deformation in response to meltwater loading. These data allowed the researchers, for the first time to detect subglacial lakes and to quantify seasonal meltwater storage processes. Using continuous GNSS data from 22 stations near outlet glaciers and bedrock from 2009 to 2015, the researchers estimated regional meltwater volume, elastic bedrock deformation, and vertical displacement to understand how meltwater evolves spatially and temporally. GNSS also enabled monitoring of large-scale mass changes in the climate system, such as groundwater depletion and lake storage variations. Results showed that most meltwater during summer was temporarily stored within the ice sheet, peaking in July and gradually decreasing thereafter. Meltwater induced average bedrock subsidence of about 5 mm, with extreme melt years like 2010 and 2012 causing subsidence up to 12 mm and 14 mm, respectively. The average meltwater residence time was about eight weeks, varying regionally—from about nine weeks in the northeast and west to just 4.5 weeks in the south and southeast. The study also found that climate models may overestimate runoff or underestimate meltwater retention, and suggested that projected meltwater runoff in warmer years should be adjusted upward by ~20% for more accurate assessments. This important discovery was published in Nature (Ran et al., 2024) and received widespread media coverage, including Xinhua News Agency, People’s Daily, China Science Daily (front page), ScienceNet.cn, CGTN, and many other major outlets in mainland China and Hong Kong (e.g., Ming Pao, Wen Wei Po, Ta Kung Pao, HK Commercial Daily).   7. Sea level rise and Earth rotation reveal permanent hydrological regime change in the 21st Century (Seo et al., 2025; Science)   Global warming has triggered changes in atmospheric and oceanic temperatures, disrupting terrestrial water cycles and surface water fluxes such as precipitation and evapotranspiration. These processes have led to significant changes in terrestrial water storage (TWS). In collaboration with international colleagues, Prof. Chen and the team (led by Prof. Ki-Weon Seo at the Seoul National University) have utilised advanced reanalysis datasets and satellite observations, and uncovered a dramatic depletion of terrestrial water storage—particularly soil moisture—across the globe. Between 2000 and 2002, global soil moisture decreased by about 1,614 Gt (km³)—a loss significantly greater than the roughly 900 Gt of ice mass lost from Greenland during a similar timeframe (2002–2006). From 2003 to 2016, another 1,009 Gt of soil water was lost, and as of 2021, the global soil moisture had not yet recovered to the pre-2000 levels. To verify this, the team examined independent data from satellite altimetry and Earth rotation observations. They found that between 2000 and 2002, global mean sea level rose by ~4.4 mm, and in the following decade, the Earth’s rotation axis shifted by ~58 cm toward the east. These independent observations support the ERA5 model results, indicating a long-term hydrological shift driven by reduced rainfall and increased evapotranspiration under global warming. The findings suggest that global soil water depletion is persistent and unlikely to recover under current climate conditions. This landmark study was recently published in Science (Seo et al., 2025) and has garnered extensive international media attention. Prof. Chen and lead author Prof. Ki-Weon Seo have built a long-term research collaboration, having jointly published over 20 high-impact journal papers in related fields.  ************************************************************* Prof. Chen is currently seeking highly motivated candidates Ph.D. student and for Research Assistant/Associate positions in the field of space geodesy and global climate change. Preferred qualifications include strong interest in space geodesy, geodynamics and global climate change, proficient English communication skills, and good data analysis and programming skills.   The Ph.D. candidates are expected to work on two RGC and NSFC sponsored major projects on global and regional sea level change. Anybody with a major in geodesy, geophysics, or other related Earth science fields is encouraged to apply. Please send your CV (including college transcripts and rankings), a cover letter, and a research statement outlining your Ph.D. research plan (all in PDF format) to Prof. Jianli Chen (jianli.chen@polyu.edu.hk).

