CS 225 - Spatial Computing

Winter 2025

Time: Monday, Wednesday - 2:00 PM to 3:20 PM

Location: Winston Chung Hall, Room 142 (WCH 142)

Instructors: Amr Magdy -
Yongyi Liu -
Office Hours: Follow eLearn Link here
Additional asynchronous hours over email or by appointment.

TA: - Office Hours: Follow eLearn Link here

(If you still cannot access eLearn, please either consult your classmates or send email to or from your enrollment email with your student ID)

Teaching Feedback Form: https://goo.gl/forms/g5C4VjKRlmButg693

Textbook: The course is based on research papers and selected readings.
Supplementary Materials: Spatial Databases: A Tour by S. Shekhar and S. Chawla, Prentice Hall, 2003, ISBN-13: 978-0130174802, ISBN-10: 0130174807 Amazon

Syllabus

Spatial data underpins a vast range of applications, from navigation systems and smart agriculture to public health and urban safety. Its significance extends across disciplines, including geographic information systems (GIS), environmental sciences, and social behavior analysis. This course offers a comprehensive introduction to the foundational principles and cutting-edge technologies driving spatial computing today. Through a mix of theoretical exploration and hands-on practice, students will engage with spatial data models, storage techniques, indexing, and querying. Real-world applications are emphasized, empowering students to develop both foundational skills and forward-looking perspectives. Students will use state-of-the-art spatial platforms to create solutions ranging from analytical tools to interactive visualizations. The topics that will be covered include:

  • Introduction to Spatial Computing
  • Spatial Relationships and Data Models
  • Spatial Data Storage and Indexing Techniques
  • Optimized Spatial Query Processing
  • Spatial Networks
  • Geo-visualization and User Interaction
  • Spatial Data Mining
  • Emerging Trends and Innovations in Spatial Technologies

Grading

    Course work

  • Class Participation (10%)
  • Evaluating others (5%)
  • Paper Reviews (7.5%)
  • Hands-on on Spatial Technologies (7.5%)
  • Presentation (10%)
  • Project (50%)
  • Final exam (10%)

Schedule

Date Topic  MaterialNotes
Mon 1/6 Course Outline + Introduction to Research
Wed 1/8Introduction to Spatial Computing
Mon 1/13Spatial Relationships and Data ModelsAssignment 0 due
Wed 1/15 Paper review 1 discussion + Spatial Relationships and Data ModelsAssignment 1 due Assignment 2 due
Mon 1/20No Lecture, MLK Day
Wed 1/22 Spatial Data Storage and Indexing
Mon 1/27 Spatial Query Processing
Wed 1/29 Spatial Networks
Mon 2/3 Geovisualization
Wed 2/5 Spatial Data Mining
Mon 2/10 Presentations 1-4 Assignment 3 due
Wed 2/12 Presentations 5-7
Mon 2/17No Lecture, Presidents' Day
Wed 2/19Paper review 2 discussion
Assignment 4 due
Mon 2/24Presentations 8-10 Assignment 5 due
Wed 2/26 Presentations 11-13
Mon 3/3 Presentations 14-17Assignment 6 due
Wed 3/5 Presentations 18-21
Mon 3/10Presentations 22-25
Wed 3/12Final Exam + Project DiscussionsFinal project deliverables due

