You know that you are into GIS, but not sure where to specialize?

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!

Pricing - Lifetime Access

Learn geospatial analysis with GIS and Python and boost your knowledge and skills.

Understand almost all of the necessary tools to analyze urban planning problems
Enroll now and advance your skills

Course curriculum

  • 02

    Useful datasets for urban analysis

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    • Lesson 3: Vector datasets: Administrative boundaries, street network and Urban atlas
    • Lesson 4: Raw satellite data: Sentinel 2 multispectral imagery
  • 03

    Data quality and topology

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    • Lesson 5: Creating and organizing a geodatabase
    • Lesson 6: Setting up a topology
    • Lesson 7: Validating the topology
  • 04

    Geocoding and data from APIs

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    • 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
  • 05

    Standard geoprocessing tools

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    • Lesson 14: Kids in danger: Locating schools closest to most traffic accidents
    • Lesson 15: A simple locationing problem
  • 06

    Introduction to Spatial statistics

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    • 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
  • 07

    Employing Satellite imagery

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    • 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
  • 08

    Introduction to Network Analyst

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    • 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
  • 09

    Conclusions

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    • Lesson 32: Discussion, key takeaways, possible future courses
    • Discussion with your Personal Virtual Instructor!
    • Test your knowledge

What will you learn?

  • 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

Any prerequisites

  • An ArcGIS desktop license

  • Familiarity with basic GIS tools and features

  • Understanding of basic scripting principles, such as variables, loops etc. (optional)

GEO Premium

Access our ENTIRE content with a yearly subscription only 8$/month

1 Year Access

Student Profile?

  • Under/post graduate students

  • Professionals and Companies

  • Master students and PhD candidates

  • Researchers and Academics

Some more information

  • Based on Block-chain Certificates of Completion

    After you successfully finish the course, you can claim your Certificate of Completion with NO extra cost! You can add it to your CV, LinkedIn profile etc

  • Available at any time! Study at your best time

    We know hard it is to acquire new skills. All our courses are self paced.

  • Online and always accessible

    Even when you finish the course and you get your certificate, you will still have access to course contents! Every time an Instructor makes an update you will be notified and be able to watch it for FREE

About your Instructor

I'm a Remote Sensing and a Surveying Engineer. I received my degree from NTUA in 2010, where I also received my Ph.D. in hyperspectral remote sensing in 2016. From graduation in 2010, my career started as a Researcher Associate and Teaching Associate in the Laboratory of Remote Sensing of NTUA. From that time I also worked at several private companies as a Remote Sensing Expert and Geospatial Analyst. From the beginning of 2015 I was positioned as Senior Earth Observation Expert. During these years, I have participated in more than 20 funded European Commission and European Space Agency projects, have over 16 peer reviewed scientific publications in the field of Remote Sensing, and have an international patent in hyperspectral data compression.My main research and professional interests are in the optical remote sensing area, where I specialize in data (images, point measurements) processing and algorithm design and development. Some of the software tools that I operate to accomplish my research and business dreams are SNAP, ENVI, IDL, QGIS, ERDAS Imagine, ArcGIS, and Python. I have been working with these tools since 2008.

Dimitris Sykas

Remote Sensing Expert

Dimitris Sykas