JayThibs / map-floodwater-satellite-imagery
This repository focuses on training semantic segmentation models to predict the presence of floodwater for disaster prevention. Models were trained using SageMaker and Colab.
☆31Updated 2 years ago
Related projects: ⓘ
- ☆66Updated 2 years ago
- This includes short and minimalistic few examples covering fundamentals of Deep Learning for Satellite Image Analysis (Remote Sensing).☆90Updated 3 years ago
- ☆46Updated this week
- Rapid map creation with machine learning and earth observation data.☆66Updated 5 months ago
- Annual and in-season crop mapping in Kenya☆22Updated 3 years ago
- End-to-end workflow for generating high resolution cropland maps☆100Updated last week
- This GitHub repository contains the machine learning models described in Edoardo Nemnni, Joseph Bullock, Samir Belabbes, Lars Bromley Ful…☆51Updated last year
- Land Use and Land Cover Mapping Using Deep Learning Based Segmentation Approaches and VHR Worldview-3 Images☆17Updated 2 years ago
- ☆24Updated 2 years ago
- ☆53Updated 2 months ago
- Enhancement of MODIS NIDVI to 10m resolution using U-Net☆28Updated last year
- Python - Rasterio and Geopandas to calculate Zonal Statistics☆14Updated 4 years ago
- ☆49Updated 11 months ago
- A community-driven effort to make examples, user-defined processes and code snippets available in a single place.☆28Updated this week
- Image segmentation of cultivated land☆26Updated last month
- Machine Learning for Earth Observation Training of Trainers Bootcamp☆92Updated 2 years ago
- Training and deployment of deep learning models for satellite & aerial imagery☆44Updated 2 months ago
- A simple script to create geo-tagged image chips from high-resolution RS images for training deep learning models such as U-net.☆14Updated 3 years ago
- Deep learning for Earth Observation☆52Updated last month
- ☆34Updated last month
- ☆60Updated 3 months ago
- A CNN-RNN based model that identifies correlations between optical and SAR data and exports dense Normalized Difference Vegetation Index …☆40Updated 3 months ago
- A neural gym for training deep learning models to carry out geoscientific image segmentation. Works best with labels generated using http…☆45Updated last month
- List of all datasets included in Google Earth Engine (generated from https://developers.google.com/earth-engine/datasets/catalog/)☆74Updated this week
- Deep Neural Network with keras(TensorFlow GPU backend) Python: Satellite-Image Classification☆36Updated 6 years ago
- A Google Earth Engine API (interactive dashboard) for satellite-based global climate hazard analysis (urban heat, landcover changes, etc)…☆38Updated last year
- ☆40Updated last year
- Winning Solutions from Crop Type Detection Competition at CV4A workshop, ICLR 2020☆63Updated 4 years ago
- ☆35Updated 3 years ago
- Reproducing the "End-to-End Google Earth Engine" course using Jupyter Notebooks and geemap.☆73Updated 3 years ago