Practical Python Code Examples for GIS Applications

Advance your Skills!

Become a stronger and more competitive GIS professional

Welcome everyone! If you are in the field of GIS/Remote Sensing, you are probably hearing everyone talking about Python and its usefulness in various GIS related tasks.

GIS and Remote Sensing are one of the most integrated fields combining skills from different areas such as Computer Science, Engineering, Geography, Mathematics, etc.

To become  a stronger and more competitive GIS professinal and to increase your value in the GIS industry you need to learn how to program. Python  is one of the most spreading programming languages in the IT world and with huge usability in the GIS/Remote Sensing field. You can find many articles mentioning why Python is the future of GIS and how you can get a more competitive salary1 just by learning how to use Python routines.

Pricing - Lifetime Access

Become a Successful GIS/Remote Sensing Professional

According to the IEEE Spectrum ( Python is the top ranked programming language!
Become a Successful GIS/Remote Sensing Professional

Course curriculum

  • 02
    Working With Vector Data
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    • Lesson 2: Reading and Writing Vector Data (30 pages with code examples)
    • Lesson 3: Geometries and Projections (28 pages with code examples)
    • Lesson 4: Analysis of Vector Data (28 pages with code examples)
  • 03
    Working With Raster Data
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    • Lesson 5: Reading and Writing Raster Data (32 pages with code examples)
    • Lesson 6: Raster Algebra (26 pages with code examples)
    • Lesson 7: Raster Analysis and Processing (23 pages with code examples)
  • 04
    Command Line Utilities
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    • Lesson 8: GDAL & OGR Command Line Recipes (29 pages with code examples)
  • 05
    Bonus Use Cases
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    • Example Data
    • Lesson 9: Calculate Bounding Box
    • Lesson 10: Create Shapefile From Bounding Box
    • Lesson 11: Calculate the Histogram of a DEM File
    • Lesson 12: Reproject & Merge Shapefiles
    • Lesson 13: Export & Save Geometries to Text
    • Lesson 14: Calculate Shapefile Dimensions

What will you learn?

  • Handle I/O Processes

  • Process Vector Data

  • Perform Raster Algebra Algorithms

  • Spatial Analysis with Vector Data

  • Process & Analyze Raster Data

  • Learn Prototyping with GDAL, Numpy, OGR and Command Line

Any Prerequisites?

  • Basic Python knowledge and scripting familiarity

  • Basic GIS/Remote Sensing Knowledge

  • Willingness to Learn New Things & Experiment

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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 am a Remote Sensing and a Surveying Engineer. I received my Diploma in the Department of Rural and Survey Engineering from the National Technical University of Athens (NTUA), where I also received my M.Sc. in the domain of Geoinformatics and Remote Sensing.From the beginning of 2013 I am working as a GIS and Photogrammetry Expert in the private sector offering support and solutions in GIS, Remote Sensing and Photogrammetry applications. Also, from 2013 I am a Research Assistant in the Laboratory of Remote Sensing of National Technical University of Athens (NTUA). I have actively participated in more than 10 funded European Commission and European Space Agency projects and I have more than 15 peer reviewed scientific publications in journals and conferences.I have experience in the fields of the state of the art technologies in WebGIS, remote sensing, data processing, multispectral images, radar, big data, data mining and machine learning algorithms. My main areas of research are the automated procedures/classification algorithms for land cover/uses mapping. Some of the software tools I operate in common basis for geospatial applications are: ERDAS IMAGINE suite, QGIS, ESRI suite and Python.

    Dimitris Bliziotis

    GIS and Photogrammetry Expert

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