Project Groups

  Group Members
#1 Nadig, Abhijith Arvind || Bennur, Rohan || Guruprasad, Sourav
#2 Bian, Yiyang || Chang, Yunhan || Abdelmaguid, Ahmed
#3 Devappa, Akash || Shah, Divyank || Zhang, Yusen ||
#4 Sharma, Akshit || Agrawal, Dhruv || Harnett, Josh
#5 Kalathiya, Parth Pareshbhai || Patil, Anant || Shanmugavadivel, Vasanthakumar
#6 Nittur Venkatesh, Anirudh || Manjunatha, Manoj || Enaganti, Vijay Ram
#7 Nicks, Brent || Yee, Justin || Pagadala, Srijan
#8 Anand Rangappa, Chandana || Narasimhamurthy, Ranjitha || Bolbandi, Vismaya Anand
#9 Kshitij, FNU || Sunilkumar, Lakhan Kumar || Kumar, Vignesh
#10 Muttepwar, Hrutvika || Ise, Kush || Patil, Vaishnavi
#11 Chou, Kelvin || Yu, Kunyi || Ibrahim, Mona
#12 Hu, Zeliang || Zhou, Lingdong || Kuang, Weihang
#13 Sharma, Pankaj || Gupta, Saransh || Challa, Viswanadh Rahul
#14 Mathur, Preksha || Jadhav, Siddhesh || Biswas, Sonali
#15 Srinivasa, Sanjay || Battula, Shreyas || Somalaram, Sumukh Balu
#16 Fu, Dasen || Patel, Bhagya || Wu, Yung Shuo
#17 Bhardwaj, Aditya || Gambhir, Aditya Rajeev

Assignments

PDF
#0 Assignment 0
#1 Assignment 1
#2 Assignment 2
#3 Assignment 3
#4 Assignment 4
#5 Assignment 5
#6 Assignment 6

Paper Reviews

#Paper Title
1 Panagiotis Tampakis, Dimitris Spyrellis, Christos Doulkeridis, Nikos Pelekis, Christos Kalyvas, Akrivi Vlachou: A Novel Indexing Method for Spatial-Keyword Range Queries. SSTD 2021: 54-63 ( https://dl.acm.org/doi/10.1145/3469830.3470897)
2 Tin Vu, Alberto Belussi, Sara Migliorini, Ahmed Eldawy: A Learned Query Optimizer for Spatial Join. SIGSPATIAL/GIS 2021: 458-467 (https://dl.acm.org/doi/abs/10.1145/3474717.3484217)