5 Aug, 2025

Research

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PhD Student ZHOU Mo Achieves Multiple Prestigious Awards

We are delighted to announce that our PhD student, ZHOU Mo, under the mentorship of Prof. Wang Shuo, has recently achieved remarkable success by receiving several competitive awards in recognition of her outstanding research and presentation skills. At the FCE 3MT Competition 2025, held on 10 June 2025, ZHOU Mo was named First Runner-up and also received the People’s Choice Award. These accolades came with a cash prize of HK$6,000, highlighting her ability to effectively communicate complex research to a broad audience. In addition, ZHOU Mo was honoured with the "Best Paper Award" at the PolyU Research Student Conference (PRSC 2024), accompanied by a cash prize of HK$20,000. This award recognises her exceptional research contributions and the high quality of her scholarly work.   Congratulations to ZHOU Mo on her outstanding achievements!

26 Jun, 2025

News

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PolyU study uncovers Hong Kong’s hidden history with cutting-edge geospatial technologies

A project led by Prof. Wallace Wai Lok Lai, Associate Head (Teaching) and Professor of the Department of Land Surveying and Geo-informatics, seeks to reveal and record the city’s lost history hidden underground by utilising cutting-edge geospatial technologies and to launch public education programmes to promote the conservation and better understanding of the city’s cultural heritage. The team has recently uncovered “lost and found” stories from five cultural and wartime heritage sites. With support from the PolyU Research Institute for Land and Space, Prof. Lai is expanding this study to Southeast Asia. The project has received funding of HK$3.22 million from the General Support Programme under the Innovation and Technology Fund of the Innovation and Technology Commission. Press release: English - https://polyu.me/3HrOSKG; Chinese - https://polyu.me/4mLY50F Online coverage: Ming Pao Daily News - https://polyu.me/4jy4byM am730 - https://polyu.me/4dXGVcn  Hong Kong Economic Times - https://polyu.me/45eqdTL Bauhinia - https://polyu.me/43Jt84w  

6 Jun, 2025

News

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Staff Highlights: Prof. Tiangang YIN

