/scalable_spatial_analytics

Grad Course (2020), CE 263N – Scalable Spatial Analytics

Primary LanguageJupyter Notebook

scalable_spatial_analytics

Grad Course, CE 263N – Scalable Spatial Analytics

Course Description: Learned techniques for analyzing human dynamics (daily activities and travels) and their interactions with the built and the natural environments.

File Descriptions:

  1. hw1.ipynb – composed and analyzed three empirical networks, examining for small world network properties
  2. hw2.ipynb – modeled trip distributions of US commuter data with singly constrained gravity and radiation models, as well as analyzed network properties
  3. hw3.ipynb – analyzed human mobility trajectories
  4. hw4.ipynb – decomposed eigenbehaviors and energy consumption with PCA
  5. project.ipynb – analyzed the vulnerability of the Bay Area water supply network
  6. Final Presentation.pdf – ppt presentation on project.ipynb
  7. final_paper.pdf – written report analyzing the vulnerability of the Bay Area water supply network