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This article aims to demonstrate how to semantically segment aerial imagery using a U-Net model defined in TensorFlow.

This workshop will present a set of established methods commonly used to account for location error in animal telemetry data, estimate unobserved animal behavioral states and space-use.

This book will introduce you to the methods required for spatial programming. It focuses on building your core programming techniques while helping you carry out various geospatial tasks.

ol-ext is a set of extensions, controls, interactions and popup to use with OpenLayers. Check here to view examples and learn more.

This tutorial shows you how to capture the expansion of built-up surfaces in the world's largest urban areas using R.

Here is a list of radar and optical satellite datasets for ship detection, classification, semantic segmentation and instance segmentation tasks.

Setting up access to Google Earth Engine from public apps could be rather complicated. Here is a post outlining the steps needed to start using Google Earth Engine from a Streamlit application.

This post provides an introduction to satellite imagery classification, and an overview of how models are trained in practice.

Check here for an implementation of an algorithm capable of finding all the areas that a person could have reached while en route between locations in a defined period.

This post details step-by-step instructions in setting up both AGOL/ArcGIS Portal and QGIS to access content hosted on AGOL/ArcGIS Portal.