feat: ✨ added flood multimodal workshop notebook

workshop/README.md

@@ -45,7 +45,12 @@ This workshop provides a complete learning path for IBM Geospatial Studio, desig
    - Fine-tuning models
    - Deploying and monitoring
 
-**Total Workshop Time**: 4.5 - 6 hours
+5. **Lab 5: Multimodal Flood Detection with TerraMind** (90-120 minutes)
+   - Working with multimodal satellite data (SAR + Optical)
+   - Training TerraMind foundation model
+   - Advanced multimodal inference workflows
+
+**Total Workshop Time**: 6 - 8 hours
 
 ## 🚀 Quick Start
 

workshop/docs/index.md

@@ -18,14 +18,15 @@ This workshop is designed for beginners who have never heard of Geospatial Studi
 
 ## ⏱️ Workshop Duration
 
-**Total Time:** Approximately 3-4 hours
+**Total Time:** Approximately 5-6 hours
 
 - **Pre-work:** 1-1.5 hours (deployment and setup)
 - **Introduction:** 15 minutes (reading)
 - **Lab 1 - Getting Started with IBM Geospatial Studio:** 10 minutes (Beginner)
 - **Lab 2 - Onboarding Pre-computed Examples:** 20 minutes (Beginner)
 - **Lab 3 - Upload Model Checkpoints and Run Inference:** 30 minutes (Intermediate)
 - **Lab 4 - Training a Custom Model for Wildfire Burn Scar Detection:** 60-90 minutes (Intermediate, includes model training)
+- **Lab 5 - Training a Multimodal Model for Flood Detection:** 90-120 minutes (Advanced, includes multimodal training)
 
 ## 🎓 Target Audience
 
@@ -49,7 +50,7 @@ cd geospatial-studio/workshop/docs/notebooks
 
 This repository includes:
 
-- ✅ All lab notebooks (Lab 1-4)
+- ✅ All lab notebooks (Lab 1-5)
 - ✅ JSON configuration files (model templates, datasets, backbones)
 - ✅ Sample data references
 - ✅ Complete workshop documentation
@@ -109,6 +110,13 @@ Complete an end-to-end workflow: onboard a training dataset, fine-tune a foundat
 
 **Note:** This lab requires GPU access for model training. If GPUs are not available, you can use an existing fine-tuned model or train outside Studio using TerraTorch.
 
+### Lab 5: Training a Multimodal Model for Flood Detection with TerraMind
+Advanced multimodal workflow combining Sentinel-1 SAR and Sentinel-2 optical data. Learn to work with TerraMind foundation model, configure multimodal datasets, and run inference with multiple sensor modalities for robust flood detection.
+
+**Time:** 90-120 minutes (includes multimodal training) | **Difficulty:** Advanced
+
+**Note:** This lab uses TerraMind Tiny which can run on CPU (2-4 hours) or GPU (60-90 minutes). Demonstrates real-world disaster response scenarios with complementary sensor data.
+
 ## 🚀 Getting Started
 
 1. **Complete the Pre-work** - Deploy Geospatial Studio in your environment

workshop/docs/introduction/welcome.md

@@ -55,13 +55,15 @@ graph LR
     C --> D[Lab 2<br/>Onboard Examples]
     D --> E[Lab 3<br/>Upload & Infer]
     E --> F[Lab 4<br/>Train Model]
+    F --> G[Lab 5<br/>Multimodal AI]
 
     style A fill:#0f62fe,stroke:#fff,color:#fff
     style B fill:#8a3ffc,stroke:#fff,color:#fff
     style C fill:#33b1ff,stroke:#fff,color:#fff
     style D fill:#42be65,stroke:#fff,color:#fff
     style E fill:#ff7eb6,stroke:#fff,color:#fff
     style F fill:#fa4d56,stroke:#fff,color:#fff
+    style G fill:#ee5396,stroke:#fff,color:#fff
 ```
 
 ## ⏱️ Time Breakdown
@@ -74,7 +76,8 @@ graph LR
 | **Lab 2** | 20 minutes | Onboarding Pre-computed Examples (Beginner) |
 | **Lab 3** | 30 minutes | Upload Model Checkpoints and Run Inference (Intermediate) |
 | **Lab 4** | 60-90 minutes | Training a Custom Model for Wildfire Burn Scar Detection (Intermediate) |
-| **Total** | ~3-4 hours | Including breaks |
+| **Lab 5** | 90-120 minutes | Training a Multimodal Model for Flood Detection (Advanced) |
+| **Total** | ~5-6 hours | Including breaks |
 
 ## 🎓 Workshop Format
 

workshop/docs/notebooks/README.md

@@ -65,6 +65,23 @@ Complete an end-to-end workflow:
 
 ---
 
+### Lab 5: Training a Multimodal Model for Flood Detection with TerraMind
+**File:** `lab5-flood-multimodal-workflow.ipynb`
+
+Advanced multimodal workflow:
+- Work with multimodal satellite data (Sentinel-1 SAR + Sentinel-2 optical)
+- Onboard and configure multimodal training datasets
+- Register and configure TerraMind foundation model
+- Submit and monitor multimodal fine-tuning
+- Run inference with multiple sensor modalities
+- Understand complementary sensor fusion for robust predictions
+
+**Estimated Time:** 90-120 minutes (includes multimodal training) | **Difficulty:** Advanced
+
+**Note:** Uses TerraMind Tiny which can run on CPU (2-4 hours) or GPU (60-90 minutes). Demonstrates real-world disaster response scenarios.
+
+---
+
 ## How to Use These Notebooks
 
 ### Prerequisites
@@ -93,7 +110,7 @@ jupyter notebook
 
 **Why the full repository is required:**
 
-- ✅ Notebooks reference JSON configs from `populate-studio/payloads/`
+- ✅ Notebooks reference JSON configs from shared directories
 - ✅ Proper directory structure for all file paths
 - ✅ Easy to update with `git pull`
 - ✅ Access to all workshop materials and shared resources
@@ -130,6 +147,7 @@ These notebooks are adapted from the official Geospatial Studio examples:
 - **Lab 2:** Based on [`002-Add-Precomputed-Examples.ipynb`](https://github.com/terrastackai/geospatial-studio-toolkit/blob/main/examples/inference/002-Add-Precomputed-Examples.ipynb)
 - **Lab 3:** Based on [`001-Introduction-to-Inferencing.ipynb`](https://github.com/terrastackai/geospatial-studio-toolkit/blob/main/examples/inference/001-Introduction-to-Inferencing.ipynb)
 - **Lab 4:** Based on [`GeospatialStudio-Walkthrough-BurnScars.ipynb`](https://github.com/terrastackai/geospatial-studio-toolkit/blob/main/examples/e2e-walkthroughs/GeospatialStudio-Walkthrough-BurnScars.ipynb)
+- **Lab 5:** Based on [`GeospatialStudio-Walkthrough-Flooding.ipynb`](https://github.com/terrastackai/geospatial-studio-toolkit/blob/main/examples/e2e-walkthroughs/GeospatialStudio-Walkthrough-Flooding.ipynb)
 
 ---