Tropical rain forest tree height measurement using ALS and TLS for estimating forest biomass and carbon stock in Ayer Hitam Forest, Malaysia

Ojoatre Sadadi, Y.A. Hussin*, H. Kloosterman, Mohd Hasmadi Ismail

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)


Forests play a major role in climate change through their unique nature of carbon sequestration which regulates the global temperatures. Climate change is directly attributed to changes in global atmospheric conditions over a given period. This requires actions towards its mitigation and hence various bodies have come up with a number of initiatives geared towards comparting climate change, for example the UNFCCC with its REDD+ (Reducing Emissions from Deforestation and forest Degradation) program. REDD+ aims at accurately quantifying the sources and sinks of carbon, and therefore has designed Measurement Reporting and Verifications (MRVs) system for its implementing countries. The REDD+ MRVs require accurate measurements. This help in quantifying the biomass/carbon stock and establish the amount of carbon sequestered. The biomass estimation equations require tree parameters like Height and Diameter at Breast Height (DBH) as an input. Therefore, there is a need to measure tree height and diameter at breast height accurately. Studies have shown that, the tree height is one of the most difficult forest parameters to be measured, yet can be mapped and measured accurately using remote sensing most notably LiDAR Technology. There is no standard set for the height measurement using the hypsometers. However, the data collected using the hypsometers are considered as the data for validation of the remotely sensed data. This possibly leads to errors which must be minimized. The error is then transferred in to the AGB biomass/carbon estimation. This study is therefore aimed at establishing methods that ensure reasonable accuracy of tree height measurement using both Airborne LiDAR and Terrestrial Laser Scanner.

Original languageEnglish
Number of pages10
Publication statusPublished - 1 Jan 2016
Event37th Asian Conference on Remote Sensing, ACRS 2016: Spatial Data Infrastructure for Sustainable Development - Colombo, Sri Lanka
Duration: 17 Oct 201621 Oct 2016
Conference number: 37


Conference37th Asian Conference on Remote Sensing, ACRS 2016
Abbreviated titleACRS
Country/TerritorySri Lanka
Internet address


  • Airborne LiDAR
  • Carbon stock
  • Terrestrial Laser Scanner
  • Tree height
  • Tropical forest

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