ml4floods
Flood estimator
An end-to-end machine learning pipeline for flood extent estimation from satellite images
An ecosystem of data, models and code pipelines to tackle flooding with ML🌊
142 stars
17 watching
41 forks
Language: Jupyter Notebook
last commit: 6 months ago
Linked from 1 awesome list
protontypes/open-sustainable-technologyRelated projects:
| Repository | Description | Stars |
|---|---|---|
 cloudtostreet/modis_globalflooddatabase | Provides tools and data for analyzing flood events and estimating population exposure to floods using satellite imagery. | 96 |
 nrcan/ricorde | Software that generates gridded water depth estimates from flood inundation data using machine learning and algorithms. | 3 |
 codeslake/dmenet | A deep learning implementation of defocus map estimation using domain adaptation | 124 |
 ecmwfcode4earth/ml_drought | Develops machine learning models to predict and understand drought using climate science data | 93 |
 jensdebruijn/global-flood-monitor | Detects floods in real-time using social media data and creates a global database of historic flood events | 26 |
 noaa-owp/ras2fim | Automates flood inundation mapping from HEC-RAS models to support real-time and predictive floodplain mapping. | 50 |
 panda5mt/depth_estimate_blur | This project develops software for depth estimation using defocus blur in images captured by automotive cameras. | 55 |
 geospatialresearch/digital-twins | An application that simulates physical assets' performance under future flood scenarios using geographic data and machine learning models. | 16 |
 mikejohnson51/floodmapping | Tools for mapping flood extents from National Water Model data | 30 |
| codeslake/syndof | An implementation of a defocus map estimation technique using domain adaptation and synthetic data generation | 53 |
 orion-ai-lab/kurosiwo | A large-scale dataset and software framework for remote sensing-based flood mapping using SAR data | 44 |
 servir-mekong/hydra-floods | A Python package for analyzing remote sensing data to produce high-quality surface water maps in near real-time. | 167 |
 zzangjinsun/dhde_cvpr17 | An image processing algorithm for estimating the defocus of an image | 59 |
 kleok/floodpy | A Python toolbox for mapping non-urban flooded regions using satellite data and machine learning algorithms | 173 |
| spaceml-org/starcop | A framework for training and deploying hyperspectral machine learning models for methane plume detection from satellite imagery | 44 |