Landslide Predicting Program for KU Hackfest 2022

A simple landslide detection project using Google Earth Engine, Python, HTML and CSS.

Team Members

prediction of prevelence of landslide in landslide prone areas using image analysis of satellite images
using the analysis in addition with the local soil and weather data to accurately predict the occurance of landslide
on site analysis of soil for further risk acessment
using twilio for communication to the affected group by landlides.

types of soil and it's effect on causation of landslides Relations Between Soil Development and Landslides Arnaud J.A.M. Temme Although landslides can occur in practically all soil types, maps of soil types and soil properties are often and successfully used as copredictors in statistically based landslide susceptibility modeling.
Classification of soil by fao base on the properties of soil https://www.fao.org/3/i3794en/I3794en.pdf
Numerically represent the data obtained from the image classification of satellite imagary higher value for soil types with higher probability of landslides

For the given input

We obtained the following output which shows the possibility of Landslides in the given areas

Name		Name	Last commit message	Last commit date
Latest commit History 34 Commits
.ipynb_checkpoints		.ipynb_checkpoints
Front end		Front end
data		data
datasets		datasets
README.md		README.md
Untitled.ipynb		Untitled.ipynb
data_crunch.py		data_crunch.py
project.ipynb		project.ipynb
rainfall_gee.js		rainfall_gee.js
slope_gee.js		slope_gee.js
tempCodeRunnerFile.py		tempCodeRunnerFile.py