Tools tagged with "Spatio-temporal Asset Catalog"

This blog, maintained by Robin Wilson, serves as a valuable resource for discovering interesting links and discussions within the geospatial and GIS community. It frequently highlights new open datasets, web mapping libraries, command-line tools, and developments in spatio-temporal asset catalogs (STAC). The content often delves into technical aspects of databases, programming, and open-source software.

pystac is an open-source Python library designed to facilitate the creation, reading, and validation of SpatioTemporal Asset Catalogs (STAC). It provides a robust framework for developers and data scientists to interact with STAC data, enabling efficient management and access to geospatial assets. The library supports various STAC specifications and extensions, making it a versatile tool for cloud-native geospatial workflows.

GeoMesa is an open-source suite of tools designed for large-scale geospatial querying and analytics on distributed systems. It provides spatio-temporal indexing on top of databases like Accumulo, HBase, Redis, and Cassandra for massive data storage. The platform also supports near real-time stream processing by layering spatial semantics on Apache Kafka and facilitates integration with mapping clients via GeoServer and OGC APIs.

This dataset provides Sentinel-2 Level-2A satellite imagery in Cloud-Optimized GeoTIFF (COG) format, offering high-resolution optical data for land monitoring. It includes global coverage with frequent updates, accessible via AWS, and is accompanied by SpatioTemporal Asset Catalog (STAC) metadata, making it easily discoverable and usable for various geospatial applications.

The KyFromAbove initiative offers a current basemap for Kentucky, including leaf-off aerial photography and LiDAR data. This resource supports state, federal, local, and regional users by providing open data to reduce GIS application development costs and promote data sharing. All data is made publicly available.

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).

Development Seed focuses on improving planetary observation through robust cloud infrastructure for managing vast geospatial data. The company applies artificial intelligence to solve environmental challenges and designs user-centric geo-data products for actionable insights.

This dataset offers New Zealand's publicly owned digital elevation and surface models, freely available under an open license. It includes 1m resolution grids derived from LiDAR data, provided as Cloud Optimised GeoTIFFs (COGs) with LERC compression. Each elevation file is accompanied by STAC metadata, organized by region and survey, and regularly updated as new data is published.

This dataset provides stereo-derived Digital Terrain Models (DTMs) of five key sites on Jupiter's moon Europa, generated from NASA's Galileo spacecraft Solid State Imager data. These DTMs offer crucial topographical insights for understanding Europa's geology and supporting future landed missions, with manual editing for accuracy and updated pointing information for precise coordination. They are suitable for most scientific analyses, acknowledging inherent uncertainties in resolution and precision.

This GitHub repository serves as a comprehensive catalog of open geospatial datasets. It organizes and lists data accessible through prominent platforms such as AWS, Google Earth Engine, Microsoft Planetary Computer, NASA CMR, and STAC Index, providing a valuable resource for geospatial professionals.

The FloodPlanet dataset provides manually labeled inundation data, meticulously collected for advancing flood detection research. It serves as a crucial resource for training and validating deep learning models, utilizing high-resolution imagery from PlanetScope, Sentinel-1, and Sentinel-2 satellites. This version 1.0 dataset, contributed by Zhijie(JJ) Zhang and collaborators, is a valuable asset for the geospatial community.

The CNG Blog is the official blog of the Cloud-Native Geospatial Forum, a community dedicated to advancing cloud-native geospatial practices. It features articles on new technologies, community sprints, technical developments, and expert insights.