Forests, which cover 31 % of Earth’s land surface, play a vital role in the global climate system, carbon sequestration, and energy cycles. Monitoring forest ecosystems is therefore essential for understanding their dynamics and guiding sustainable management practices.   Prof. Tiangang Yin, from the Department of Land Surveying and Geo-informatics (LSGI), leads the 3-D Sensing, Modeling, and Data Intelligence (3MSI) Lab (https://www.3msi.net/). By leveraging multi-platform lidar technology and big data techniques, the team focuses on accurate 3D reconstruction of vegetation and enhanced retrieval of forest biophysical variables from diverse remote sensing data. Through the integration of advanced radiative-transfer models (RTMs) and artificial intelligence (AI) methods, they aim to develop a comprehensive Forest Digital Twin (FDT) system capable of delivering large-scale, time-series realistic forest representations, satellite observations, and energy-cycle simulations.   Topic 1: Large-Scale and High-Fidelity 3D Forest Reconstruction Using Airborne Lidar Data   The 3D structure of forests is critical for understanding complex ecological processes and conducting forest inventories, thereby supporting sustainable forest management. By providing 3D information, lidar technology is an ideal tool for reconstructing forest structures. Compared to terrestrial lidar, airborne laser scanning (ALS) can efficiently characterize extensive forested areas, making large-scale 3D reconstruction feasible.   To achieve this, we developed an ALS-driven, large-scale forest 3D reconstruction workflow (LS-PVlad), capable of producing high-resolution (2 m) voxelized 3D scenes covering up to 11,000 ha. Using this workflow, we created the FoScenes product, which comprises multiple high-fidelity scenes of various forest sites across North America. When combined with 3D RTM (e.g., DART and DART-EB, https://dart.omp.eu/index.php#/), FoScenes supports multi-scale remote sensing simulation and sensitivity analysis, demonstrating strong potential for enhancing global forest parameter retrieval and advancing ecological research.    Topic 2: Retrieving Forest Canopy Surface by Integrating Stereophotogrammetry into 3D Radiative Transfer Model   Canopy Height Model (CHM), as a critical parameter characterizing forest canopy’s structures, plays a vital role in forest inventory management, carbon sink quantification, biodiversity assessment, and etc. Spaceborne photogrammetry has emerged as a crucial approach for acquiring very-high-resolution (VHR) CHM data. However, the acquisition of high-quality VHR stereopairs data remains constrained by multiple factors including satellite revisit cycles and sensor's observational angles, etc. Our team proposed a novel stereopair simulation pipeline integrating PVlad-derived 3D LAD forest scenes with a 3D radiative transfer model (i.e., DART). Through simulating extensive VHR satellite stereopairs, this approach enables systematic sensitivity analysis of key factors affecting the estimation of forest canopy height. This research direction holds significant guidance value for future satellite mission design and the development of forest CHM retrieving algorithms.    Topic 3: Monitoring Urban Trees Using Multi-Source Lidar Data   Urban trees play a crucial role in human well-being by improving air quality, reducing the urban heat island effect, and enhancing living environments. Therefore, large-scale, long-term, and precise monitoring of key metrics—such as tree count, leaf area, and health—has become vital for urban management. Traditional manual surveys struggle with efficiency, coverage, and real-time needs, highlighting the potential of lidar combined with multisource data for accurate monitoring.   Our team has collected long-term lidar data from hundreds of urban trees in Hong Kong, creating a unique database in collaboration with local authorities. We focus on single-tree point cloud processing, including branch/leaf classification, occlusion completion, 3D reconstruction, and biomass/leaf area density estimating, using deep learning techniques trained on both empirical and simulated data.      References:   Yin, T., Cook, B. D. & Morton, D. C., 2022. Three-dimensional estimation of deciduous forest canopy structure and leaf area using multi-directional, leaf-on and leaf-off airborne lidar data. Agricultural and Forest Meteorology. 314, 108781. https://doi.org/10.1016/j.agrformet.2021.108781.   Yin, T., Montesano, P. M., Cook, B. D., Chavanon, E., Neigh, C. S. R., Shean, D., Peng, D., Lauret, N., Mkaouar, A., Morton, D. C., Regaieg, O., Zhen, Z. & Gastellu-Etchegorry, J.-P., 2023. Modeling forest canopy surface retrievals using very high-resolution spaceborne stereogrammetry: (I) methods and comparisons with actual data. Remote Sensing of Environment. 298, 113825. https://doi.org/10.1016/j.rse.2023.113825.   Yin, T., Montesano, P. M., Cook, B. D., Chavanon, E., Neigh, C. S. R., Shean, D., Peng, D., Lauret, N., Mkaouar, A., Regaieg, O., Zhen, Z., Qin, R., Gastellu-Etchegorry, J.-P. & Morton, D. C., 2023. Modeling forest canopy surface retrievals using very high-resolution spaceborne stereogrammetry: (II) optimizing acquisition configurations. Remote Sensing of Environment. 298, 113824. https://doi.org/10.1016/j.rse.2023.113824.   Wei, S. S., Yin, T. G., Dissegna, M. A., Whittle, A. J., Ow, G. L. F., Yusof, M. L. M., Lauret, N. & Gastellu-Etchegorry, J. P., 2020. An assessment study of three indirect methods for estimating leaf area density and leaf area index of individual trees. Agricultural and Forest Meteorology. 292, 108101. https://doi.org/10.1016/j.agrformet.2020.108101.  

5 Jun, 2025

Research

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LSGI Professor Wallace Lai Showcases Urban Solutions for Uncovering WWII Relics on ViuTV’s "Now Report"

Prof. Wallace LAI Wai-Lok, Associate Head (Teaching) of the Department of Land Surveying and Geo-Informatics (LSGI) was recently featured on ViuTV’s renowned current affairs programme, "Now Report" (《經緯線》). This episode focused on revitalization of World War II air-raid shelters in Hong Kong and the challenges might be encountered.   During the programme, Prof. Lai shared how 21st-century geospatial and geophysical technologies are being applied to discover World War II relics. By using these technologies, the stories and history of that era can be uncovered and presented to the public.   For more details, watch the interview here: Youtube   Online coverage: Viu TV - https://viu.tv/encore/now-report (19:59 - 22:15) Now TV News - https://news.now.com/home/local/player?newsId=605872 (7:29 - 9:46)

