Geospatial Data Science Quick Start Guide

More Information
  • Learn how companies now use location data
  • Set up your Python environment and install Python geospatial packages
  • Visualize spatial data as graphs
  • Extract geometry from spatial data
  • Perform spatial regression from scratch
  • Build web applications which dynamically references geospatial data

Data scientists, who have access to vast data streams, are a bit myopic when it comes to intrinsic and extrinsic location-based data and are missing out on the intelligence it can provide to their models. This book demonstrates effective techniques for using the power of data science and geospatial intelligence to build effective, intelligent data models that make use of location-based data to give useful predictions and analyses.

This book begins with a quick overview of the fundamentals of location-based data and how techniques such as Exploratory Data Analysis can be applied to it. We then delve into spatial operations such as computing distances, areas, extents, centroids, buffer polygons, intersecting geometries, geocoding, and more, which adds additional context to location data. Moving ahead, you will learn how to quickly build and deploy a geo-fencing system using Python. Lastly, you will learn how to leverage geospatial analysis techniques in popular recommendation systems such as collaborative filtering and location-based recommendations, and more.

By the end of the book, you will be a rockstar when it comes to performing geospatial analysis with ease.

  • Manipulate location-based data and create intelligent geospatial data models
  • Build effective location recommendation systems used by popular companies such as Uber
  • A hands-on guide to help you consume spatial data and parallelize GIS operations effectively
Page Count 170
Course Length 5 hours 6 minutes
ISBN 9781789809411
Date Of Publication 30 May 2019


Abdishakur Hassan

Abdishakur Hassan is a geographic information systems (GIS) expert and consultant with over 5 years of experience working with UN Habitat. He holds an MSc in geoinformation science and earth observations. During his tenure as a GIS expert, Abdishakur has developed fully fledged GIS applications in the urban planning and land administration domains. He is interested in all things related to geospatial data science.

Jayakrishnan Vijayaraghavan

Jayakrishnan Vijayaraghavan is a geospatial data scientist, innovator, and author of a book titled ArcGIS for JavaScript developers. He currently resides in the San Francisco Bay Area and has over 8 years of work experience. He has built patented technologies and products in the geospatial domain and has coached teams on leveraging mapping and spatial analytics tools for solving pertinent business problems. He is adept at computational geometry, especially in graph networks and in geospatial inferencing. He is a DAAD scholar and a winner of the UN-Habitat special jury award. He is keen on developing intelligent and ubiquitous mapping systems by integrating ML and DL techniques with GIS. He is also a novelist and a certified UAV pilot.