Integration of VANT-LiDAR with multispectral imagery for the estimation of carbon stocks in Prosopis sp. forest plantations

• Autores: Chumbimune-Vivanco, Sheyla Y., León, Hairo, Llanos-Carrillo, Cristina, Millan-Ramírez, José, Vilca-Gamarra, Cesar, Vera, Elvis, Agurto, Alex, Baselly-Villanueva, Juan R., Cruz-Grimaldo, Camila
• Formato: artículo
• Fecha de Publicación: 2025
• Institución: Universidad Nacional de Trujillo
• Repositorio: Revistas - Universidad Nacional de Trujillo
• Lenguaje: español
• OAI Identifier: oai:ojs.revistas.unitru.edu.pe:article/6386
• Enlace del recurso: https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/6386
• Nivel de acceso: acceso abierto
• Materia: UAV; LiDAR; biomass; carbon stocks; vegetation indices; VANT; biomasa; carbono almacenado; índices de vegetación

The Prosopis sp. individuals known as carob trees are key species in the development of dry forest and recovery of degraded areas in the northern coast of Peru. The evaluation of plantations, calculation of aboveground forest biomass (AFB) and carbon stock represent an important role in forest management and climate change mitigation. This study evaluates monitoring methodologies using multispectral and LiDAR images coupled to a UAV, to validate them and generate models to estimate carbon stocks. Seven species of Prosopis sp. were evaluated with the conventional methodology and significant differences were found between species for dasometric characteristics and vegetation indices, as well as in the comparison with the data obtained with LiDAR. Models were selected to determine BAF and the association between the aerial carbon obtained with the models constituted by LiDAR data and vegetation indexes that presented significant correlations (p < 0.05), seven models were built for carbon prediction and the model that has as regressor variables the total height and crown area obtained from LiDAR, as well as the indexes CIgreen, GNDVI, RECI, LCI and NDVI (R² = 0.77) stands out. This confirms that the use of the LiDAR methodology with the vegetation indices allows a more practical estimation of the carbon stored in the plantation.