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Geospatial Data Science Quick Start Guide

Geospatial Data Science Quick Start Guide

By : Abdishakur Hassan, Jayakrishnan Vijayaraghavan
4 (6)
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Geospatial Data Science Quick Start Guide

Geospatial Data Science Quick Start Guide

4 (6)
By: Abdishakur Hassan, Jayakrishnan Vijayaraghavan

Overview of this book

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.
Table of Contents (9 chapters)
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Summary

In this chapter, we covered geofencing concepts and what geofencing is and presented different use cases and applications of geofencing. We touched upon and revisited geometry operations, especially LineString and polygons. To illustrate a simple application of geofencing, we first covered masking with points in polygon topology operations. Once we mastered these geometry and topology concepts, we moved on to using geofencing in real-world application data. Putting all of these different pieces together, we were able to construct a mask for the whole trajectory data with three geofencing polygons: an airport, beach, and city center. Finally, we animated the trajectory points, where trajectory points move and indicate whether the point is inside the geofence polygon or outside. The applications of geofencing are limitless and can be applied in different case scenarios and...

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