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Geospatial Analysis With Python

Do you want to make a career in geospatial technology? What knowledge do you have about the field and its connection with Python, the programming language?<br><br>At GAH, we provide various geospatial courses to educate aspiring candidates. If you are interested to learn about Geospatial Analysis with Python, hereu2019s a presentation that will give you a brief idea about the topic.

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Geospatial Analysis With Python

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  1. Geospatial Analysis With Python

  2. Introduction 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.

  3. Geospatial Analysis

  4. 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.

  5. The Geographic Location of the object

  6. Geograpahic data is combined with Python applications

  7. Types of Geospatial Analysis done using Python

  8. Python is used in different types of Geospatial Analysis, such as for • Satellite image feature extraction • Special data modeling • Flood risk modeling • GPS tracking and modeling and more.

  9. Different types of Geospatial Analysis

  10. Geospatial Python Libraries There are essential Python libraries that is used to work with geospatial data. Some of the important Python libraries include:

  11. Shapely: Shapely helps in creating geometry objects and manipulate them to calculate the area, intersection etc.

  12. 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.

  13. Generally, Shapely and Geopandas are used together for more accurate geospatial analysis results.

  14. 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.

  15. 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.

  16. Scikit learn: It is the Python ML library that allows regression, dimensionality reductions and classification of geospatial data.

  17. Folium: Folium allows you to visualize spatial data on different interactive leaflet maps.

  18. There are many more Python libraries used with Geospatial Data, such as: • Rasterstats • Scikit-image • Descartes and more.

  19. 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.

  20. 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.

  21. Thanks for attending • Geospatial Queries https://geospatialawarenesshub.com/ • Geospatial Technology https://geospatialawarenesshub.com/our-services/geospatial-technology/ • Geospatial Education & Courses https://geospatialawarenesshub.com/our-services/geospatial-education-and-courses/

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