2 Jun, 2025

News

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LSGI Retreat 2025

The Department of Land Surveying and Geo-Informatics (LSGI) at The Hong Kong Polytechnic University held its annual retreat on 26-27 May 2025, at the Hyatt Regency Hengqin in Zhuhai, Mainland China. This event brought together teaching, academic, and selected administrative staff to discuss strategies for advancing the department's educational and research goals, as well as promoting the department. Following an opening address by Department Head Prof. Wu Chen, the first discussion session was led by Prof. Wallace Lai and Prof. Xintao Liu, focusing on the latest initiatives in Learning & Teaching. Participants explored integrating generative AI into Geomatics education and using geo-spatial large language models in teaching. Group presentations highlighted innovative ideas in AI education. Prof. Xintao Liu also announced that LSGI will host the 2nd International Conference on Geomatics Education in December 2025, encouraging staff participation and paper submissions. After a coffee break, the focus shifted to "Partnership and Strategic Development" introduced by Prof. Yang Xu. Discussions centered on positioning LSGI as a global leader in Geomatics through marketing strategies and industry partnerships. The day concluded with presentations and a summary by Prof. Wu Chen, capturing the essence of the discussions and setting a collaborative tone for the retreat.   On the second day, Prof. Bo Wu shared the LSGI's research performance and updates on the Research Assessment Exercise (RAE), calling for further input from colleagues to enhance the Environment Statement in the RAE. Discussions followed on fostering a collaborative research environment and supporting staff in securing major funding. Presentations showcased diverse strategies for impactful research development. The retreat concluded with a summary by Prof. Wu Chen, emphasizing the strategies developed over the two days. Participants left with renewed insights to advance LSGI's mission.   The LSGI Retreat 2025 underscored the department's commitment to innovation in Geomatics education and research, fostering collaboration to enhance its global impact.

28 May, 2025

News

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PolyU JUPAS Consultation Day 2025

The PolyU JUPAS Consultation Day 2025 was concluded successfully on 24 May 2025 (Saturday). On the day of event, many recent HKDSE candidates and their parents showed great interest in the scheme programme offered by our department.  In addition to visiting our consultation counter to inquire about JUPAS subject selection strategies, students and parents also attended our admission seminar with surveying equipment demonstration to gain a deeper understanding of our programme information. Apart of receiving guidance on changes of JUPAS choices and latest Flexible Admission arrangement, they have also explored the career prospects our programmes may offer. We wish all students the best of luck in the HKDSE and hope all your aspirations come true. We look forward to seeing all again on PolyU campus! If you missed the event, you may find more information on our programme page below:     BSc (Hons) Scheme in Spatial Data Science and Smart Cities (Land Surveying and Geo-Informatics / Urban Informatics and Smart Cities)

26 May, 2025

News

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Call for Abstract: The 2nd International Conference on Geomatics Education (ICGE 2025)

The Department of Land Surveying and Geo-Informatics (LSGI) at The Hong Kong Polytechnic University is proud to announce “The 2nd International Conference on Geomatics Education – AI for Geomatics Education: Perspectives and Challenges (ICGE 2025)” will be held during 3-5 Dec 2025.   ICGE 2025 will bring together global educators, researchers, and industry leaders to explore the transformative role of AI in advancing geospatial science education. The conference will address critical opportunities, innovative methodologies, and ethical considerations in integrating AI technologies into geomatics curricula and practices.   Date:    3 - 5 December 2025 Venue: PolyU Campus, Hung Hom, Hong Kong   Click here for Abstract Submission   Important Dates: Call for abstracts:                          1 Mar 2025 Submission of final abstract:        1 Aug 2025 Notification of acceptance:           1 Sep 2025 Registration opens:                       10 Apr 2025     For more information, please visit ICGE 2025 website or email info.icge@polyu.edu.hk.

21 May, 2025

News

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Feature Talk "Unfolding HK Lost WWII Heritage with Geo-Spatial Science" at Geospatial Lab

On 17 May 2025, Ir. Prof. Wallace Lai, Associate Head of Department (Teaching) from LSGI and Prof. Chi Man Kwong from Hong Kong Baptist University (HKBU) were invited to be guest speakers for a feature talk " Unfolding HK Lost WWII Heritage with Geo-Spatial Science " at the Geospatial Lab. The talk attracted 42 participants who attended in person and 80 people participated online. We sincerely thank all participants for their enthusiastic engagement and the support from Geospatial Lab. The talk not only brought to life WWII ruins from Battle of Hong Kong in 1941, but also deepened the audience’s understanding of the significance of Hong Kong’s WWII history. Attendees witnessed the powerful fusion of geospatial technology and historical research, sparking a renewed appreciation for preserving Hong Kong’s cultural heritage. Click here to read more.

