Analysis of Urban Transformation Processes: Part 1 - Python and Earth Observation Data
NFDI4EarthXRUB
About This Course
The course "Analysis of Urban Transformation Processes: Python and Earth Observation Data" introduces participants to the use of Python and Earth Observation data to analyze and visualize various urban transformation processes. Participants will learn to filter and select feature and image collections, perform needed analytical metrics, and interpret spatial data using Google Earth Engine (GEE). Key topics include flood detection with Sentinel-1 data, nighttime light trend analysis, and air quality measurement using Sentinel-5p data. Through practical examples and exercises, participants will gain hands-on experience in urban analysis and environmental monitoring (Access this course on GitLab).
Level
Intermediate, Advanced
Requirements
Basic knowledge of Python, digital image processing and Geographic Information Systems is required.
Subject Area
Land System Science, Geography, Remote Sensing, Earth Observation, GI Science, Urban Planning
What You Will Learn
- Introduction and Preparation
- Feature Collection Basics
- Image Basics & Filters: Landuse Extraction
- Landcover Extraction
- Create Timelapse GIFs from Landsat Satellite Data
- Flood Detection
- Air Quality Assessment
- Nighttime Light Trends
Resources
EduPilot "The future is urban, the data is smart" by Andreas Rienow and Lars Tum