8 tips using GeoPandas and Python for Geospatial People

GeoPandas is great. If you are learning Geospatial Programming and work with vector data then you could do alot worse than giving GeoPandas a go. I’ve written a little about GeoPandas before; so first a couple of links. Installing a Python Geospatial work environment that includes GeoPandas: Python for Geospatial work flows part 1: Use Read more about 8 tips using GeoPandas and Python for Geospatial People[…]

Ridge map plots using Python

I saw this tweet on May 1st: Inspired by @ZachACole's beautiful illustrations and @jakevdp's pulsar plots, I just released a library to make "ridge elevation plots" with Python and @matplotlib. Let me know if you make something nice! https://t.co/X3XLnA6qAM pic.twitter.com/UfApYUDTH8 — Colin Carroll (@colindcarroll) May 1, 2019 I’ve seen these plots created before and find Read more about Ridge map plots using Python[…]

sentinelsat – using Python to search and download Sentinel 2 data

There are so many ways to download Sentinel 2 data. I am not going to list them all here, but most involve an interaction with a website that contains a map. This is fine for many users. Sometimes though it is preferable to access via the command line or a script and again there are Read more about sentinelsat – using Python to search and download Sentinel 2 data[…]

Virtual_env

Python for Geospatial work flows, part 3: Virtual Environments

In the summer of 2018 I began a series of posts about setting up Python for anyone who is new to using it. My focus is predominantly on Geospatial Python, but I think the principals should be applicable to any application of Python. If you want a recap then part 1 (setting up in Anaconda) Read more about Python for Geospatial work flows, part 3: Virtual Environments[…]

up

A look at the growth and the polarity of sentiment of Earth Observation and Remote Sensing since 2008, with Python and Pandas

  About 18 months ago I looked at tweets from Twitter containing the phrases Earth Observation or Remote Sensing. Primarily I did this after the first Future EO event that ESA held. You can have a look at the post here: #FutureEO and twitter data mining With the next future EO event this November I Read more about A look at the growth and the polarity of sentiment of Earth Observation and Remote Sensing since 2008, with Python and Pandas[…]

Community GBDX Notebooks

GBDX notebooks are a great way of acessing a vast array of satellite data. You can get yourself a trial account here: https://notebooks.geobigdata.io/ No more downloading satellite imagery, just process it in the cloud. When you think about the sheer volume of satellite data that Digital Globe has and its size to download, processing it Read more about Community GBDX Notebooks[…]

Python for Geospatial work flows part 2: Use Jupyter Notebooks

In part 1 I looked at how to set up a Python 3 environment for use with Geospatial Workflows. If you want to recap take a look here In part 2 we will look at Jupyter Notebooks. Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Read more about Python for Geospatial work flows part 2: Use Jupyter Notebooks[…]

Python for Geospatial work flows part 1: Use anaconda

I have written a lot in the past about using Python for GIS and Earth Observation. If you have not used Python before and you are looking to get started here are a few recommendations to get you up and running. This blog post is for anyone who is new to programming with Python. There Read more about Python for Geospatial work flows part 1: Use anaconda[…]

Sentinel_5P

Sentinel-5P and Python

The data for Sentinel 5P was made available on 11th July 2018. #BreakingSince yesterday #Sentinel5P #opendata is available for downloadWith a resolution of up to 7×3.5 km, it enables detection of air pollution over individual cities.This high spatial resolution is key to locate the origin of pollutants and identifying #pollution hotspots pic.twitter.com/ncoP2ZkCmP — Copernicus EU Read more about Sentinel-5P and Python[…]

K-means in Python 3 on Sentinel 2 data

18 months ago I wrote about unsupervised classification of randomly extracted point data from satellite data. I have been meaning to follow it up with showing how straightforward it is to use the cluster algorithms in Sklearn to classify Sentinel 2 data. I have made this blog into a Juypter Notebook which is available here. Read more about K-means in Python 3 on Sentinel 2 data[…]

GeoPandas

Using GeoPandas to display Shapefiles in Jupyter Notebooks

GeoPandas is a super simple way to work with GIS data using Python. It sits nicely in Jupyter Notebooks as well. This blog is all about displaying and visualising shapefiles in Jupyter Notebooks with GeoPandas. I am going to use a subset of the hexagonal Crop Map of England (CROME) and visualise it in a Read more about Using GeoPandas to display Shapefiles in Jupyter Notebooks[…]