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using social media to detect coastal flooding
Python notebook used for flood maps calculation using ArcGIS' ArcPy package.
Global shoreline mapping tool from satellite imagery
Python labs for COESSING (Coastal Ocean and Environment Summer School in Ghana) 2021
This repo is for all Python/Julia content at COESSING 2022.
Supplementary script for meta-analysis primer
A repository of data on coronavirus cases and deaths in the U.S.
This code provides methodology for preparing flood hazard maps in a replicable way, particularly for the coastal cities where floods pose a recurrent danger because of climate change and its impact on sea level rise. Taking San Francisco, California as an example and using OpenStreetMap data from OSMnx Python Package, our study compiled a crisis map indicating hazard prone areas for evacuation management or emergency access.
This is a repo for the course CSE 499 which contains all the files for the codebase of the project and the presentation files.
Main repository for challenge 31/2022: Flood forecasting: the power of citizen science
Data Analysis with Bootstrap Estimation in R
A collection of data analysis tools for post-processing raw data and importing to python for further analysis.
Data of paper on Coastal Flooding in LAC (Effects of Climate Change on Exposure to Coastal Flooding in Latin America and the Caribbean), by B.G. Reguero, I.J. Losada, P. Díaz-Simal, F.J. Méndez and M .Beck.
Data-driven Bayesian network developer
An ArcGIS toolbox for identifying nested depressions in digital elevation models (DEMs)
Enhanced Bayesian Network for Raster Data
Floods are the most destructive form of natural hazards in both local and global context. This is true in terms of both loss of life and property damage. Early flood forecasting can be used to identify potential areas of flooding in order to develop mitigatory planning and evacuation programs to remove people from such areas during flooding and also to implement suitable preventive measures to avoid damage to properties. In this project, our main objective is to build a flood forecasting system for Mi Oya river basin(Sri Lanka). Mi Oya Basin is heavily affected by seasonal flooding and droughts. As per the available data, floods in the Mi Oya basin are unleashed due to river overflow and reservoir spilling. Out of the several reservoirs located in the basin, Tabbowa and Inginimitiya are crucial in worsening the flood impacts as these two reservoirs are frequently spilling under adverse weather conditions. As such, the prevalence of a real-time flood forecasting model with the incorporation of the reservoir operations for the entire basin is essential to alleviate the flood induced impacts while preserving the optimum volume of water in the major reservoirs in the basin.
Reversing Google's 3D satellite mode
A collection of 300+ Jupyter Python notebook examples for using Google Earth Engine with interactive mapping
This is a repository for course description and agenda.
Earth Lab @ UC Boulder, Colorado - Assessing the Extent of a Flood Event using Python: A Change Detection Approach with Landsat Imagery
Flood Detection with Google Earth Engine
Multitemporal Cloud Masking in the Google Earth Engine
faster implementation of Facebook's Prophet algorithm for time series forecasting
This project lists the resources used to assess the efficacy of multiple coastal adaptation strategies in reducing flooding, economic damages, and impacts on the local population of Santa Monica Bay California.
Flood Mapping Python Toolbox: The FLOod Mapping PYthon toolbox is a free and open-source python toolbox for mapping of floodwater. It exploits the dense Sentinel-1 GRD intensity time series and is based on four processing steps. In the first step, a selection of Sentinel-1 images related to pre-flood (baseline) state and flood state is performed. In the second step, the preprocessing of the selected images is performed in order to create a co-registered stack with all the pre-flood and flood images. In the third step, a statistical temporal analysis is performed and a t-score map that represents the changes due to flood event is calculated. Finally, in the fourth step, a multi-scale iterative thresholding algorithm based on t-score map is performed to extract the final flood map. We believe that the end-user community can benefit by exploiting the FLOMPY's floodwater maps.
Flood Areas Map (Israel) with Google earth engine, geemap library and streamlit
Flood detection with Matlab
A JavaScript code developed in Google Earth Engine (GEE) Platform to Detect Flooded Area along with Affected Population
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.