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INTRODUCTION TO GEOSPATIAL DATA SCIENCE (video course)
INTRODUCTION TO GEOSPATIAL DATA SCIENCE (video course)
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INTRODUCTION TO GEOSPATIAL DATA SCIENCE (video course)
– Vector Data Edition
About
This nearly two and a half hour pre-recorded course aims to give a comprehensive overview of getting started in geospatial data science using Python. The course covers the key concepts of spatial analytics, such as geometries and coordinate reference systems, different types of geometric data, such as road networks and building footprints, and map status and interactive visualizations. Attention - this is a fully hands-on Python course with a main focus on vector data.
The course includes 4 pre-recorded subtitled videos with and the entire code base discussed during class in live and revised versions.
When
Whenever you want - this is a pre-recorded online course.
Benefits
This course aims to get you fully on board in the Pythonic world of geospatial data science, allowing you to process, analyze, and visualize geospatial vector data in Python.
Prerequisites
This course is in Python. Hence, basic knowledge of Python is highly recommended.
Outline
The course consists of the following chapters:
Geometries - The Building Blocks of Spatial Analytics (15min)
GeoPandas in Practice - The Spatial Swiss Knife (29min)
Collecting and Exploring Vector Data - OpenStreetMap (53min)
Geospatial Features and some Urban Analytics (41min)
Setting up
To fully enjoy this course, you need to install a Python version, preferably in a Jupyter Notebook environment. Additionally, you will need to install several Python libraries, the versions of which are listed in the requirements.txt file.
https://jupyter.org
Detailed outline
1. Geometries - The Building Blocks of Spatial Analytics
- Onboarding to geometries - Shapely, imports, basic geometry types
- Geometry operations - buffering, set operations, and others
2. GeoPandas in Practice - The Spatial Swiss Knife
- Onboarding to GeoPandas - imports, versions, sample data, Natural Earth, GeoDataFrames
- Simple functions and computations - creating new geo features, statistics, histograms, correlations
- Visualizing sample data with GeoPandas - basic statistics, color maps, log scaling
- CRS and map projections - local and global coordinate reference systems
3. Collecting and Exploring Vector Data - OpenStreetMap
- OpenStreetMap
- Download data with OSMNx - polygons, footprints, POIs, road networks, computational exercises
- Combined map visualization - multiple layers, base maps, deriving complex urban features
- Interactive visualizations - Folium
4. Geospatial Features and Urban Analytics
- Download all districts for Budapest - downloading, storing, parsing, and merging data
- Urban feature engineering - road networks, density, and distance-based metrics
- Automate feature generation
After your purchase we'll send a link to the course files.