Tools tagged with "Remote Sensing"

A comprehensive guide to performing spatial analysis and GIS operations using the R programming language.

A comprehensive guide to the foundational principles and practical applications of Geographic Information Systems.

A practical guide to mastering GIS programming using Python and open-source geospatial tools.

Learn spatial data analysis and GIS fundamentals using the R programming language.

Elevate data storytelling skills through interactive, geospatial, and narrative data visualization techniques.

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

Dive into geostatistics with practical skills in spatial data analysis and modeling.

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

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.

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

This collection provides remote sensing data and tools for monitoring snow and ice changes across the High Mountain Asia region.

A blog providing updates and technical insights related to geospatial code and news.

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

A coordinated effort to simplify browser-based data visualization in Python.

Learn to process and visualize point cloud data efficiently using QGIS's native tools and the powerful PDAL wrench.

A fast and scalable Python library for raster-based spatial analytics.

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

Transforming Earth Observation Data into Insights for Africa's Sustainable Growth.

This Python package automatically generates high-resolution river relative elevation models (REM) and visualizations from digital elevation models.

A map-first STAC search and visualization tool, offering robust support for stac-geoparquet data.

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

A Python package for interactive geospatial analysis and visualization with Google Earth Engine.

OCWGIS provides free and open online courses for individuals to learn and enhance their skills in Geographic Information Systems.

A Python package that extends Google Earth Engine with pre-processing and processing tools for satellite platforms.

This course offers a gentle introduction to Python programming, specifically tailored for spatial data analysis.

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

This open-source 3D tool generates Digital Surface Models from satellite imagery using advanced photogrammetry techniques.

An extremely precise digital elevation model describing the surface of Switzerland without vegetation and development.

A structured introduction to XArray, STAC, and Dask for cloud-based remote sensing applications.

A robust open-source Python package for comprehensive analysis of digital elevation models.

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

Provides free open-source solutions for comprehensive forest and land monitoring globally.

A free, user-friendly, and extendable application for processing drone imagery into maps, 3D models, and more.

An open book about algorithms and methodologies to reconstruct, manipulate, and extract information from terrains.