Download this PDF book : Python for Geospatial Data Analysis 2022
Are you a geographer, geologist, or computer scientist? Impressive if you answered yes, but I am a spatial data analyst. In a nutshell, I am interested in exploring data and integrating location.
Now that access to location data and geospatial datasets is fairly ubiquitous, most of us are becoming data curious regardless of professional title or area of study.
Appreciating the where in our analyses introduces a new dimension of comprehending the impact of a wider variety of features on a particular observation or outcome. I spend a lot of professional time examining public health data and large open source datasets in healthcare.
Once you become familiar with geocoding and spatial files, not only can you curate insights across multiple domains but you will also be able to target areas where profound gaps exist.
This is also the age of citizen scientists. The accessibility of open source tools and massive open online courses (MOOCs) empowers a broader range of not only professionals but also the data curious.
Perhaps you have a hobby or interest in a certain species of bird and would like to access spatial data to learn about their habitats. Where are they nesting? Where are they traveling from and to? Which habitats support the most species and how is this changing over time? You might be able to create maps of your sightings or other variables of interest.
We’ll explore this idea a little later when we generate a data question to explore. Meanwhile, if you are interested in a citizen scientist project look no further than the New York Public Library (NYPL) Map Warper project.
As you might imagine, NYPL has a vast amount of historical maps. The challenge is to correct the errors in outdated survey technology by searching for modern matching ground control points (GCPs) and warp the image accordingly. This is known as map rectification.
About the book:
Author: Bonny P. McClain
Year: 2022
Publisher: O’Reilly
Pages: 61
Language: Eng
Format: PDF
Size: 9 Mb
Free Download the Book: Python for Geospatial Data Analysis
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