PyGMTSAR (Python InSAR): Powerful and Accessible Satellite Interferometry
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Updated
May 27, 2024 - Jupyter Notebook
PyGMTSAR (Python InSAR): Powerful and Accessible Satellite Interferometry
Fractal alert is a repository for developing an effective warning system that would predict and prevent the impact of natural disasters such as earthquake, hurricanes, floods, etc.
Detects emergency situations using an React-Native app and Firebase
Jupyter Notebook for representing the data of world-natural-disaster events
Graduate deep learning course projects: Physics-informed neural networks for simulating physical systems and CNN-based wildfire prediction models.
Repository for model of models development.
Alert users of impending Disasters near them, provide them with relief info.
the natural disaster algerian api
A Django application to archive real-time earthquake notifications from the USGS's Advanced National Seismic System
[🥉 3rd place] Detect damaged building by natural disasters and get a brief information about it.
Modular structure that feeds on instant data, warns about natural disasters and conveys what needs to be done
[WIP] Get smart insights, alerts & warnings about predicted natural disasters and take precautions before they arrive to keep family, friends & yourself safe.
The PyDisaster project uses a master function that extracts GPS location and EXIF data from photos submitted to our Flask application platform, and opens a Google Maps search of the location. This project is geared towards helping FEMA conduct damage assessments in areas effected by natural disasters.
Messiah: The Mighty Son Of God Is Here To Help You Through Times Of Calamity
It contains codes and documentations within the scope of the Special Topics in Remote Sensing course
Repository to preview, describe, and link to Tableau dashboard.
Using Observable to make data visualizations
Exploring deaths by natural disasters, and possible relations to climate change.
ResQ is a socially responsible Flutter Application. It assists the flood rescue operations.
Prediction of market premiums for property damage and business interruption insurance products. Added natural hazard data and stacked 3 best models as the final model.
Add a description, image, and links to the natural-disasters topic page so that developers can more easily learn about it.
To associate your repository with the natural-disasters topic, visit your repo's landing page and select "manage topics."