Tools tagged with "SAR"

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.

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.

AnytimeFormer is a deep learning model designed to reconstruct land surface reflectance at any given time by effectively fusing irregular and asynchronous Synthetic Aperture Radar (SAR) and optical time series data. It addresses the challenge of combining diverse satellite data streams to provide continuous, high-quality environmental monitoring. The project offers a robust solution for generating comprehensive reflectance products from disparate remote sensing observations.

This resource provides access to the global Sentinel-1 GRD archive, encompassing data from its inception to the present. The data is converted into cloud-optimized GeoTIFF format, making it readily available for various applications. It supports diverse use cases, including land and sea monitoring, emergency response for environmental disasters, and economic applications.

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.

This dataset offers Radiometrically Terrain Corrected (RTC) Sentinel-1 C-band Synthetic Aperture Radar (SAR) imagery, processed from original Ground Range Detected (GRD) scenes. It provides analysis-ready data, suitable for environmental monitoring, available over the Contiguous United States (CONUS) since 2017. The data is managed by Indigo Ag, Inc. and targets daily updates.

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.

S1FloodFinder is a user-friendly open-source solution designed for flood mapping using Synthetic Aperture Radar (SAR) imagery from Sentinel-1. This package addresses the limitations of optical satellite imagery during floods, which often struggle with cloud cover, by leveraging SAR's ability to penetrate clouds. It provides specialized techniques and tools for accurate floodwater extent measurements, crucial for emergency response and minimizing disaster impact.

The Sentinel Application Platform (SNAP) provides a unified architecture for all Sentinel Toolboxes, enabling efficient processing and analysis of Earth Observation data. It leverages technological innovations such as a modular rich client platform, generic EO data abstraction, and a graph processing framework. This platform is designed for extensibility and portability, facilitating advanced geospatial data manipulation.

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 dataset contains ALOS-2 PALSAR-2 ScanSAR Level 2.1 data, offering orthorectified backscatter observations with a 350 km observation width at 25m resolution. It was generated by JAXA in response to torrential rainfall, flooding, and landslides in Rwanda, activated through the International Disaster Charter. The data provides valuable insights for disaster response and natural resource monitoring in affected regions.

EOReader is a powerful open-source Python library designed for remote sensing applications. It provides a sensor-agnostic framework for reading and processing data from a wide range of optical and Synthetic Aperture Radar (SAR) satellite constellations. Users can efficiently load and stack various components such as spectral bands, cloud masks, Digital Elevation Models (DEMs), and spectral indices, simplifying complex satellite imagery workflows.

NASA's Applied Remote Sensing Training (ARSET) program provides free online and in-person webinars and workshops. It aims to empower individuals and organizations to leverage Earth-observing data for informed environmental management and decision-making across various applications globally.

This resource provides Synthetic Aperture Radar (SAR) and SAR-derived satellite data products from various sources, specifically curated for disaster events. It offers valuable insights for researchers, scientists, and emergency response teams, with irregular updates in response to new disasters. The data is managed by the Alaska Satellite Facility (ASF).

The HydroSHEDS database offers a suite of freely available global digital data layers supporting hydro-ecological research and applications worldwide. Its hydrographic data products encompass catchment boundaries, river networks, and lakes at multiple resolutions and scales, forming a geospatial framework for diverse assessments.

This platform provides access to a variety of geospatial datasets focusing on the Antarctic. It serves as a central hub for researchers and users to explore and download critical environmental data, including satellite imagery and ice-related products. The service aims to support monitoring and analysis of the dynamic polar environment.

S1Tiling is an open-source software project hosted on GitLab, designed for the automatic ortho-rectification of Sentinel-1 Synthetic Aperture Radar (SAR) data. It processes this data to align with the Sentinel-2 tiling grid, making it suitable for integration with optical imagery analysis. The tool aims to simplify the preparation of Sentinel-1 data for various geospatial applications.

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.

This program offers high-resolution Synthetic Aperture Radar (SAR) imagery from Umbra satellites, with resolutions up to 16-cm. SAR data can penetrate clouds and darkness, making it ideal for continuous monitoring and change detection. The Open Data Program provides frequently updated time-series locations and a collection of global images for various applications.

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.