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[…]

every_sensor

Every sensor will be used

This post is a copy of original posted below. I was paid to guest write this. https://medium.com/@mail_83112/every-sensor-will-be-used-d27cf0223f69 Pool your information from anything and everything — Inform decision making — Let the most appropriate person make the final decision… namely, the user Last time I looked at how data from space, particularly Earth Observation data, is growing at a staggering Read more about Every sensor will be used[…]

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[…]

Using space technology to quantify data part 1

This post is a copy of original posted below. I was paid to guest write this. https://medium.com/@mail_83112/using-space-technology-to-quantify-data-part-1-519d397049aa Earth Observation data is part of the foundations of MIS; you could say it is at their core. Being fundamentally a Geospatial company, all of their insights are built upon a layer(s) of remotely sensed data. I believe Read more about Using space technology to quantify data part 1[…]

Fastest image reader? Four ways to open a Satellite image in Python

I wasn’t sure what to call this post… “The Fastest Way to Read a Satellite Image in Python”? “Using Magic Functions in Jupyter Notebooks”? “Four Ways to Read Images into NumPy Arrays”? There are several ways; I’ve not even looked at PIL here, to read your Satellite data into a NumPy array. After all, if Read more about Fastest image reader? Four ways to open a Satellite image in Python[…]

Video Space

First steps – video from space

There are many Satellites in orbit today capable of recording video from space; there is even a camera attached to the ISS. This is a relatively new and exciting area in Earth Observation. I say new… this article is almost four years old at the time of writing. https://blogs.scientificamerican.com/plugged-in/high-definition-video-from-space-is-available-for-purchase-finally/ What does this mean? Is anyone Read more about First steps – video from space[…]

learning

Massive Open Online Courses on Earth Observation 2017

In Q4 2017 there have been at least four Earth Observation related MOOCs that I have been aware of. I have keenly followed these three: Future Learn Earth Observation EO College “Echoes in space” IEA’s Big Data (not solely focused on EO, but there is a decent part devoted to it). All this information was/is Read more about Massive Open Online Courses on Earth Observation 2017[…]