An Introductory Dive Into Geospatial Analysis With Python

Introduction

Geospatial data is data that has a spatial component — meaning data that represents features or phenomena that are associated with a location relative to the Earth. There are many industries such as urban planning, transportation, and environmental science where geospatial analysis becomes exceedingly useful. With Python, data manipulation and analysis become hassle-free.

In this tutorial, we will explore the basics of using Python for geospatial data manipulation using the packages geopandas and folium.

Required Libraries:

!pip install geopandas folium

Getting Started with GeoPandas

GeoPandas is an open-source Python project for manipulation and analysis of geospatial data. It extends the pandas library to allow spatial operations on geometric types.

Here's how we can load a GeoJSON file which is a common format for encoding geographic data structures.

import geopandas as gpd

# Load GeoJSON file
geodata = gpd.read_file('filename.geojson')

Let's check the first five lines of the data.

geodata.head()

We can access the geometry of the data by calling the geometry attribute.

geodata.geometry

Plotting geospatial data with Folium

After manipulating our spatial data, we can visualize it using the Folium library in Python that builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the leaflet.js library.

Let’s say we want to create a map centered at a specific location. We create a Folium Map object and then we display it.

import folium 

# Define a map centered around coordinates
m = folium.Map(location=[51.5074, -0.1278], zoom_start=15)

# Display the map
m

Wrapping up

This was a surface scrapping dive into geospatial data visualization with Python. With GeoPandas and Folium, advanced geographical plots can be made and various techniques can be implemented for other geospatial analysis tasks. With Python, the sky is the limit!

Remember, every spatial problem is unique, and with these tools, you can curate solutions that fit the problem at hand. Have fun exploring and analyzing!

Note: Make sure to replace 'filename.geojson' with the path of your own GeoJSON file for running the code snippets. GeoJSON provides a wealth of geography data in GeoJSON format.