GoogleEarthEnginePy | Basic script to order data

GoogleEarthEnginePy is a Python library typically used in Internet of Things (IoT) applications. GoogleEarthEnginePy has no bugs, it has no vulnerabilities and it has low support. However GoogleEarthEnginePy build file is not available. You can download it from GitHub.

Basic script to order data on Google Earth Engine using Python API. October 2016 brought the announcement from Google that it had all Landsat and Sentinel data on its cloud. Amazon are also hosting all this data, ESRI are using the Amazon cloud and so are Planet (both of these for over a year). Never before has so much Earth Observation data been available to everyone. I wrote last week about Google Earth Engine Timelapse – you can view anywhere on the planet, one image per year from 1984-2016 (and onwards you would think). Already, amazing changes are being shown; what a stunning tool for the teaching of Geography and Earth Science. It will surely set student’s minds alight. For the last 10 years I have downloaded huge volumes of data, processed it locally, saved the output and archived the data. However, things are changing; traditional workflows are being replaced by server side processing. I am going to describe this in part below, but first this. It’s all a bit like ordering a sandwich. Bear with me. America has a strong service culture. On my first visit to the US I wanted a sandwich. I went in with the best of intentions of ordering something like a chicken sandwich (I can’t remember exactly), but what ultimately I was faced with was a bewildering array of questions pertaining to my choice. What type of bread (after about 5 types I panic and just take the one I can remember being offered)…what filling…what spread…what salad…how much…sauces…pepper…extra cheese. I end up by just saying yes (I am British, I didn’t want to cause a fuss). Later on in the day I was in a bookshop and wanted a tea; after being offered small, medium, large, extra large – errr, just medium is fine. I am pretty sure I ended up with what can only be described as a pint of tea – how much would I have got with extra large?. Where am I going with this rather tenuous(?) analogy? Accessing imagery on the cloud through an API and processing it seems to me to be much like ordering a sandwich, only this time I am in control and I can always change my order if it doesn’t meet my needs/expectations. Processing imagery with Google Earth Engine – basic.