Rubber Trees and Biomass Estimation Using Remote Sensing Technology

Mohd Hasmadi Ismail, Iqbal Putut Ash Shidiq, Mohammad Firuz Ramli, Norizah Kamarudin, Pakhriazad Hassan Zaki, R. Rokhmatuloh

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


In Southeast Asia, rubber plantation is considered the second largest main crop after oil palm. Hence, it also becomes more critical when seeing rubber as part of the forest ecosystem that possesses an essential biomass and carbon sequestration source. In general, the changes in carbon stocks of the terrestrial ecosystem may have direct implications on the socioeconomics of local communities and biodiversity. However, the process of measuring carbon stock over time is essential to complement climate change mitigation needs. Therefore, there are several numbers or errors in estimating the given carbon pools. It varied from sampling error in the number of plots within the tree’s population, error in measuring soil carbon and stem diameter, and error when applying regression using inventory data or biomass conversion. Unfortunately, the estimation of biomass and carbon fluxes from rubber plantations has been rarely studied. This chapter mainly elaborates the related studies and discussions towards biomass, specifically above-ground biomass (AGB), the accretion of biomass utilization since it was first discovered, the benefit for renewable energy intervention, and the significant role in sequestrating the atmospheric carbon. More importantly, several studies refer to remote sensing applications for biomass quantifications that engage different remote sensing systems. This paper’s main perspective is to give insight into the ability and potential of remote sensing for delivering an efficient spatial approach as the primary tool for rubber plantation biomass estimates.

Original languageEnglish
Title of host publicationConcepts and Applications of Remote Sensing in Forestry
PublisherSpringer Nature
Number of pages30
ISBN (Electronic)9789811942006
ISBN (Print)9789811941993
Publication statusPublished - 1 Jan 2023


  • Allometric equation
  • Biomass
  • Remote sensing
  • Rubber tree
  • Spatial techniques


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