Objective

The objective of this project is to create a comprehensive and unified spatial dataset representing all mangrove forest areas across Bangladesh. This project aims to map the entire national mangrove coverage by converting raster-based mangrove data into a clean, dissolved vector polygon suitable for area calculation and further geospatial analysis.

Data Acquisition

1. Administrative Boundary: The FAO GAUL (2015) dataset provided the national boundary of Bangladesh to clip the global data.

2. Mangrove Baseline Data: The Global Mangrove Forests Distribution (2000) dataset from Landsat served as the primary source for identifying mangrove pixels worldwide.

Data Processing

The processing pipeline was designed to create a clean, national-level mangrove map:

1. Clipping: The global mangrove raster was clipped to the Bangladesh boundary.

2. Mask Creation: A binary mask was created where pixels classified as mangroves have a value of 1, and all other areas are 0.

3. Raster to Vector Conversion: The reduceToVectors function was used to convert the mangrove pixels into vector polygons.

4. Noise Reduction: Small, potentially erroneous polygons were filtered out using a threshold based on pixel count (count > 50).

5. Geometry Dissolving: All the individual mangrove polygons were merged into a single, unified geometry using the dissolve() method, creating one continuous feature representing the total mangrove forest area.

Data Analysis

The key analytical output is the total area of mangrove forests in Bangladesh, calculated directly from the final dissolved geometry. The analysis also involved:

• Quantifying the number of individual mangrove patches before the merge.

• Visualizing the national distribution of mangroves, highlighting the Sundarbans as the dominant feature.

• Creating a clean, ready-to-use asset for future projects that require a precise mangrove boundary.

Potential Usage and Impact

• National Resource Inventory: Provides an authoritative map for government agencies to quantify and monitor national mangrove resources.

• Conservation Planning: Essential for creating protected area boundaries and managing forest resources.

• Climate Policy and Carbon Accounting: Serves as a baseline for calculating blue carbon stocks and reporting under initiatives like REDD+.

• Disaster Risk Reduction: Informs coastal zone management plans by identifying where mangroves provide natural storm surge protection.

• Comparative Studies: Allows for comparison with mangrove extents in other countries or with future national-level maps to assess change.GitHub Code Link: https://github.com/mohammadoney/Mangrove-Extent-Mapping/blob/main/Code