In the last post in this series, I showed some pretty maps of roadside leafiness, created by extracting NDVI values near roads – like this: This time, I want to move away from pretty images to some numerical analysis – and also move from a local scale to a national scale. My first question was: […]
If you just want to see some pretty maps of roadside leafiness then scroll down…otherwise, start at the top to find out how I did this. I’ve recently started doing a little bit of satellite imaging work again, and started off with a project that was inspired by a post on James O’Connor’s blog. He […]
I haven’t posted anything on this blog for a long time – sorry about that. I’ve been quite ill, and had a new baby – so blogging hasn’t been my top priority. Hopefully I’ll manage some slightly more regular posts now. Anyway, on with the post… I recently needed to delete some attribute columns from a […]
I remember experimenting with doing regressions in Python using R-style formulae a long time ago, and I remember it being a bit complicated. Luckily it’s become really easy now – and I’ll show you just how easy. Before running this you will need to install the pandas, statsmodels and patsy packages. If you’re using conda […]
This is just a very brief reminder about something you might run into when you’re trying to get your code to work on multiple platforms – in this case, OS X, Linux and Windows. Basically: file names/paths are case-sensitive on Linux, but not on OS X or Windows. Therefore, you could have some Python code […]
This is a quick post to brief describe a problem I ran into the other day when trying to debug someone’s code – the answer may be entirely obvious to you, but it took me a while to work out, so I thought I’d document it here. The problem that I was called over to […]
A key – but challenging – part of learning to program is moving from writing technically-correct code ‘that works’ to writing high-quality code that is sensibly decomposed into functions, generically-applicable and generally ‘good’. Indeed, you could say that this is exactly what Software Carpentry is about – taking you from someone bodging together a few […]
I use data from the AERONET network of sun photometers a lot in my work, and do a lot of processing of the data in Python. As part of this I usually want to load the data into pandas – but because of the format of the data, it’s not quite as simple as it […]
I now use Anaconda as my primary Python distribution – and my company have also adopted it for use on all of their developer machines as well as their servers – so I like to think I’m a relatively knowledgeable user. However, the other day I came across a wonderful feature that I’d never known about […]
There was a question recently on the Py6S mailing list about what data sources are best to use to provide atmospheric parameters (such as AOT, water vapour and ozone) for use with 6S, other atmospheric Radiative Transfer Models (such as MODTRAN) or other atmospheric correction algorithms (such as ATCOR). In the spirit of ‘reply to […]