Discussion Questions

PDF
Discussion Questions

Presentations

ID# of presentersTopicPresentation Type and ContentAssigned Presenters
1 2 Spatio-temporal data Discussion: Interactive discussion guided by the discussion questions posted here.
2 2 Spatio-temporal data Slideshow: Tamas Abraham, John F. Roddick: Survey of Spatio-Temporal Databases. GeoInformatica 3(1): 61-99 (1999)
3 2 Geovisualization Slideshow: Saheli Ghosh, Ahmed Eldawy: AID*: A Spatial Index for Visual Exploration of Geo-Spatial Data. IEEE Transactions on Knowledge Data Engineering, 34(8): 3569-3582 (2022)
4 2 Geovisualization Slideshow: Liming Dong, Qiushi Bai, Taewoo Kim, Taiji Chen, Weidong Liu, Chen Li: Marviq: Quality-Aware Geospatial Visualization of Range-Selection Queries Using Materialization. SIGMOD Conference 2020: 67-82
5 2 Spatial keyword search Discussion: Interactive discussion guided by the discussion questions posted here.
6 2 Spatial keyword search Slideshow: Gao Cong, Christian S. Jensen, Dingming Wu: Efficient Retrieval of the Top-k Most Relevant Spatial Web Objects. Proc. VLDB Endow. 2(1): 337-348 (2009)
7 2 Spatial keyword search Slideshow: Lisi Chen, Shuo Shang, Chengcheng Yang, Jing Li: Spatial keyword search: a survey. GeoInformatica 24(1): 85-106 (2020)
8 2 Spatial big data platforms Slideshow: Wherobots Cloud and Apache Sedona, guided by: Jia Yu, Zongsi Zhang, Mohamed Sarwat: Spatial data management in apache spark: the GeoSpark perspective and beyond. GeoInformatica 23(1): 37-78 (2019)
9 2 Spatial big data platforms Slideshow: Varun Pandey, Andreas Kipf, Thomas Neumann, Alfons Kemper: How Good Are Modern Spatial Analytics Systems? Proc. VLDB Endow. 11(11): 1661-1673 (2018)
10 2 Spatial data on GPUs Discussion: Interactive discussion guided by the discussion questions posted here.
11 2 Spatial data on GPUs Slideshow: Arpan Man Sainju, Danial Aghajarian, Zhe Jiang, Sushil K. Prasad: Parallel Grid-Based Colocation Mining Algorithms on GPUs for Big Spatial Event Data. IEEE Trans. Big Data 6(1): 107-118 (2020)
12 2 Spatial crowdsourcing Discussion: Interactive discussion guided by the discussion questions posted here.
13 2 Spatial crowdsourcing Slideshow: Yongxin Tong, Zimu Zhou, Yuxiang Zeng, Lei Chen, Cyrus Shahabi: Spatial crowdsourcing: a survey. VLDB Journal 29(1): 217-250 (2020)
14 2 GeoAI Discussion: Interactive discussion guided by the discussion questions posted here.
15 2 GeoAI Slideshow: Ruibing Hou, Hong Chang, Bingpeng Ma, Rui Huang, Shiguang Shan: BiCnet-TKS: Learning Efficient Spatial-Temporal Representation for Video Person Re-Identification. CVPR 2021: 2014-2023
16 2 GeoAI Slideshow: Sijie Ruan, Cheng Long, Zhipeng Ma, Jie Bao, Tianfu He, Ruiyuan Li, Yiheng Chen, Shengnan Wu, Yu Zheng: Service Time Prediction for Delivery Tasks via Spatial Meta-Learning. KDD 2022: 3829-3837
17 2 GeoAI Slideshow: Haoyu Han, Mengdi Zhang, Min Hou, Fuzheng Zhang, Zhongyuan Wang, Enhong Chen, Hongwei Wang, Jianhui Ma, Qi Liu: STGCN: A Spatial-Temporal Aware Graph Learning Method for POI Recommendation. ICDM 2020: 1052-1057
18 2 Remote Sensing Slideshow: Pages 1-6 of "Introduction to Remote Sensing, by Nicholas C. Coops and Thoreau Rory Tooke. In Learning Landscape Ecology pp 3-19" + Brief highlight of major remote sensing applications.
19 2 Remote Sensing Slideshow: Fundamentals about LiDAR:
* What is lidar data? (https://desktop.arcgis.com/en/arcmap/10.3/manage-data/las-dataset/what-is-lidar-data-.htm)
* Types of lidar (https://desktop.arcgis.com/en/arcmap/10.3/manage-data/las-dataset/types-of-lidar.htm)
* Storing lidar data (https://desktop.arcgis.com/en/arcmap/10.3/manage-data/las-dataset/storing-lidar-data.htm)
* What is lidar intensity data? (https://desktop.arcgis.com/en/arcmap/10.3/manage-data/las-dataset/what-is-intensity-data-.htm)
* Lidar point classification (https://desktop.arcgis.com/en/arcmap/10.3/manage-data/las-dataset/lidar-point-classification.htm)
20 2 Remote Sensing Slideshow: Chao Chen, Jintao Liang, Fang Xie, Zijun Hu, Weiwei Sun, Gang Yang, Jie Yu, Li Chen, Lihua Wang, Liyan Wang, Huixin Chen, Xinyue He, Zili Zhang: Temporal and spatial variation of coastline using remote sensing images for Zhoushan archipelago, China. Int. J. Appl. Earth Obs. Geoinformation 107: 102711 (2022))
21 2 Remote Sensing Slideshow: Anh-Vu Vo, Chamin Nalinda Lokugam Hewage, Gianmarco Russo, Neel Chauhan, Debra F. Laefer, Michela Bertolotto, Nhien-An Le-Khac, Ulrich Oftendinger: Efficient LiDAR point cloud data encoding for scalable data management within the Hadoop eco-system. IEEE BigData 2019: 5644-5653
22 2 Remote Sensing Slideshow: A. S. Mohammed Abdul Athick, Shih-Yu Lee: A Combination of Spatial Domain Filters to Detect Surface Ocean Current from Multi-Sensor Remote Sensing Data. Remote. Sens. 14(2): 332 (2022)
23 2 HD Maps Discussion: Interactive discussion guided by the discussion questions posted here.
24 2 HD Maps Slideshow: Mahdi Elhousni, Yecheng Lyu, Ziming Zhang, Xinming Huang: Automatic Building and Labeling of HD Maps with Deep Learning. AAAI 2020: 13255-13260
25 2 HD Maps Slideshow: Elwan Héry, Philippe Xu, Philippe Bonnifait: Consistent decentralized cooperative localization for autonomous vehicles using LiDAR, GNSS, and HD maps. J. Field Robotics 38(4): 552-571 (2021)

