Geospatial Analysis for Urban Applications with GIS and a bit of Python
Unlock the full potential of GIS by analyzing practical urban applications
Do you already have a GIS background but want to grasp its full capabilities?
Do you want to take your first steps away from commercial GIS software to independent scripting?
Are you a smart city enthusiast and you want to understand how to analyze urban problems to build useful applications?
Then this course is for you!
Join me in this 2.5 hour course we will unlock more than enough tools and algorithms to highlight and analyze urban problems. Well packed with their background theory so that you don’t miss anything and that you also become ready to further delve into them and a 10 question quiz to test your knowledge!
Enroll now and let’s get to work!
€30,00
Regular price
Lesson 3: Vector datasets: Administrative boundaries, street network and Urban atlas
Lesson 4: Raw satellite data: Sentinel 2 multispectral imagery
Lesson 5: Creating and organizing a geodatabase
Lesson 6: Setting up a topology
Lesson 7: Validating the topology
Lesson 8: Geocoding addresses with Google MyMaps
Lesson 9: Importing a dataset into python for geocoding
Lesson 10: Geocoding with geopy and creating an output shapefile
Lesson 11: Exporting the shapefile
Lesson 12: OpenWeatherMap API for meteorological data: Making the call
Lesson 13: OpenWeatherMap API for meteorological data: Importing and visualizing in GIS
Lesson 14: Kids in danger: Locating schools closest to most traffic accidents
Lesson 15: A simple locationing problem
Lesson 16: Fundamental statistics aspects: Random variables, probability functions, common distributions and the Normal distribution
Lesson 17: Fundamental statistics aspects: Hypothesis testing, statistical significance, results interpretation and spatial statistics metrics
Lesson 18: Preparing the data: Attribute filling with Arcpy and generating spatial weights
Lesson 19: Global spatial autocorrelation: Moran’s I for traffic accidents’ time zones
Lesson 20: Local autocorrelation and clustering: Getis – Ord’s Gi* and Anselin’s Local Moran’s I
Lesson 21: Calculating global spatial autocorrelation with PySAL
Lesson 22: Calculating and visualizing local autocorrelation with PySAL and matplotlib
Lesson 23: Introduction: Why and what is Remote Sensing?
Lesson 24: Preparing the data: Auxiliary vector data and automatic clipping of rasters
Lesson 25: Mapping urban green with NDVI
Lesson 26: Detecting informal settlements with unsupervised classification
Lesson 27: Automating procedures with Model Builder
Lesson 28: What is a network dataset?
Lesson 29: Preparing the data: Building our network
Lesson 30: Generating service areas for Super Markets
Lesson 31: Calculating accessibility to green open spaces
Lesson 32: Discussion, key takeaways, possible future courses
Discussion with your Personal Virtual Instructor!
Test your knowledge
Data analysis in the urban scales to highlight problematic areas and inequalities
Basic to advanced functionality of most GIS tools that are useful for urban geospatial analysis
Use of Model Builder and arcpy to unlock the full potential of GIS
Use of independent python scripts to supplement your GIS work and build the confidence to make your own algorithms
Satellite image processing using python
An ArcGIS desktop license
Familiarity with basic GIS tools and features
Understanding of basic scripting principles, such as variables, loops etc. (optional)
Under/post graduate students
Professionals and Companies
Master students and PhD candidates
Researchers and Academics