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[…]

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[…]

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[…]


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[…]


Combining OpenCV and leaflet for simple web mapping

I am always on the look out for an easy way to build simple web maps. Ideally I would like to perform OpenCV in the browser but I am not aware of that possibility at present. I work with computer vision and satellite imagery a great deal and have written several blogs on the subject. Read more about Combining OpenCV and leaflet for simple web mapping[…]

colaboratory satellite

Colaboratory notebooks and GDAL

Last year I heard about Colaboratory by Google and, now that I am using Jupyter Notebooks, it seems the perfect opportunity to explore it further. I previously wrote about how using Jupyter Notebooks is a perfect match for Satellite imagery processing. If you would like to read about that then the post is here. Otherwise, Read more about Colaboratory notebooks and GDAL[…]

How many Shapefiles on my computer?

If you work with Geospatial software you cannot ignore the Shapefile. Whatever your thoughts on them (and it does polarise opinion in the GIS world; look for #Teamshapefile or #switchfromshapefile), I feel that I am ultimately driven by whatever a client would prefer. More often than not that is a preference for a Shapefile. FME Read more about How many Shapefiles on my computer?[…]