Bamboo

Bamboo is one of the fastest-growing species, distributed widely across some of the most biodiverse and carbon-rich areas of the tropics and subtropics in Africa, Asia and South America. With an estimated area of 35 million ha and more than 1 600 species recorded, bamboos are very versatile plants suitable for multiple uses.

To harness this potential, a new, scalable, user-friendly bamboo mapping methodology has been developed using free available satellite imagery and open-source solutions on cloud-based FAO’s Open Foris platforms such as SEPAL and Collect Earth Online, as well as Google Earth Engine. The approach applied across Asia, particularly Myanmar, Thailand and Bangladesh, shows that the methodology is very efficient and accurate. The results establish a robust framework for evidence-based bamboo resource management and policy development.

Developed with support from the AIM4Forests programme, this work was carried out in collaboration with the International Bamboo and Rattan Organization (INBAR) in the framework of a Memorandum of Understanding. Together, the initiative aims to promote bamboo, reduce rural poverty, increasing carbon sequestration, promoting land restoration and green construction.

Background

Despite bamboo's recognized potential for climate change mitigation, with carbon stocks ranging from 94 to 392 tonnes per hectare and annual sequestration reaching 25 tC/ha, its sustainable management remains limited. Several key challenges are:

Limited data availability: Only 23 countries reported bamboo-specific data in FAO's Global Forest Resources Assessment 2020.
Mapping complexity: Bamboo’s spectral similarity to other vegetation types and frequent cloud cover in tropical regions.
Knowledge gaps: Limited information on bamboo species distribution, diversity, and ecosystem services they provide.
Technical barriers: Lack of accessible solutions and methodologies for large-scale assessment.

Mapping bamboo in Asia presents additional difficulties due to the region’s complex terrain, diverse landscapes, and limited ground-truth data. This study addresses these challenges by developing an innovative approach that combines advanced remote sensing with user-friendly cloud computing platforms.

Methodology

The project developed a simple and practical approach to mapping bamboo on a large scale across Asia. The methodology leverages SEPAL platform to make complex time-series analysis accessible in a user-friendly interface, eliminating the need for programming expertise. This approach democratizes bamboo mapping, making it accessible to developing countries and organizations with limited technical capacity. The initial focus has been on:

Myanmar – home to the third-largest bamboo area globally
Thailand – rich in bamboo diversity, with 69 species across 17 genera
Bangladesh (Chittagong Division) – characterized by extensive Melocanna baccifera forests

Methods

Sentinel-1 (SAR) and Sentinel-2 (optical) time-series data (2021-2024)
Ancillary data: SRTM elevation and ETH global canopy height datasets

Utilizes the CCDC (Continuous Change Detection and Classification) algorithm
Extracts phenological characteristics (amplitude, phase, slope) that capture seasonal bamboo dynamics
Time-series features proved most important for classification (36-49% contribution)

Vegetation indices: NDVI, EVI, GCVI, MTCI, NDFI, Bamboo Index
Texture features: GLCM-derived metrics for spatial patterns
Topographic data: Elevation, slope, aspect, and coordinates

Multi-source approach: National forest inventory data + global land cover datasets
Collect Earth Online (CEO): Visual interpretation with high-resolution imagery

Random Forest classifier with optimized parameters
Validation: 70/30 train-test split
Achieves high classification accuracy (90–96%) and strong kappa coefficients (0.81–0.89).

Bamboo Resources Assessment in Chittagong Region, Bangladesh - a methodological approach using SEPAL

10/07/2025

The presentation titled “Bamboo Resources Assessment in Chittagong Region, Bangladesh: A Methodological Approach Using SEPAL” was delivered during the...

Bamboo Resources Assessment in Myanmar - a methodological approach using SEPAL

10/07/2025

The presentation titled “Bamboo Resources Assessment in Myanmar: A Methodological Approach Using SEPAL” was delivered during the Global Forest Resources...

Bamboo Resources Assessment in Thailand - a methodological approach using SEPAL

10/07/2025

The presentation titled “Bamboo Resources Assessment in Thailand: A Methodological Approach Using SEPAL” was delivered during the Global Forest Resources...

Bamboo resources assessment - A methodological approach using SEPAL with case studies in Asia

13/08/2025

This study proposes a simple and practical approach to mapping bamboo on a large scale in Southeast Asia with the help of cloud-computing tools, including...