Geospatial Data Science in Python
Syllabus
Schedule
Section 401
Section 402
Content
Assignments
Overview
Section 401
Section 402
Resources
GitHub
Canvas
Ed Discussion
14. Advanced Raster Analysis
Weekly Course Content
1. Exploratory Data Science in Python
2. Data Visualization Fundamentals
3. More Interactive Data Viz, Intro to Vector Data & GeoPandas
4. Geospatial Analysis & Mapping
5. More Geospatial Analysis: Street Networks and Raster Data
6. Web Scraping
7. Working with APIs
8. Analyzing and Visualizing Large Datasets
9. From Notebooks to the Web: Part 1
10. From Notebooks to the Web: Part 2
11. Clustering Analysis in Python
12. Predictive Modeling with Scikit-Learn, Part 1
13. Predictive Modeling with Scikit-Learn, Part 2
14. Advanced Raster Analysis
On this page
Two Case Studies
Interesting Readings and Maps
References
Week 14: Advanced Raster Analysis
Content for lectures 14A and 14B
View materials:
MUSA-550-Fall-2023/week-14
HTML slides:
Lecture 14A
Lecture 14B
Executable slides:
Lecture 14A
Lecture 14B
Two Case Studies
Using satellite imagery to detect changes in lake volume
Detecting urban heat islands in Philadelphia
Interesting Readings and Maps
Redlining and Urban Heat Islands (NYT)
Redlining in Philadelphia
Redlining and Street Trees (NYT)
Mapping Inequality: Philadelphia
References
EarthML
The Disappearing Walker Lake
The Aral Sea
Lake Orumiyeh
Urban Heat Islands
EarthML Tutorial on Heat Island
Slicing with xarray
Slicing in Python
rio-toa: Top Of Atmosphere (TOA) calculations for Landsat 8
rioxarray
Landsat data on Google Cloud Storage
Google Earth Engine (GEE):
Documentation
Data Catalog
Landsat data on Google Earth Engine
GEE Guides
Examples of Python packages for GEE
geemap
package:
Documentation
GEE tutorials
Example notebooks with videos
13. Predictive Modeling with Scikit-Learn, Part 2