20 May, 2025

News

20250519_A

Staff Highlights: Prof. Chengxiang ZHUGE

The development of smart cities contributes to inclusive growth, resilience, and global sustainability efforts, and thus plays a crucial role in advancing the Sustainable Development Goals (SDGs).   Prof. Chengxiang Zhuge, Assistant Professor from the Department of Land Surveying and Geo-informatics (LSGI) is leading the TIP research group focusing on Technology innovation, Infrastructure planning and Policy making in Smart Cities. They consider cities as complex systems and develop technologies and models to address urban issues based on artificial intelligence, simulation approaches and big data analytics. Recently, they are particularly interested in the TIP-related research topics in the mobility and residential sectors.   Topic 1: Electric Vehicle User Behavior Analysis and Modelling and Infrastructure Planning Many cities are acting actively to electrify their transportation system towards a smart and sustainable mobility system. In 2024, electric vehicle (EV) sales in China surpassed 10 million units, accounting for 61% of global sales. The TIP group focuses on understanding EV user behavior and optimizing the layout and operation of charging infrastructure. From the behavioral perspective, they have developed an EV big data analytical framework based on large-scale real-world trajectory data from over 100,000 EV users. This framework can help to uncover the underlying mechanisms behind EV users’ travel, parking, and charging decisions.   To support short-term charging demand forecasting, the TIP group integrate deep learning techniques with the spatiotemporal patterns of charging demand. Their models enable accurate short-term predictions of charging needs at the station or regional level, thereby supporting more efficient infrastructure operations and management. For infrastructure deployment, the TIP group propose a series of microsimulation-based optimization models considering multiple energy sources, vehicle types, facility types, and stakeholder objectives. These models can help to search for tailored solutions that balance factors such as system cost, carbon emissions, and operational efficiency. The case studies span a range of cities, including Hong Kong, Beijing, Shenzhen, and New York.   Topic 2: Agent-based Urban Simulation Model As a typical complex system, city is composed of multiple interrelated and interdependent subsystems, including transportation, land use, energy, environment, population, and economy. Urban micro-simulation models have been increasingly used as decision support systems to explore such complex dynamic systems, enabling urban planners and policymakers to systematically evaluate the impacts of various planning strategies and policy interventions, anticipate long-term urban development patterns under different scenarios, and provide scientific evidence to support urban planning, policy making, and technology investment.   The TIP group has been developing an open-source agent-based urban simulation model, SelfSim. Compared with existing urban micro-simulation models, SelfSim is focused on simulating the impacts of sustainable technologies, policies, and infrastructures. Its modular framework allows for the integration of various low-carbon technology diffusion models and the social network evolution model. Based on open-source data, the TIP group has applied SelfSim in five global cities: Beijing, Shenzhen, London, Berlin, and New York. These city-scale scenarios allow for the simulation-based appraisal of a wide range of planning and policy strategies, offering decision support for sustainable urban development.   Topic 3: Adoption and Impacts of Low-Carbon Technologies and Services In 2019, the buildings and transport sectors each accounted for 29% of global end-use energy consumption and contributed 19% and 7%, respectively, to direct energy-related greenhouse gas (GHG) emissions. Studies indicate that by 2050, demand-side measures could reduce GHG emissions from buildings and land transport by 66% and 67%, respectively.   The TIP group focuses on the adoption behaviors of low-carbon technologies and services within the transportation and residential sectors. Using urban big data analytics and agent-based simulation methods, the group investigates the mechanisms behind the interlinked adoption of emerging technologies and services, particularly within development of smart cities. These include autonomous vehicles, shared mobility, and new energy vehicles in the transport sector, as well as smart home technologies, smart heating/cooling systems, and energy-efficient lighting systems in the residential sector. Based on the empirical analysis and simulation modeling of adoption behaviors, the TIP group has further developed an integrated framework to assess their impacts from infrastructural, energy, environmental, and social perspectives.

19 May, 2025

Research

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