GIS Day: GeoPython Using Google Colab Notebooks Export this event to calendar

Wednesday, November 20, 2024 — 1:30 PM to 2:20 PM EST

Date: Wednesday November 20, 2024
Time: 1:30 – 2:20 p.m. 
Location: Dana Porter Library, Room 323 
Facilitator: Alex Smith 

Google Colab with the GeoPandas Python package is an effective platform for GIS analysis. This introductory workshop, a combination of presentation, demonstration, and question & answer session, will showcase how users can load, project, query and visualize GIS data through graphs and maps.  

By the end of this workshop, participants will have: 

  • Introductory knowledge of how to load, project, query and visualize GIS data 

  • Some insight into future directions of where this platform could be taken 

  • An understanding of the benefits and drawbacks of GIS analysis with Google Colab 

To participate, please bring a laptop and have a Google account. 

This in-person workshop has limited capacity; please register to reserve your seat. If you have accommodation requests or questions, reach out to Eva Dodsworth (edodsworth@uwaterloo.ca) with your needs.

Register now

Facilitator: Alex Smith is a Higher Education Specialist at Esri Canada. He focuses on managing the Esri Canada GIS Centres of Excellence, developing spatial data science resources and conducting research projects. He first began working with ArcGIS products in high school but had a more formal introduction while studying Geomatics at the University of Waterloo. A fourth-year project led to a Master of Science degree focusing on the classification of land use and cover using machine learning techniques. Alex then went on to complete his doctorate at Simon Fraser University, writing his thesis on agent-based modelling and spatial statistics in three-dimensional space plus time. 

Location 
Dana Porter Library
Room 323
200 University Avenue West

Waterloo, N2L 3G1
Canada

S M T W T F S
27
28
29
30
31
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
  1. 2024 (49)
    1. November (11)
    2. October (12)
    3. September (1)
    4. June (2)
    5. May (1)
    6. March (9)
    7. February (8)
    8. January (5)
  2. 2023 (31)
    1. November (6)
    2. October (13)
    3. September (2)
    4. June (1)
    5. May (4)
    6. April (1)
    7. March (1)
    8. February (3)
  3. 2022 (11)
  4. 2021 (37)
  5. 2020 (68)
  6. 2019 (90)
  7. 2018 (208)
  8. 2017 (115)
  9. 2016 (59)
  10. 2015 (71)
  11. 2014 (44)