CS 225 - Spatial Computing

Fall 2021

Time: Tuesday, Thursday - 9:30 AM to 10:50 AM

Location: Olmsted Hall, Room 1212, live and recording links are posted here

Instructor: Amr Magdy - - Office Hours: Thursdays 1pm-2pm Pacific Time. In office or online on Office Hours Links -
Additional asynchronous hours over email or by appointment.

TA: - Office Hours: Mondays 5pm-6pm Pacific Time. Online on Office Hours Links -
Asynchronous hours over email/slack


(If you still cannot access iLearn, 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- UCR Bookstore

Syllabus

Spatial data is ubiquitous in different applications, e.g., map applications, agriculture, public health, transportation, and public safety, and in different scientific disciplines, e.g., geographic information sciences, environmental sciences, and behavioral sciences. This course covers the main concepts behind the existing technologies in spatial applications in addition to the future directions where spatial data is driving innovations. The course introduces spatial computing with coverage for spatial data models, storage, indexing, and querying. In addition, the course allows hands-on experience on both low-level and high-level spatial applications building on existing spatial data platforms. The topics that will be covered include:

  • Introduction to Spatial Computing
  • Spatial Relationships and Data Models
  • Spatial Data Storage and Indexing
  • Spatial Query Processing
  • Spatial Networks
  • Geo-visualization
  • Spatial Data Mining
  • Trends and Innovations in Spatial Applications

Grading

    Course work

  • Project (65%)
  • Hands-on on Spatial Technologies (7.5%)
  • Evaluating others (5%)
  • Paper Reviews (7.5%)
  • Presentation (10%)
  • Final exam (5%)

Online Lecture Links

Schedule

Date Topic  MaterialNotes
Thu 9/23 Course Outline + Introduction to Research
Tue 9/28Introduction to Spatial Computing
Thu 9/30Spatial Relationships and Data ModelsAssignment 0 due
Tue 10/5Spatial Relationships and Data Models (Cont'd) +
Spatial Data Storage and Indexing
Thu 10/7Spatial Data Storage and Indexing +
Spatial Query Processing		Assignment 1 due
Tue 10/12 Spatial Query Processing
Thu 10/14 Paper review 1 discussion + Presentation 1
(Spatial-keyword search)		Assignment 2 due
Tue 10/19 Presentation 2 (Spatio-temporal Databases)
+ Spatial Networks		Assignment 3 due
Thu 10/21 Geovisualization + Presentation 3
Tue 10/26 Geovisualization
Thu 10/28Presentations 4-7
(Geovisualization + Big Data Systems + GPUs)
Tue 11/2Spatial Data Mining + Presentation 8
(GPUs)		Assignment 4 due
Thu 11/4Presentations 9-12
(Spatial crowdsourcing + GeoAI)
Tue 11/9Presentations 13-16 (GeoAI + HD Maps)
Thu 11/11No Lecture for Veterans Day
Tue 11/16 Presentations 17-20
(Remote Sensing)
Thu 11/18 Project presentations + Paper review 2 discussionAssignment 5 due
Tue 11/23 Project presentations
Thu 11/25No Lecture for Thanksgiving
Tue 11/30Project presentations Final project deliverables due
Thu 12/2Trends in spatial applications + Project discussions
Tue 12/7Final Exam

Groups

  Group Members
#1 Baba Skandar Raveendar Vaithlingam,
Malmurugan Sukumar,
Sujith Kumar Sashikanth,
Yash Chinmay Gandhi
#2 Rohit Kumashi,
Subir Jadhav,
Vineet Madhav Naique Dhaimodker
#3 Abdelrahim Hentabli,
Prince Choudhary,
Samuel Tapia,
Shreya Singh,
Suraj Thalari
#4 Abhishek Sharma,
BalaSanjana Thumma,
Gaurav Ratnakar Gadewar,
Roshini Angamgari
#5 Baoju Wang,
Henry Wu,
Tianhan Chen,
Tomal Majumder
#6 Arun Venkatesh,
Baslyos Tesfamariam ,
Ponmanikandan Velmurugan,
Rucha Kolhatkar
#7 Ryan Bruellman,
Joshua Filstrup,
Jean Claude Iradukunda
#8 Adil Ammar Baig Mirza,
Franklin Moses Mahendra Ruban,
Shubham Sharma,
Saloni Kashiv
#9 Jingong Huang,
Guoyao Hao,
Jiajun Yu
#10 Kaushik Sai Kadali,
Sai Teja Pasupulety
#11 Bipin Dhoddamane Ravi,
Utkarsh Neema,
Sarthak Jain,
Deron Martinl

Assignments

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

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
2 Mohamed S. Bakli, Mahmoud Attia Sakr, Esteban Zimanyi: Distributed Spatiotemporal Trajectory Query Processing in SQL. SIGSPATIAL/GIS 2020: 87-98

