The Earth is rapidly changing, and this change has numerous important environmental and societal impacts. There is a strong need to understand these changes at a global scale in high resolution so that we might reverse or adapt to them.
Access to public Earth observation and model data is exploding, driven by recent satellite launches by government, intergovernmental agencies, and private organizations as well as Earth system model simulations run by institutions around the world. Given this deluge of data, the old paradigm of downloading raw data for local processing is highly limiting. New approaches are needed. To address this, many organizations are building cloud- or HPC-based platforms that allow filtering, aggregation, and complex processing prior to transferring data to users. Jupyter Project technologies are increasingly useful for providing access to these large Earth science data stores and analysis platforms.
Tyler Erickson highlights the use of JupyterLab and Jupyter widgets in analyzing complex high-dimensional datasets, providing insights into how our Earth is changing and what the future might look like.
While the case studies will use Google’s Earth Engine platform, the techniques demonstrated are applicable to most remote geospatial platforms that provide API access.
Tyler A. Erickson is a senior developer advocate at Google, where he fosters collaborations with researchers from academia, NGOs, and governmental organizations seeking to capitalize on Earth Engine’s capabilities for geospatial analyses that involve immense satellite and model-based datasets. Tyler leads the development of Earth Engine’s core efforts in water and climate, guides the evolution of Earth Engine to support these scientific domains, and leads support efforts for the Earth Engine Python API. A snow hydrologist by training, he holds degrees in civil and environmental engineering and geography from Colorado State University, CalTech, Stanford, and the University of Colorado at Boulder. Tyler is a longtime Python programmer, with contributions to the Open Source Geospatial (OSGeo) Foundation and the Free and Open Source Software for Geospatial (FOSS4G) conferences.
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