Satellite Remote Sensing & GIS for Seagrass Mapping and Coastal Conservation

Aim

Workshop Objectives

Workshop Structure

Day 1: Satellite Remote Sensing & GIS for Coastal Habitat Analysis

Topics Covered:

• Fundamentals of satellite remote sensing and GIS applications in coastal and marine ecosystems.
• Seagrass ecology, coastal habitat characteristics and blue carbon ecosystems.
• Spectral characteristics of seagrass, water, sand and other shallow-water habitats.
• Introduction to Sentinel-2, Landsat, Google Earth Engine and Python-based geospatial analysis.
• Satellite image acquisition, coastal study-area selection and data visualization.
• Image preprocessing: cloud masking, spectral band combinations and image compositing.
• Challenges in underwater habitat mapping: water depth, turbidity, tides and sun glint.

Hands-on: Coastal Satellite Image Processing

• Acquire and preprocess Sentinel-2 imagery, apply cloud masking and generate coastal image composites using Google Earth Engine.
• Explore spectral data using Python in Google Colab and visualize processed coastal imagery using QGIS.

Tools: Google Earth Engine, Sentinel-2, Google Colab, Python, QGIS

Learning Outcome: Prepare, process and visualize satellite imagery for coastal habitat mapping and geospatial analysis.

Day 2: Machine Learning-Based Seagrass Mapping & GIS Classification

Topics Covered:

• Spectral feature extraction and identification of shallow-water habitat characteristics.
• Selection of satellite spectral bands and classification features.
• Preparation of reference samples and training datasets using Python and Pandas.
• Supervised machine learning and Random Forest classification.
• Classification of seagrass, bare sediment and other relevant coastal habitats.
• Habitat distribution mapping and spatial pattern interpretation.
• Model validation using confusion matrices, overall accuracy, precision, recall and F1-score.
• GIS-based habitat area estimation and spatial analysis using QGIS.

Hands-on: AI-Based Seagrass Habitat Classification

• Train a Random Forest classifier using reference samples and map seagrass habitats in Google Earth Engine.
• Evaluate classification results using Python and Scikit-learn in Google Colab; estimate seagrass extent and prepare habitat maps in QGIS.

Tools: Google Earth Engine, Google Colab, Python, Scikit-learn, Random Forest, Sentinel-2, QGIS

Learning Outcome: Develop and validate a machine-learning-based seagrass classification workflow and generate accurate GIS-based habitat distribution maps.

Day 3: Coastal Habitat Change Detection, Blue Carbon Assessment & Conservation Planning

Topics Covered:

• Multi-temporal satellite remote sensing for coastal ecosystem monitoring.
• Seagrass habitat change detection using multi-year satellite-derived classifications.
• Assessment of habitat persistence, apparent loss and potential recovery.
• Python-based spatial data analysis and visualization of coastal habitat changes.
• Introduction to blue carbon stocks and the ecological role of seagrass ecosystems.
• Integration of satellite-derived habitat extent with field-based carbon-density data.
• Preliminary blue carbon stock estimation using Python and uncertainty assessment.
• GIS-based identification of conservation and restoration priority zones.
• Integration of marine protected areas and coastal environmental datasets.
• Scientific interpretation and visualization of coastal habitat monitoring results.

Hands-on: Coastal Habitat Monitoring & Blue Carbon Assessment

• Compare multi-temporal seagrass maps using Google Earth Engine and QGIS; quantify habitat changes using Python in Google Colab.
• Estimate preliminary blue carbon stocks using Python and supplied carbon-density data; prepare GIS-based conservation priority maps.

Tools: Google Earth Engine, Google Colab, Python, Pandas, NumPy, Matplotlib, QGIS, Blue Carbon Reference Data

Learning Outcome: Analyze coastal habitat changes, estimate preliminary blue carbon stocks and develop GIS-based conservation planning maps.

Who Should Enrol?

Important Dates

Workshop Outcomes

Fee Structure