Case Study Data Science GEO and GIS Jupyter Python 3See in schedule
In this talk, we will show you the use of GRASS GIS (Geographic Resources Analysis Support System - Geographical Information System) and other geospatial Python libraries within a Jupyter Notebook to simulate wildfire spread in Yosemite National Park California USA. We will also show you a straightforward workflow to obtain and save input geospatial data for wildfire simulation using Google Earth Engine (GEE) Python API, GeoPandas, and geemap (a Python package for interactive mapping with GEE). GRASS GIS commands are generally run into bash shells, thus in this talk, we will demonstrate how we run GRASS GIS commands from Jupyter notebook to model wildfire behavior and display the resulting maps. We expect the audience has a basic understanding of GIS, Remote Sensing, and Python programming.
Type: Talk (30 mins); Python level: Beginner; Domain level: Beginner
I'm an agronomist specialized in geomatics. My research interests include Geographical Information System (GIS), Remote Sensing, and Geographical Data Science. My professional and scientific experience includes spatial analysis and Remote Sensing image analysis using Google Earth Engine and Python geospatial libraries. I have also developed web mapping applications using open-source software. I have published articles in both geospatial journals and Data Science blogs. I hold a bachelor's degree in Agronomy and a postgraduate diploma in Geomatics from the Central University of Venezuela.