How to create a STAC catalog for geospatial data in Python with pystac package — Introduction Those who work with geospatial data may be used to the huge amounts of files to deal with. Normally plenty of steps with intermediate files have to be processed to achieve the final goal. …

Mask clouds (and cloud shadows) effectively on Microsoft Planetary Computer using S2 Cloudless layers from GEE with geeS2Downloader package — Introduction Microsoft Planetary Computing is a good competitor to the well established Google Earth Engine in the geospatial arena. The possibility to access petabytes of satellite information without the need to download each image and the computational power provided by Dask clusters is a gamechanger for developing regional/global applications and research…

Learn how to use market data from Yahoo Finance to backtest strategies locally in Python through the LEAN engine from Quantconnect. — Introduction In this story I will share my recent experience backtesting strategies that I’ve developed on Quantconnect locally, using the LEAN-CLI, and how to use free Yahoo data for it. Those who follow my stories may know that I’ve been using the Quantconnect platform to write and test my trading strategies…

Learn a workaround that can be applied to avoid the annoying limitation set by Google to download contents directly to your local machine — Introduction When I started using Google Earth Engine (GEE) back in 2018, I found it an amazing idea to have all the satellite imagery datasets in the cloud, and accessing them in such on-demand basis. Once we understand that the computations happen on the server side, through the Earth Engine API…

Jupyter notebooks were game changers for data scientists across the globe. But should it be used indiscriminately? — Introduction It’s no doubt that the launch of the project Jupyter, and its notebooks, back in 2015, changed the relation between scientific programmers and their code. The first reason is the simplicity to connect to different programming languages (kernels) and combine text with code snippets and outputs such as tables and…

Let’s discuss some of the main reasons why software developed in the Academia and research centers are so poorly designed and find solutions — Introduction It’s been some time I wanted to write about this topic, but I must confess I’ve been procrastinating it a little bit. Although I don’t have a formal Computer Science background myself (I have a civil engineer degree), I’ve been working with the IT industry for more than 15 years…

Introduction As technology evolves rapidly, remote sensing is finding its many uses across different subjects, from forest fire mapping to water quality assessment, 3D surface modeling and many others. The advantages of obtaining physical characteristics of an area by measuring its reflected and emitted radiation at a distance are many. However…

Learn how to implement and backtest a Mean Reverting strategy from the book “Algorithmic Trading: Winning Strategies and Their Rationale” using the Quantconnect framework. — Introduction Hi! Today we will continue to develop the Mean Reverting algorithm introduced in the last post Implementing a Simple Mean Reverting Pairs Trading Algorithm in the Quantconnect platform (Part 1) [1], and hopefully improve its results .

Learn how to implement and backtest a Mean Reverting strategy from the book “Algorithmic Trading: Winning Strategies and Their Rationale” using the Quantconnect framework. — Update For information about the course Introduction to Python for Scientists (available on YouTube) and other articles like this, please visit my website cordmaur.carrd.co. Introduction Hi! In my last story “Understanding and Implementing Kalman Filter for Pairs Trading” [1] I’ve used an example from the book Algorithmic Trading: Winning Strategies and Their…