Geospatial data analysis with python

Learn how to read, write and visualize the raster/vector dataset and perform spatial analysis using python

4.50 (88 reviews)
Udemy
platform
English
language
Other
category
401
students
4.5 hours
content
Mar 2024
last update
$44.99
regular price

What you will learn

Reading and writing of geospatial data

Visualization of geospatial data using python

Benefits of python over GIS software

Resampling, reprojection, reclassification of data

Most essential geospatial libraries

Essential things for geopandas, fiona, shapely, rasterio etc

Description

Geospatial data is also known as spatial data. It contains the locational information of the things or objects. In this course, we are going to read the data from various sources (like from spatial database) and formats (like shapefile, geojson, geo package, GeoTIFF etc), perform the spatial analysis and try to find insights for spatial data. In this course, we lay the foundation for a career in the Geospatial community.


Here is the list of topics that I covered in this course,

  • Installation of required geospatial libraries (GDAL, GeoPandas, rasterio, fiona, shapely, pandas, numpy etc)

  • Reading and Writing the spatial data from various sources/formats

  • Visualization of geospatial data using python

  • Working with the attribute table and geometries

  • Resampling, Reprojection, and Reclassification of satellite data

  • Mathematical operation with Raster

  • NDVI calculation using NIR and RED band


Here are the introductions to the main topics that are covered in this course:


GeoPandas: It is the open-source python package for reading, writing and analyzing the vector dataset. It extends the datatypes used by pandas to allow spatial operations on geometric types. It further depends on fiona for file access and matplotlib for visualization of data.


Rasterio: It is a GDAL and Numpy-based Python library designed to make your work with geospatial raster data more productive, and fast. Rasterio reads and writes raster file formats and provides a Python API based on Numpy N-dimensional arrays and GeoJSON.


Shapely: It is the open-source python package for dealing with the vector dataset.


Fiona: It can read and writes geographic data files and thereby helps Python programmers integrate geographic information systems with other computer systems. Fiona contains extension modules that link the Geospatial Data Abstraction Library (GDAL).


Each section contains a summary and a walkthrough with code examples that will help you learn more effectively. After completing this course, you will be confident to do the spatial analysis by python. You can automate the processing of your geospatial data without GIS software (eg. ArcGIS, QGIS etc).

Content

Introduction

Course intro
Introduction to google colab
Notebooks for this course

Vector data analysis

Overview of this section
required dataset
Installation of geopandas
Reading vector data
Reading the metadata of the geodataframe
Visualization of vector data
writing vector data
Working with attribute table
Working with geometry (Shapely)
Dissolve municipality into district

Case study on vector data

Notebook for this course
Statement of problem
Solution

Basic of raster data analysis

Land cover data download (optional)
Rasterio installation
Reading raster dataset
Reading metadata of raster
Visualization of raster data
Writing tiff file
Mathematical operation with raster

Raster data analysis (Advance)

Masking the tiff file with shapefile
Raster reclassification
Raster resampling
Raster reprojection
NDVI calculation
Correction on NDVI calculation
Bonus lecture

Screenshots

Geospatial data analysis with python - Screenshot_01Geospatial data analysis with python - Screenshot_02Geospatial data analysis with python - Screenshot_03Geospatial data analysis with python - Screenshot_04

Reviews

Tristan
June 2, 2023
i like how the course gets straight into it, no boring stuff about syntax and the google colab is really easy to use compared to idle like some of the courses have for arcpy. i want to get off arcpy adn esri so this is good
David
September 6, 2022
It's a good course. I hoped that it would start with a guide to installing the packages in my pc since I dont intend to work with google collab in the future and the installation of some of this packages has proven to be troublesome. Besides that it is what I expected.
Gaurav
February 18, 2022
Amazing course. I would suggest everyone to look after this course. A great effort from Tek dai to deliver this course.
Abdulhaffiz
August 8, 2021
A very comprehensive and interesting course. The instructor's pace and guidance is great, once I started, I couldn't do anything else until I finished the course. The assignments are also curated to ensure that you have hands on experience with coding, and it checkmates whether you have been following the video/coding instruction, despite being very easy to execute.
Oluwatosin
August 5, 2021
This course broaden my knowledge on using python for data analysis and I am grateful to Tek Kshetri for his elaborative teaching.

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4207322
udemy ID
7/27/2021
course created date
8/18/2021
course indexed date
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