| Sno | Lecture Topics | Slides and relavant material | Important Due Dates* |
|---|---|---|---|
| 1 | Introduction | Lecture Slides, Course Projects |
|
| 2 | Fundamental spatial concepts | Lecture SlidesP1,Lecture SlidesP2 | |
| 3 | Representation and Algorithms (I) | Lecture SlidesP1,Lecture SlidesP2 Paper on Raster thining Supp material on polygon triangulation |
Initial proposal of course project (Aug-21), Prospoal instructions |
| 4 | Representation and Algorithms (II) | Lecture SlidesP1,Lecture SlidesP2 Supp material on Fortune Algorithm |
Homework 1 is due |
| 5 | Spatial query languages | Lecture Slides Courtesy Shekhar et. al. UMN |
|
| 6 | Spatial indexing techniques (I) | Lecture Slides | Homework 2is due |
| 7 | Midterm Examination week (Sept-21 -- Sept-26) | Practice Questions | |
| 8 | Spatial indexing techniques (II) | Lecture Slide P1, Lecture Slides P2 comparing Rtree and Quad tree |
|
| 9 | Midterm Project reviews (Oct-5 -- Oct-10) | Presentation schedule for teams | |
| 10 | Spatial networks (I) | Lecture Slides Courtesey Shekhar et. al. UMN |
|
| 11 | Mid-sem Recess (Oct-19 -- Oct-24) | ||
| 12 | Spatial networks (II) | Lecture slides | |
| 13 | Spatial data mining | Lecture slides Courtesey Shekhar UMN paper on scan statistic Refer first 5 pages (till Section 3.1) of the paper Presentation on Moran's I |
Homework 3 is due. |
| 14 | Trends Topics | Spatio-temptoral Graphs Engine Big Data |
|
| 15 | Final exam and Project presentations (Nov-23 -- Dec-4) |