Tools tagged with "Machine Learning"

A unified Python toolkit for obtaining embeddings from any Remote Sensing Foundation Model with a single line of code.

This book introduces `sits`, an open-source R package for analyzing big Earth observation data using satellite image time series and data cubes.

A geospatial career journey exploring technology, tools, and industry insights.

Master remote sensing image acquisition, analysis, and applications, from fundamentals to deep learning techniques.

A Python library for high-accuracy water segmentation in satellite and aerial imagery using deep learning and spectral indices.

A practical guide to applying remote sensing methodologies for agricultural statistics and land use mapping.

An open-source deep-learning framework for exploring, building, and deploying AI weather and climate workflows.

A foundation model for processing time-series satellite imagery to extract temporal patterns for Earth observation.

This Python library converts diverse geospatial datasets into graph structures for advanced GNN and spatial analysis.

GoldenEye provides a unified interface for geospatial vision-language models, enabling rapid deployment with minimal code.

A data-oriented pansharpening model designed to enhance the spatial resolution of satellite imagery through image fusion.

Provides current news and updates on developments within the geospatial industry.

A blog exploring advanced drone LiDAR mapping, AI segmentation, and UAS operational insights for geospatial professionals.

An open-source SDK designed for logging, storing, querying, and visualizing diverse multimodal and multi-rate data streams.

A unified framework for end-to-end segmentation of forest LiDAR 3D point clouds.

This course provides essential Machine Learning skills tailored for Earth Observation research.

A pan-European label dataset providing harmonized crop type information for large-scale agricultural classification.

A community-sourced repository providing standardized, machine-learning-ready imagery and annotations for coral reef conservation.

A global, temporal dataset tracking solar and wind energy installations using satellite imagery and deep learning.

Provides free online courses focused on Earth Observation, remote sensing, and geospatial applications.

A powerful Python package for integrating artificial intelligence with geospatial data analysis and visualization.

A standard for curating, sharing, and combining large-scale Earth Observation datasets for AI and ML.

An acceleration framework for 3D Gaussian Splatting, significantly reducing training times while maintaining high rendering quality.

A Substack publication delivering news, technical posts, and research focused on Earth Observation.

A Python toolkit designed for fine-tuning Geospatial Foundation Models (GFMs) for various applications.

A curated, long list of geospatial tools and resources on GitHub.

A Modern Library for 3D Data Processing

Generate and process large-scale geospatial datasets with Google Earth Engine for AI research.

A leading cloud-native GIS software and online mapping platform for speed, simplicity, and collaboration.

AI-powered geo-location analysis using Google's Gemini API to uncover photo locations.

The Agentic GIS Platform for scalable spatial analysis in your cloud ecosystem.

This dataset provides comprehensive biodiversity information, accessible through the Microsoft Planetary Computer for environmental analysis.

Equator empowers housing professionals with accurate site data and AI-driven proposal generation for land development.

A comprehensive dataset of annual satellite embeddings, provided as Cloud-Optimized GeoTIFF (COG) files.

Access detailed population density maps for humanitarian and development efforts.

Maps Are Everywhere. These are conversations with those building them.