Geospatial Analysis With Python
                     Geospatial 
Analysis 
With Python
Introductio
n
In this presentation, we have discussed 
geospatial analysis using Python and how we, at 
GAH, offer the course to aspiring individuals who 
wish to make a career in Geospatial Technology.
Geospatial Analysis
Geospatial Analysis
and Python
Geospatial data or GIS data or Spatial data or 
geodata is name for the numeric data collected 
to identify the geographic location of an object 
(physical object), such as a town, a building, a 
city, etc. based on the geographic co-ordinate 
system.
The Geographic Location of the object
Geograpahic data is  combined 
with Python applications
Types of Geospatial Analysis 
done using Python
Python is used in different 
types of Geospatial Analysis, 
su• cShat eallsit ef oimrage feature extraction
• Special data modeling
• Flood risk modeling
• GPS tracking and modeling and more.
Different types of Geospatial 
Analysis
Geospatial Python 
There are essenLtiailb Prytahorni elibsraries that is 
used to work with geospatial data. Some of 
the important Python libraries include:
Shapely: Shapely helps in creating geometry 
objects and manipulate them to calculate the 
area, intersection etc.
Geopandas: It merges the geometry objects of 
Shapely, the powerful data frame interface of the 
pandas library and the write/read/projection 
functions of Fiona in one package.
Generally, Shapely and Geopandas are 
used together for more accurate 
geospatial analysis results.
Rasterios: It is a go-to Python library used for 
raster data handling. Raster iOS allows you to 
read or write raster files to NumPy arrays and 
manipulate these arrays.
GDAL: GDAL or Geospatial Data Abstraction Library 
is the Python library that allows reading, writing 
and manipulating vector and raster data in several 
software packages.
Scikit learn: It is the Python ML library that allows
regression, dimensionality reductions and 
classification of geospatial data.
Folium: Folium allows you to visualize 
spatial data on different interactive 
leaflet maps.
There are many more Python libraries used 
with Geospatial Data, such as:
 
• Rasterstats
• Scikit-image
• Descartes and more.
Geospatial analysis skills combined with Python 
are critical for our society and economy. When you 
learn geospatial analysis using Python, you 
upgrade your skillset to a level that allows you to 
make a career as a Geospatial Analyst, Remote 
Sensing Analyst, Spatial Statistician, GIS Specialist 
and Environmental Scientist.
So, if you wish to learn Geospatial Analysis using 
Python, Geospatial Awareness Hub can help you 
in the process. We offer various courses of 
Geospatial Education that prepares interested 
candidates to make a career in the field of 
Geospatial Technology.
Thanks for attending
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