CS 225 - Spatial Computing
Fall 2020
Time: Tuesday, Thursday - 9:30 AM to 10:50 AM
Location: Online, links posted on iLearn course materials, click here for details
Instructor: Amr Magdy -
- Office Hours: Asynchronous hours over email and online hours on Office Hours Links -
Wednesdays 5-6 pm Pacific Time
TA:
- Office Hours: Asynchronous hours over email/slack and online hours on Office Hours Links -
Mondays 5-6 pm Pacific Time
(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
- Project (65%)
- Hands-on on Spatial Technologies (7.5%)
- Evaluating others (5%)
- Paper Reviews (7.5%)
- Presentation (10%)
- Final exam (5%)
Course work
Online Lecture Links
- First lecture: https://ucr.zoom.us/j/92613789038?pwd=Wlo5Y2hLeTFldU1tazlpMkVQWFc5UT09
- Rest of lectures: Links Posted on iLearn Course Materials, click here for details.
- Additional Zoom options: You can join Zoom meetings through alternative options, click here for details.
Lecture Links
Schedule
| Date | Topic | Material | Notes |
|---|---|---|---|
| Thu 10/1 | Course Outline + Introduction to Research | ||
| Tue 10/6 | Introduction to Spatial Computing | ||
| Thu 10/8 | Spatial Relationships and Data Models | Assignment 0 due | |
| Tue 10/13 | Spatial Relationships and Data Models (Cont'd) + Spatial Data Storage and Indexing | ||
| Thu 10/15 | Spatial Data Storage and Indexing + Paper review 1 discussion | Assignment 1 due | |
| Tue 10/20 | Spatial Query Processing | ||
| Thu 10/22 | Spatial Query Processing + Presentation 1 (Spatial-keyword search) | ||
| Tue 10/27 | Presentations 2-3 (Spatio-temporal Databases) | Assignment 2 due | |
| Thu 10/29 | Spatial Networks + Presentation 20 (Remote Sensing) | ||
| Tue 11/3 | Geovisualization + Presentation 5 | ||
| Thu 11/5 | Spatial Data Mining + Presentation 6 (Geovisualization) | ||
| Tue 11/10 | Presentations 4,7-8 (Spatio-temporal Data Mining + Spatial big data platforms) | ||
| Thu 11/12 | Presentations 9-10 (Spatial data on GPUs) + Paper review 2 discussion | Assignment 3 due | |
| Tue 11/17 | Presentations 11-12 (Spatial crowdsourcing) | ||
| Thu 11/19 | Presentations 13-16 (GeoAI) | ||
| Tue 11/24 | Presentations 17-19,21 (HD Maps + GeoAI + Remote Sensing) | ||
| Thu 11/26 | No Lecture for Thanksgiving Thursday | ||
| Tue 12/1 | Presentations 22-25 (Remote Sensing) | ||
| Thu 12/3 | Trends in Spatial Technologies | Assignment 4 due | |
| Tue 12/8 | Final project fast-forward presentations | ||
| Thu 12/10 | Final project fast-forward presentations | ||
| Wednesday 12/16 and Thursday 12/17 | Final Exam + Final project discussions | Final project deliverables due | |
Groups
| Group Members | |
|---|---|
| #1 | Anjali Ramchandani, Gowtham Tumati, Lovepreet Singh dhaliwal, Sudip Bala |
| #2 | Arman Irani, Duc Nguyen, Keith Zmudzinski, Pedro Valdivia, Wijdan Alsurayya |
| #3 | Dongdong Hou, Jie Lin, Songrui He, Yiyuan Liu, Zhizhi Wang |
| #4 | Erin Wong DeForest, Fedah Alanazi, Francisco Gallego, Majid Saeed Ali Saeedan, Mariana Machado Garcez Duarte |
| #5 | Jiapeng Wang, Qicheng Hu, Wei-Ting Chang, Xinning Dong, Yuanbin Cheng |
| #6 | Bocheng Li, Ian-chin Wang, Tianshu Qin, Yao Chun Chan, Yingnan Zhang |
| #7 | Aravind Sainathan, Divyanshi Srivastava, Gyan Prakash, Rohit Chugh |
| #8 | Chunhan Zhang, Song Bai, Yuanjie Zhu, Zhengyi Qu, Ziliang Zhang |
| #9 | ChiaTien Tsai, Hung Chih Ni, Tzu-Ching Chuang, Wei-De Dai |
| #10 | Chiyuan Ma, Hui Su, Lisa Chen, Xinxin Xie, Yue Lu |
| #11 | Cheng Chen, Haide He, Jiaojiao Cheng, Youkun Wu |
| #12 | Chuliang Zhang, Jiahao Ge, Yuxi Dong, Zeyu Pang |
| #13 | Jatin Patwa, Mohammad Reza Zare Shahneh, Mohammadreza Rezvani, Shreshta Vinayak |
Paper Reviews
| # | Paper Title |
|---|---|
| 1 | "An Investigation of Grid-enabled Tree Indexes for Spatial Query Processing" Jaewoo Shin, Ahmed R. Mahmood, Walid G. Aref. In ACM SIGSPATIAL 2019, p.169-178. |
