Are you a beginner at Python for Geospatial Processing? Do you find the installation process a wee bit cumbersome? The details are mentioned in a Medium post entitled Python and GDAL Installation Automated for Windows 10.
Platforms, Tools and Packages for Geospatial/Earth Observation Data Scientists. In this article, I highlight the best open source tools in the market that are integrated into the data science ecosystem.
How to implement augmentations for Multispectral Satellite Images Segmentation using Fastai-v2 and Albumentations. Improve the performance of your deep learning algorithms with multispectral image augmentations and Fastai v2
In this tutorial we’ll be showing you how to get started with Arlula and order your first Landsat 8 satellite imagery datasets for free using our API.
Turkey’s unique geographic position with a 911 Km border with Syria, and its standing as a land migration route to Europe has resulted in the country receiving a large influx of Syrian refugees.
A step by step guide with code and data on how to create a datablock for multispectral satellite image segmentation with the Fastai-v2.
In this article, we will discuss the detailed process of surface soil moisture (top 5 cm) estimation using satellite images. This article is divided into five sections. First, we will see the satellite images used then we will see the study area. Afterwards, we will go through the models. Then we will see the detailed methodology. Lastly, we will see the results, discussion and conclusion section.
How to teach drone to see what is below and segment the object with high resolution. Drone uses already gain popularity in the past few years.
Learn how to use Google Earth to create training patches for Image Segmentation to be used with any Deep Learning framework.