Tools tagged with "InSAR"

MintPy is an open-source Python package developed for processing Interferometric Synthetic Aperture Radar (InSAR) time-series data. It specializes in analyzing ground deformation by extracting precise displacement measurements from satellite imagery. The software provides tools for various geodetic applications, including monitoring earthquakes, volcanoes, and land subsidence.

Pyrocko is a flexible open-source seismology environment and framework, providing building blocks for researchers and students. It is utilized for various geophysical tasks, including seismological data processing and analysis, modeling of InSAR and GPS data, dynamic waveforms, and seismic source characterization.

The TanDEM-X Science Server offers researchers and scientists access to high-resolution Synthetic Aperture Radar (SAR) data and Digital Elevation Models (DEMs) derived from the TanDEM-X mission. This platform supports a wide range of scientific applications by providing crucial geospatial information for Earth observation.

This library, hosted on GitHub, provides tools for InSAR phase linking, a critical technique for measuring surface displacement. It supports both persistent scatterer (PS) and distributed scatterer (DS) processing methods. The primary goal is to facilitate the generation of accurate surface displacement maps, crucial for various geoscientific applications.

The European Ground Motion Service (EGMS) offers high-precision data on ground movements across Copernicus participating countries. This service leverages space-based remote sensing technology, specifically Synthetic Aperture Radar Interferometry (InSAR) from Sentinel-1, to detect and measure ground motion with millimeter accuracy. The data is updated annually, supporting diverse applications from infrastructure monitoring to urban planning and climate change research.

This online course from the University of Alaska Fairbanks focuses on the applications of Synthetic Aperture Radar (SAR) remote sensing for disaster monitoring. It covers weather and illumination-independent SAR technology and its use in analyzing natural hazards such as earthquakes, volcanic eruptions, and flooding.

InSAR.dev is the next evolution of PyGMTSAR, offering a federated Python ecosystem for satellite interferometry. It separates the workflow into SLC data preparation and core interferometric analysis, designed to scale efficiently across hundreds or thousands of bursts, multiple polarizations, and orbital paths. The ecosystem consists of three Python packages: insardev_toolkit, insardev_pygmtsar, and insardev, facilitating advanced InSAR processing.

This book details five and a half years of research into radar interferometry, a space-geodetic technique for measuring Earth's topography and deformation with high precision. It addresses critical issues such as data interpretation and the propagation of various errors from sensors, processing, and atmospheric effects. The work aims to provide a quantitative approach for understanding and mitigating errors in interferometric measurements.

This GitHub organization hosts the Algorithm Development Team (ADT) for the OPERA project. The team focuses on developing and sharing open-source algorithms for processing remote sensing data, particularly from Synthetic Aperture Radar (SAR) missions. Their work supports the creation of various Earth observation products for end-users.

Orfeo ToolBox (OTB) is a powerful C++ library designed for processing satellite images and other high-resolution geospatial data. It offers a wide array of image processing algorithms, including classification, segmentation, filtering, and geometric corrections, making it a robust solution for remote sensing applications.