| 2 | "Efficient Processing of Spatial Group Keyword Queries" Xin Cao, Gao Cong, Tao Guo, Christian S. Jensen, Beng Chin Ooi. ACM Transactions on Database Systems. 40(2): 13:1-13:48 (2015). |
Presentations
| ID | # of presenters | Topic | Presentation Content | Assigned 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) | Tianshu Qin, Xinxin Xie |
| 2 | 4 | Spatio-temporal data | Tamas Abraham, John F. Roddick: Survey of Spatio-Temporal Databases. GeoInformatica 3(1): 61-99 (1999) | Cheng Chen, Haide He, Ian-chin Wang, Zhizhi Wang |
| 3 | 4 | Spatio-temporal data | Ahmed R. Mahmood, Sri Punni, Walid G. Aref: Spatio-temporal access methods: a survey (2010 - 2017). GeoInformatica 23(1): 1-36 (2019) | Chuliang Zhang, Jiahao Ge, Yuxi Dong, Zeyu Pang |
| 4 | 4 | Spatio-temporal data | 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) | Gowtham Tumati, Mariana Machado Garcez Duarte, Qicheng Hu, Sudip Bala |
| 5 | 2 | Geovisualization | Jia Yu, Mohamed Sarwat: Turbocharging Geospatial Visualization Dashboards via a Materialized Sampling Cube Approach. ICDE 2020: 1165-1176 | Divyanshi Srivastava, Yingnan Zhang |
| 6 | 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 | Jiapeng Wang, Songrui He |
| 7 | 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) | Jie Lin, Yiyuan Liu |
| 8 | 2 | Spatial big data platforms | Dong Xie, Feifei Li, Bin Yao, Gefei Li, Liang Zhou, Minyi Guo: Simba: Efficient In-Memory Spatial Analytics. SIGMOD Conference 2016: 1071-1085 | Lovepreet Singh dhaliwal, Majid Saeed Ali Saeedan |
| 9 | 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 | Chunhan Zhang, Yuanbin Cheng |
| 10 | 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 | Dongdong Hou, Song Bai |
| 11 | 4 | Spatial crowdsourcing | Yongxin Tong, Zimu Zhou, Yuxiang Zeng, Lei Chen, Cyrus Shahabi: Spatial crowdsourcing: a survey. VLDB Journal 29(1): 217-250 (2020) | Gyan Prakash, Rohit Chugh, Tzu-Ching Chuang, Ziliang Zhang |
| 12 | 4 | Spatial crowdsourcing | 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) | Anjali Ramchandani, Francisco Gallego, Lisa Chen |
| 13 | 2 | GeoAI | Mike Izbicki, Vagelis Papalexakis, Vassilis J. Tsotras: Geolocating Tweets in any Language at any Location. CIKM 2019: 89-98 | Fedah Alanazi, Yuanjie Zhu |
| 14 | 2 | GeoAI | 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 | Erin Wong DeForest, Keith Zmudzinski |
| 15 | 2 | GeoAI | Ibrahim Sabek, Mohamed F. Mokbel: Sya: Enabling Spatial Awareness inside Probabilistic Knowledge Base Construction. ICDE 2020: 1177-1188 | Mohammad Reza Zare Shahneh, Mohammadreza Rezvani |
| 16 | 2 | GeoAI | 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) | Chiyuan Ma, Yue Lu |
| 17 | 2 | GeoAI | 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 | Wei-Ting Chang, Xinning Dong |
| 18 | 2 | HD Maps | 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 | ChiaTien Tsai, Youkun Wu |
| 19 | 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 | Hung Chih Ni, Wei-De Dai |
| 20 | 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. | Bocheng Li, Pedro Valdivia |
| 21 | 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) |
Shreshta Vinayak, Jatin Patwa |
| 22 | 2 | Remote Sensing | 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 | Jiaojiao Cheng, Yao Chun Chan |
| 23 | 2 | Remote Sensing | Csaba Benedek: 3D people surveillance on range data sequences of a rotating Lidar. Pattern Recognition Letters 50: 149-158 (2014) | Aravind Sainathan, Hui Su |
| 24 | 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 | Duc Nguyen, Zhengyi Qu |
| 25 | 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) | Arman Irani, Wijdan Alsurayya |
Course Resources
| 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) |