Course Resources
Recommended Readings:
  • (1) Tamas Abraham, John F. Roddick: Survey of Spatio-Temporal Databases. GeoInformatica 3(1): 61-99 (1999)
  • (2) Ahmed R. Mahmood, Sri Punni, Walid G. Aref: Spatio-temporal access methods: a survey (2010 - 2017). GeoInformatica 23(1): 1-36 (2019)
  • (3) Gowtham Atluri, Anuj Karpatne, Vipin Kumar: Spatio-Temporal Data Mining: A Survey of Problems and Methods. ACM Computing Surveys 51(4): 83:1-83:41 (2018)
  • (4) Jia Yu, Mohamed Sarwat: Turbocharging Geospatial Visualization Dashboards via a Materialized Sampling Cube Approach. ICDE 2020: 1165-1176
  • (5) Dong Xie, Feifei Li, Bin Yao, Gefei Li, Liang Zhou, Minyi Guo: Simba: Efficient In-Memory Spatial Analytics. SIGMOD Conference 2016: 1071-1085
  • (6) Md. Mahbub Alam, Suprio Ray, Virendra C. Bhavsar: A Performance Study of Big Spatial Data Systems. BigSpatial@SIGSPATIAL 2018: 1-9
  • (7) Srinivasa Raghavendra Bhuvan Gummidi, Xike Xie, Torben Bach Pedersen: A Survey of Spatial Crowdsourcing. ACM Transactions on Database Systems. 44(2): 8:1-8:46 (2019)
  • (8) Ruibing Hou, Hong Chang, Bingpeng Ma, Rui Huang, Shiguang Shan: BiCnet-TKS: Learning Efficient Spatial-Temporal Representation for Video Person Re-Identification. CVPR 2021: 2014-2023
  • (9) James Tu, Mengye Ren, Sivabalan Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun: Physically Realizable Adversarial Examples for LiDAR Object Detection. CVPR 2020: 13713-13722
  • (10) Csaba Benedek: 3D people surveillance on range data sequences of a rotating Lidar. Pattern Recognition Letters 50: 149-158 (2014)
  • (11) Mike Izbicki, Vagelis Papalexakis, Vassilis J. Tsotras: Geolocating Tweets in any Language at any Location. CIKM 2019: 89-98
  • (12) Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, Junbo Zhang: Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning. KDD 2019: 1720-1730
  • (13) Ibrahim Sabek, Mohamed F. Mokbel: Sya: Enabling Spatial Awareness inside Probabilistic Knowledge Base Construction. ICDE 2020: 1177-1188
  • (14) Weiyu Cheng, Yanyan Shen, Yanmin Zhu, Linpeng Huang: A Neural Attention Model for Urban Air Quality Inference: Learning the Weights of Monitoring Stations. AAAI 2018: 2151-2158
  • (15) Kay Massow, Birgit Kwella, Niko Pfeifer, Florian Hausler, Jens Pontow, Ilja Radusch, Jochen Hipp, Frank Dölitzscher, Martin Haueis: Deriving HD maps for highly automated driving from vehicular probe data. ITSC 2016: 1745-1752
  • (16) Ahram Song, Yongil Kim, Youkyung Han: Uncertainty Analysis for Object-Based Change Detection in Very High-Resolution Satellite Images Using Deep Learning Network. Remote Sensing 12(15): 2345 (2020)
Selected Articles from Encyclopedia of GIS
Reading List
Spatio-temporal Access Methods
Spatio-Temporal Access Methods: Part 2 (2003 - 2010)
Spatio-temporal access methods: a survey (2010 - 2017)
What is Human Geography?
Five Themes of Geography
Types of Regions
What is GeoInt?
Perspectives on the Cuban Missile Crisis
What is Photogrammetry?
What is Lidar?
Tobler's First Law of Geography
Why Do People Migrate? (Push & Pull Factors)