Learn how to install the basic geospatial dependencies, such as GDAL and XArray, and deploy them as a container — Introduction Newcomers to the Python programming language quickly understand the significance of utilizing virtual environments and package management tools. The vast number of packages available presents a challenge in maintaining compatibility among dependencies, making virtual environments and package management critical components of a well-organized Python environment.

Assessing the true power of Apple Silicon architecture for geospatial analysis. — Introduction When I started working with geospatial data science during my PhD in 2019, I knew that the volume of data would require significant computational power. Those who work with geospatial data know that it’s easy to fill up memory by loading satellite imagery into Numpy arrays and combining them into…

An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages — Introduction In the previous stories (Part 1 and Part 2), we saw how to prepare a dataset of raster (multispectral) images and combined them with the corresponding labels (ground truth masks) using the IntersectionDataset provided by TorchGeo. …

An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages — Introduction In the previous story (Part 1 — here), we saw how to create a RasterDataset using TorchGeo and a RandomSampler to draw patches from it. In the current story, we are moving further and we will concatenate both the images and the masks into a IntersectionDataset, to draw tuples with…

An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages — Introduction According to its documentation, TorchGeo is a “PyTorch domain library providing datasets, samplers, transforms, and pre-trained models specific to geospatial data”. The cause is noble. Make it easier for practitioners to use Deep Learning models on geospatial data. And why is that a good deal?

Introduction Water security is one of the sustainable goals for 2030, set by the United Nations — UN [1]. Having water available in proper quantity and quality is essential for life on Earth. There are estimations that the world’s population can reach 10 billion people by 2050. …

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…