Importance of artificial intelligence on forest biomass evaluation in Perú - Ormachea Ramos, Álvaro Manuel (2024)
This article explains basic concepts of Artificial Intelligence (AI) linked to forest biomass estimation, and reviews three research studies carried out in tropical areas using AI models with traditional allometric equations. The results show that AI-based methods have greater accuracy and ability to relate key variables in forest biomass development than allometric equations. These facts highlight the need for Peruvian forest engineers to develop capabilities for the use of AI in the estimation of forest biomass in the country. This capacity building would imply a more demanding curriculum in mathematics, statistics and computer science for forest engineers; as well as the installation of an extensive network of permanent plots for the creation of a solid database of the variables involved in the development of forest biomass. It is proposed to start a discussion on the subject among the Peruvian forestry community in order not to lose opportunities in the carbon credits market, which, according to the cases reviewed, will require more precise measurements than the current ones carried out through the use of allometric equations.