The "Flood Mapping Using Deep Learning" YouTube playlist delves into the innovative application of deep learning techniques to effectively map and analyze floods. This comprehensive series explores various methodologies, algorithms, and models employed in the domain of flood mapping, leveraging the power of neural networks and advanced machine learning. From fundamental concepts to advanced strategies, each video in this playlist offers insights into the utilization of deep learning frameworks for flood detection, prediction, and mapping. Viewers will gain a deep understanding of how convolutional neural networks (CNNs), recurrent neural networks (RNNs), and other deep learning architectures can process satellite imagery, sensor data, or geographic information system (GIS) data to accurately detect, monitor, and map floodprone areas. Whether you're a researcher, a data enthusiast, or a practitioner in the field, this playlist serves as a valuable resource for exploring the intersection of deep learning and flood mapping, showcasing its potential impact on disaster management and environmental conservation.

Full playlist:    • Flood mapping using Deep Learning  

Dataset: https://www.kaggle.com/datasets/faiza...

Notebook: https://github.com/iamtekson/deeplea...

Sent12 flood dataset: https://clmrmb.github.io/SEN12FLOOD/

Timestamps:
0:00 Intro
0:24 Quick recap on methodology
1:08 Accuracy metrics for image segmentation
2:25 Quick recap on CustomDataGenerator and Attention Unet
4:31 Train and test dataset split
7:18 Accuracy metrics (f1score, dice score, precision, recall)
8:11 Training attention unet model
11:24 Model evaluation
14:56 Testing model using random images from google
20:18 Outro (Sent12 Flood dataset)



Here are some playlists that you might be interested in:

End to End deep learning using GEE dataset:    • End to End Deep Learning | From data ...  
Deep Learning for Satellite Imagery:    • Deep learning for satellite imagery |...  
Machine learning from the basic:    • Machine Learning for geospatial data  
Historical Imagery Processing:    • Historical Imagery processing | KH9 ...  
Leaflet from basic to advance:    • Leaflet from basic to advance  
GeoServer with leaflet webGIS:    • GeoServer and Leaflet WebGIS  
GeoDjango project:    • Bookmark note on map | GeoDjango tuto...  
geoserverrest:    • geoserverrest  
GIS training in Nepali:    • Beginner GIS training in Nepali | Arc...  
LULC map production:    • LandUse Land Cover Map production || ...  
Geospatial analysis with python:    • GeoSpatial analysis with python  
GeoNode from basic to advance:    • GeoNode from basic to Advance  


Check out my discounted courses at the following link:

1. "Geospatial data analysis with python": https://www.udemy.com/course/geospati...
2. "Web GIS Development 2021": https://www.udemy.com/course/webgis...
3. "Web mapping and WebGIS from Dev to Deploy 2021: GeoDjango": https://www.udemy.com/course/webmapp...
4. "Introduction to Web Mapping and Web GIS 2020: GeoDjango": https://www.udemy.com/course/introduc...
5. Deep Learning Application for Earth Observation: https://www.udemy.com/course/deeplea...
6. Geospatial Data Analysis with Python: https://www.udemy.com/course/geospati...


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