Tools tagged with "Google Earth Engine"

GeeFlow is a Python library from Google DeepMind designed for generating and processing large-scale geospatial datasets using Google Earth Engine. It focuses on supporting geospatial AI research by creating datasets in TFDS format, ready for model training, and enabling the creation of inference maps up to global scale.

This plugin seamlessly integrates Google Earth Engine with QGIS, providing users with powerful geospatial analysis capabilities. It leverages the Google Earth Engine Python API to enable advanced remote sensing and data processing directly within the QGIS environment.

This dataset offers annual satellite embeddings for the years 2018 to 2024, inclusive. Produced by Google and Google DeepMind, it provides valuable earth observation data in an easily accessible format. It is ideal for machine learning applications and environmental analysis.

This website offers an interactive web mapping application displaying the Ecoregions 2017 dataset. Users can navigate and zoom across a global map to visualize and understand the distribution of terrestrial ecoregions. It provides a visual tool for environmental research and conservation efforts.

Google Earth Engine provides a comprehensive data catalog for scientists, researchers, and developers. It combines a vast collection of satellite imagery and geospatial datasets with powerful analysis tools. Users can detect changes, map trends, and quantify differences on the Earth's surface at a planetary scale.

This website offers the GlobalHighAirPollutants (GHAP) and ChinaHighAirPollutants (CHAP) datasets, featuring long-term, full-coverage, and high-resolution data for various air pollutants. These datasets are generated using advanced artificial intelligence techniques on big data, considering the spatiotemporal heterogeneity of air pollution.

leafmap is a Python package designed for interactive geospatial analysis and mapping. It simplifies complex GIS tasks within Jupyter environments, enabling users to create dynamic maps and perform advanced spatial analysis with minimal coding.

This resource provides access to version 1.2 of the Global Forest Change dataset, offering detailed information on forest extent and loss from 2000 through 2014. The data is derived from time-series analysis of Landsat imagery, with updates incorporating Landsat 8 OLI for more recent years. Users can download the dataset and are encouraged to register for updates.

This website serves as a comprehensive catalog for community datasets accessible within Google Earth Engine. It provides users with organized access to a wide array of geospatial data, along with resources to facilitate their exploration and utilization. The platform also features tutorials, publications, and tools for getting started with GEE community assets.

Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. It enables scientists, researchers, and developers to detect changes, map trends, and quantify differences on the Earth's surface, leveraging Google's cloud infrastructure.

This resource provides access to the book "Cloud-Based Remote Sensing with Google Earth Engine: Fundamentals and Applications." Published by Springer, the book is available for free download as a PDF, offering in-depth material for learning and applying geospatial analysis. It covers essential concepts and practical applications within the Google Earth Engine platform.

Spatial Thoughts provides an open learning platform focused on modern geospatial technologies. It offers hundreds of hours of free, openly accessible, and ad-free learning materials, alongside cohort-based live online instructor-led classes. The platform aims to equip learners with skills to solve complex real-world problems using key open-source tools.

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.

This resource provides a ready-to-use and curated list of spectral indices for various remote sensing applications. It keeps track of both classical and novel indices, ensuring they are standardized and usable across different environments and programming languages. The indices are available in convenient formats like CSV and JSON.