Thanks for reading my newsletter. Special shoutout to the new subscribers! Read on for new learning resources for QGIS, Python, Google Earth Engine, GDAL and more.
Time-Series Analysis
Over the past few months, I have been researching and writing code to make working with time-series easy in Google Earth Engine. I have several new resources to share.
Time Series Smoothing
Remote Sensing data is noisy. There is quite a bit of literature on techniques for smoothing time-series by filtering outliers - but there is a lack of open-source implementations in Earth Engine. Check out my posts with open-source code for the following techniques:
Trend Analysis
Once you have a time-series, the next step is to analyze it. We also published an end-to-end module on Precipitation Time Series Analysis that shows how to create an aggregated time-series and use non-parametric methods to do per-pixel trend analysis in Google Earth Engine.
Upcoming Classes
My brand-new Introduction to QGIS certification course just launched and will be hosting our first 2 cohorts in April.
Introduction to QGIS, 9-10 April 2022
Introduction to QGIS, 26-27 April 2022
Advanced QGIS, 30 April- 1 May 2022
Check out the session details and sign-up!
New Learning Materials
QGIS
We updated our Performing Table Joins on working with US Census Data, including downloading data from the new census bureau website.
Cliff Patterson from Luna Geospatial hosted a free webinar on “Create custom attribute forms in QGIS” which is a great introduction to forms in QGIS.
Tim Sutton from Kartoza hosted a mini-workshop on “QGIS Reporting Tool”. You can view the session recording and training materials from the GitHub repository.
Staten published a detailed post on “Mapping Historical New York with dot density maps” using QGIS that uses nifty expressions and custom functions to map demographic data.
Python
My new article Creating Animated Plots with Matplotlib explores some advanced visualization techniques to visualize recursive algorithms using Python.
Ryan Abernathey published the full course material for An Introduction to Earth and Environmental Data Science that uses numpy, pandas, xarray, dask and matplotlib for working with climate datasets using Python.
Earth Engine
Jesse Anderson published a new module called gee-blend that brings the popular layer blending modes to GEE.
GDAL/Command-line
I love command-line tools and use GDAL tools regularly to speed up and optimize my workflows. A new free e-book “Data Science at the Command Line” by Jeroen Janssens caught my eye. It shows some really useful data cleaning and analysis tricks that will make you a productive data scientist.
IIEP Hackathon
I wanted to mention an interesting hackathon event hosted by IIEP-UNESCO from 6-8 May 2022. I am a big believer and learning-by-doing and this event provides the perfect opportunity to take your skills to the next level. This event will be of particular interest to my readers who know Google Earth Engine and want to apply it to solve an important real-world issue. Learn more and sign-up! You can also read about the projects created by winners from the previous edition.