Summary and Schedule
This is a new lesson built with The Carpentries Workbench.
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. Census Geocoding |
What is geocoding and why is it essential for census analysis? How can we convert addresses into spatial coordinates? How do we combine census data with OpenStreetMap features? How can spatial context improve demographic analysis? |
| Duration: 01h 42m | 2. Network Analysis |
How do we download and visualize road networks with OSM data? What is a graph network and how is it represented in Python? How can we compute shortest paths and network distances? |
| Duration: 03h 24m | 3. Spatial Analysis |
What is PySAL and what can it do for spatial analysis? How do we compute spatial weights and perform spatial autocorrelation? How do we interpret results like Moran’s I? |
| Duration: 05h 05m | 4. Spatial Clustering |
What is spatial clustering and why do we use it? How can we perform basic clustering on geographic point data? How do algorithms like K-Means, Hierarchical Clustering, and DBSCAN differ? |
| Duration: 06h 46m | 5. NDVI Analysis |
What is NDVI and why is it useful? How do we calculate NDVI from Landsat imagery? How do we load and visualize raster data in Python? How can we classify and map greenness using NDVI? |
| Duration: 08h 48m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
FIXME: Setup instructions live in this document. Please specify the tools and the data sets the Learner needs to have installed.
Data Sets
Download the data zip file and unzip it to your Desktop
Software Setup
Details
Setup for different systems can be presented in dropdown menus via a
spoiler tag. They will join to this discussion block, so
you can give a general overview of the software used in this lesson here
and fill out the individual operating systems (and potentially add more,
e.g. online setup) in the solutions blocks.
Use PuTTY
Use Terminal.app
Use Terminal