Presentations

ID# of presentersTopicPresentation ContentAssigned Presenters
1 2 Spatial keyword search Lisi Chen, Shuo Shang, Chengcheng Yang, Jing Li: Spatial keyword search: a survey. GeoInformatica 24(1): 85-106 (2020) Ryan Bruellman, Rohit Kumashi
2 2 Spatio-temporal data Sai Wu, Zhifei Pang, Gang Chen, Yunjun Gao, Cenjiong Zhao, Shili Xiang: NEIST: A Neural-Enhanced Index for Spatio-Temporal Queries. IEEE Transactions Knowledge and Data Engineering 33(4): 1659-1673 (2021) Tomal Majumder, Rucha Kolhatkar
3 2 Geovisualization Yan Zheng, Yi Ou, Alexander Lex, Jeff M. Phillips: Visualization of Big Spatial Data Using Coresets for Kernel Density Estimates. IEEE Transactions on Big Data 7(3): 524-534 (2021) Tianhan Chen, Bipin Dhoddamane Ravi
4 2 Geovisualization 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 Ponmanikandan Velmurugan, Yash Chinmay Gandhi
5 2 Spatial big data platforms Jia Yu, Zongsi Zhang, Mohamed Sarwat: Spatial data management in apache spark: the GeoSpark perspective and beyond. GeoInformatica 23(1): 37-78 (2019) Abhishek Sharma, Gaurav Ratnakar Gadewar
6 2 Spatial big data platforms Varun Pandey, Andreas Kipf, Thomas Neumann, Alfons Kemper: How Good Are Modern Spatial Analytics Systems? Proc. VLDB Endow. 11(11): 1661-1673 (2018) Utkarsh Neema, Prince Choudhary
7 2 Spatial data on GPUs Zhila Nouri, Yi-Cheng Tu:GPU-based parallel indexing for concurrent spatial query processing. SSDBM 2018: 23:1-23:12 Joshua Filstrup, Sai Teja Pasupulety
8 2 Spatial data on GPUs Harish Doraiswamy, Juliana Freire: A GPU-friendly Geometric Data Model and Algebra for Spatial Queries. SIGMOD Conference 2020: 1875-1885 Sarthak Jain, Kaushik Sai Kadali
9 2 Spatial crowdsourcing Yongxin Tong, Zimu Zhou, Yuxiang Zeng, Lei Chen, Cyrus Shahabi: Spatial crowdsourcing: a survey. VLDB Journal 29(1): 217-250 (2020) Vineet Madhav Naique Dhaimodker, Subir Jadhav
10 2 Spatial crowdsourcing Ting Wang, Xike Xie, Xin Cao, Torben Bach Pedersen, Yang Wang, Mingjun Xiao: On Efficient and Scalable Time-Continuous Spatial Crowdsourcing. ICDE 2021: 1212-1223 Roshini R Angamgari, Deron Martin
11 2 GeoAI Beibei Wang, Youfang Lin, Shengnan Guo, Huaiyu Wan: GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting. AAAI 2021: 4402-4409 Adil Ammar Baig Mirza, Franklin Moses Mahendra Ruban
12 2 GeoAI Zhe Jiang, Wenchong He, Marcus Stephen Kirby, Sultan Asiri, Da Yan: Weakly Supervised Spatial Deep Learning based on Imperfect Vector Labels with Registration Errors. KDD 2021: 767-775 Baoju Wang, Arun Venkatesh
13 2 GeoAI Qiyu Liu, Yanyan Shen, Lei Chen: LHist: Towards Learning Multi-dimensional Histogram for Massive Spatial Data. ICDE 2021: 1188-1199 Jiajun Yu, Malmurugan Sukumar
14 2 GeoAI Byungseok Roh, Wuhyun Shin, Ildoo Kim, Sungwoong Kim: Spatially Consistent Representation Learning. CVPR 2021: 1144-1153 Jingong Huang, Guoyao Hao
15 2 HD Maps Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Congcong Li, Cordelia Schmid: VectorNet: Encoding HD Maps and Agent Dynamics From Vectorized Representation. CVPR 2020: 11522-11530 Suraj Thalari, Baslyos Tesfamariam
16 2 HD Maps Andi Zang, Shiyu Luo, Xin Chen, Goce Trajcevski: Real-Time Applications Using High Resolution 3D Objects in High Definition Maps (Systems Paper). SIGSPATIAL/GIS 2019: 229-238 Shreya Singh, Baba Skandar Raveendar Vaithlingam
17 2 Remote Sensing 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. Henry Wu, Jean Claude Iradukunda
18 2 Remote Sensing 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) 		Shubham Sharma, Saloni Kashiv
19 2 Remote Sensing 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. BigData 2019: 5644-5653 Samuel Tapia, Abdelrahim Hentabli
20 2 Remote Sensing Wei Su, Daniel Z. Sui, Xiaodong Zhang: Satellite image analysis using crowdsourcing data for collaborative mapping: current and opportunities. International Journal of Digital Earth 13(6): 645-660 (2020) BalaSanjana Thumma, Sujith Kumar Sashikanth

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)