Qiusheng Wu

This session delves into cutting-edge tools and applications of Google Earth Engine to address critical environmental challenges. Discover how users are empowered to visualize and analyze GEE data with geemap, a powerful interactive mapping tool, and explore automated decision-support reporting for resource management, leveraging the scalability of Earth Engine and Google Cloud.

This presentation will highlight the key features of the leafmap Python package for interactive visualization and analysis of geospatial data with minimal coding in a Jupyter environment.

This workshop aims to bridge the gap between big geospatial data and research scientists by providing training on an open-source online platform for managing big drone and satellite data.

Google Earth Engine's new data extraction interfaces seamlessly transfer geospatial data into familiar Python formats provided by NumPy, Pandas, GeoPandas, and Xarray. This integration empowers you to harness Earth Engine's vast data catalog and compute power directly within your preferred Python workflows.

Image segmentation plays a crucial role in extracting valuable insights from geospatial data. While traditional segmentation methods can be laborious, deep learning offers automation but often demands extensive training and resources.

Get all the latest news on our efforts to improve the Earth Engine + Python developer experience. Topics will include increased doc coverage, notebook environment options, data interoperability, and support for geemap.

This workshop provides an introduction to cloud-based geospatial analysis using the Earth Engine Python API. Attendees will learn the basics of Earth Engine data types and how to visualize, analyze, and export Earth Engine data in a Jupyter environment with geemap .

This workshop provides an introduction to cloud-based geospatial analysis using the Earth Engine Python API. Attendees will learn the basics of Earth Engine data types and how to visualize, analyze, and export Earth Engine data in a Jupyter environment with geemap .

This workshop provides an introduction to cloud-based geospatial analysis using the Earth Engine Python API. Attendees will learn the basics of Earth Engine data types and how to visualize, analyze, and export Earth Engine data in a Jupyter environment with geemap .

This workshop provides an introduction to cloud-based geospatial analysis using the Earth Engine Python API. Attendees will learn the basics of Earth Engine data types and how to visualize, analyze, and export Earth Engine data in a Jupyter environment with geemap .

This tutorial is an introduction to cloud-based geospatial analysis with Earth Engine and the geemap Python package. We will cover the basics of Earth Engine data types and how to visualize, analyze, and export Earth Engine data in a Jupyter environment using geemap.

Google Earth Engine is a cloud-computing platform with a multi-petabyte catalog of satellite imagery and geospatial datasets. Built upon the Earth Engine Python API and open-source mapping libraries, geemap enables Earth Engine users to interactively manipulate, analyze, and visualize geospatial big data in a Jupyter environment.