Since late last year Alastair Graham and I have been working together on a Podcast. It is something we have both been keen to explore for a while and it certainly felt that the time was right. The aim, at least for me, was to produce something that I would want to listen to. To… Read More »Scene from above Podcast
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 »Every sensor will be used
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 »Colaboratory notebooks and GDAL
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 »Using space technology to quantify data part 1
Google Earth Engine (GEE) has a very nice feature called ‘image reducer’ and, frankly, it is incredibly useful. Say, for example, you have a field boundary and you want to know the mean, median, maximum and minimum NDVI values for it. In GEE you can use the reducer to get these values. You can also… Read More »Image reducer in Python
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 »How many Shapefiles on my computer?
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 »Fastest image reader? Four ways to open a Satellite image in Python
I have been meaning for the last 6 months to write about Jupyter Notebooks and why they are the perfect toolbox for working with Python and Satellite Imagery. I like Notepad ++ a great deal, it is simple and easy to use and will remain my default choice for the time being for writing code.… Read More »Jupyter Notebooks and Satellite Imagery
I started writing these reviews last year, really to get a feel of the pace of change in Earth Observation / Geospatial today. Looking back over the year the pace has been incredible. Q1 review Q2 review Q3 review First off I want to mention https://unsplash.com. This is an excellent website supplying free images to… Read More »Q4 2017 Earth Observation
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 »First steps – video from space
There are a variety of ways to download Sentinel 2 data, for example here, here or here. One of the easiest ways, and it seems to at least to me the fastest, is through AWS. You can go straight to the bucket, or search and explore for data through one of the eight recommended featured… Read More »Sentinel 2 level 2a data from AWS
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 »Massive Open Online Courses on Earth Observation 2017
The Rub’ al Khali, also known as the Empty Quarter, is beautiful and is also massive. It is the world’s largest sand desert (also known as an erg) covering an area larger than France. If you have watched Star Wars: Force Awakens you might be interested to know that 6 months of filming took place… Read More »Superpixel and Earth Observation – Intro
If you have an hour (or 3) to spare then there are certainly worse things to do than to investigate the last 30 or so years of time-lapsed imagery on Google Earth Engine Timelapse. It can make for uncomfortable viewing as ice retreats or urban areas expand at a phenomenal rate. It can inform you;… Read More »Building time-lapse imagery with Google Earth Engine
Sentinel-5P is scheduled for launch on the 13th October 2017 from Plesetsk launch site in Russia. Its objectives are to measure Air Quality, Ozone and Surface UV and the climate – it’s the first mission for Copernicus to monitor the atmosphere. The P stands for Precursor. You can follow the launch event from the details… Read More »Why is Sentinel-5P important?