CyberFaCES - Learn: Mini-Workshop: CyberTraining on Geospatial Data Processing using Python for Hydrology

Mini-Workshop: CyberTraining on Geospatial Data Processing using Python for Hydrology

6 modules

About

The hands-on tutorial aims to train participants in accessing and processing geospatial data for hydrologic applications using cyberinfrastructure, with a focus on FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. The training will focus on accessing high-resolution Digital Elevation Model (DEM) data from the USGS 3D Elevation Program (3DEP) hosted on Amazon Web Services (AWS) for any location within the CONUS, and on processing DEM data for hydrologic applications. Typically, hydrology researchers rely on GUI-based tools such as ArcGIS and QGIS for their geospatial operations. However, performing repetitive tasks on multiple areas of interest can be time-consuming and redundant. By adopting Python-based workflows, participants can streamline these operations and efficiently handle repetitive tasks, leading to increased productivity and minimized redundancy.

Objectives

To gain knowledge in accessing and processing geospatial data for hydrologic applications using Python-based Jupyter Notebooks.
To develop the skills to process digital elevation model (DEM) data specifically tailored for hydrologic applications, enhancing your expertise in the field.
To learn how to transition from GUI-based tools like ArcGIS and QGIS to Python-based workflows, enabling you to streamline operations to enhance productivity and reduce redundancy in hydrological research.

Features
Type	Course
Level	Developer
Length	3 hours

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Modules

Pre-workshop Survey [Apr 2025]

Module 1
Geospatial & Hydrological Science: DEM Access and Visualization from USGS AWS [v09]

Module 2 • 150 days
Geospatial & Hydrological Science: DEM Processing and Topographic Wetness Index (TWI) [v2e]

Module 3
Geospatial & Hydrological Science: HPC Based DEM Accessing and Processing (Single Job)

Module 4 • 1 hour
Assessment for DEM Processing

Module 5
Post-workshop Survey [Apr 2025]

Module 6