Spatio-Temporal Hurricane Tracking in the Gulf of Mexico with QGIS and PyQGIS - Tutorial

SpatioTemporalQGIS.PNG

QGIS is a great software for the processing/analysis of spatial data, Python is a clear, powerful programming lenguaje; together they can enhance the spatial analysis to solve more complex or more dedicated problems in less time. PyQGIS is the Python environment inside QGIS with a set of QGIS libraries plus the Python tools with the potential of running other powerful libraries as Pandas, Numpy or Scikit-learn. 

At the date of this post QGIS 3 was not officially launched. QGIS3 will run with Python 3 and interactive scripting as Jupyter notebook. With the Python 3 tools in QGIS, the capabilities and speed in geospatial data processing will be huge and QGIS will become a key instrument for the understanding of different phenomena in our society as climate change, money laundering and criminality.

This tutorial shows a mixed procedure with native QGIS tools and PyQGIS commands for the data representation, styling and plotting regarding spatio-temporal criteria with the TimeManager plugin. Data for this tutorial was downloaded from the National Hurricane Center's Tropical Cyclone Reports that contains information as six-hourly positions and intensities. You can access the whole hurricane database on this link:

http://www.nhc.noaa.gov/data/tcr/index.php?season=2016&basin=atl

 

Animation

 

Tutorial

 

Input data

You can download the input data from this link.

Saul Montoya

Saul Montoya es Ingeniero Civil graduado de la Pontificia Universidad Católica del Perú en Lima con estudios de postgrado en Manejo e Ingeniería de Recursos Hídricos (Programa WAREM) de la Universidad de Stuttgart con mención en Ingeniería de Aguas Subterráneas y Hidroinformática.

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