Using Google Earth Engine for interactive mapping and analysis of large-scale geospatial datasets
by Qiusheng Wu, University of Tennessee
View recording of this talk on our Coffee Hour Channel.
About the talk
Google Earth Engine is a free cloud computing platform with a multi-petabyte catalog of satellite imagery and geospatial datasets. During the past few years, Earth Engine has become very popular in the geospatial community and it has been used for numerous environmental applications at local, regional, and global scales. In this presentation, I will first introduce the geemap Python package (https://giswqs.github.io/geemap) for interactive mapping and analysis with Earth Engine. Then, I will introduce the Earth Engine plugin for QGIS along with 300+ Python examples. Lastly, I will demonstrate how Earth Engine can be used for automated mapping of surface water and wetland inundation dynamics with 1-m resolution aerial imagery and LiDAR data.
About the speaker
Dr. Qiusheng Wu is an Assistant Professor in the Department of Geography at the University of Tennessee, Knoxville (UTK). His research interests include Geographic Information Science (GIS), remote sensing, and environmental modeling. More specifically, he is interested in applying geospatial big data, machine learning, and cloud computing (e.g., Google Earth Engine) to study environmental change, especially surface water and wetland inundation dynamics. To date, he has published over 40 peer-reviewed journal articles (12 as the first author) in the leading journals in a wide range of fields. Currently, Dr. Wu serves as Associate Editor for the journals Wetlands and Remote Sensing. Dr. Wu is a strong advocate of open science and reproducible research. He has developed and published various open-source packages for advanced geospatial analysis (e.g., geemap, lidar, whitebox-python, whiteboxR, whitebox-ArcGIS), which are available on GitHub (https://github.com/giswqs). More information about his research can be found on his personal website (https://wetlands.io) and YouTube channel (https://www.youtube.com/c/QiushengWu)
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