hurricane-data

On-demand S3 caching of Google Spreadsheets for Tabletop.js, in Python

Classification and analysis of post-storm response imagery

Tropical cyclone intensity change forecast graphic aid

Deep Reinforcement Learning for Hurricane Path Prediction

Unified data sets that summarises the relevant variables (for my Master’s Thesis) of each analysed tropical-cyclone using data from the HURDAT2 and the HadISST1

Hurricane impact analysis pipeline that processes storm envelope data to generate geospatial impact views for schools, health centers, population, and infrastructure. Uses giga-spatial for geospatial processing and generates risk assessments by wind speed thresholds.

Deep reinforcement learning for hurricane path prediction.

Comparing a customised CNN model and Pre-trained MobileNetV2 on image classification of Damaged Houses during a Hurricane

StormDPS is a real-time tropical cyclone analysis tool that computes a Destructive Potential Index using NOAA/NHC data, Integrated Kinetic Energy modeling, storm surge estimates, and regional economic vulnerability analysis. It covers all global basins, features historical storm comparisons, and delivers live weather intelligence for every consumer

Computer.org Contest of the year 2004 to visualize hurricane Data, implemented using matplotlib

CATMOSPHERE-STORM is an updated version of the IH-STORM model (Oderiz et al.) which is itself an improved version of STORM (Bloemendaal et al., 2020), featuring additional functions to prepare non-continuous climatology (including Vertical Wind Shear and adjusted MPI)

Data journalism project on power access across income levels in Gainesville, Florida in the wake of Hurricane Irma.

Project that illustrates how to create a new ggplot2 geom in R.

Synthesizing data from reconnaissance reports conducted by GEER, documenting observed geotechnical failures post-hurricane and a framework for assessing damages by analyzing the types, degrees, and socio-economic impacts of geotechnical failures, alongside their geographical distribution in relation to landfall and trajectory.

Convolutional Neural Network with PyTorch over Post Hurricane Images

The Effect of Global Warming on Hurricane and Typhoon Occurrence

Deep reinforcement learning for hurricane path prediction.

Jupyter Notebook showing my solutions to questions related to sample Category 5 Atlantic Hurricane Data. The data covers the years from 1928 to 2018.

Multi-stage Stochastic Programming for Integrated Network Optimization in Hurricane Relief Logistics and Evacuation Planning

Probabilistic catastrophe risk model for hurricane loss quantification — simulates a 10,000-year synthetic storm catalog (NOAA HURDAT2 + ENOW data) to price tropical cyclone insurance losses at the property level.