IAMAP: Unlocking Deep Learning in QGIS for non-coders and limited computing resources

We introduce IAMAP, a user-friendly plugin for the geographic information system QGIS that allows users to ( 1) tile raster images and feed them into pre-trained deep learning model to extract image features; (2) reduce feature dimensionality; (3) perform clustering on features or their reduced representations; (4) generate feature similarity maps; (5) calibrate and validate supervised machine learning models to create maps.By enabling non-AI specialists to leverage the high-quality features provided by foundation models without requiring GPU capacity or extensive reference datasets, IAMAP contributes to the democratization of these computationally efficient and energy-conscious methods.Development of the plugin is open- source on GitHub.Documentation and tutorials are available on Read the Docs.