Use of aerial image in the estimation of volume and biomass of Eucalyptus sp. forest stand

Abstract

Assessing forest stands is crucial for managing and planning the use of these resources. Forest inventory is the instrument that provides information about the stand situation, which can be costly and time consuming. In order to facilitate and reduce the time spent obtaining these data, the main objective of this work was to evaluate the accuracy of volume and biomass estimates per unit area with data from remote sensing. Forty sample units were allocated and georeferenced, in which all trees with diameter at breast height (DBH) ≥ 5 cm were inventoried. Sequentially, the cubage was performed in order to obtain individual biomass, volume, and adjustment of the individual models. With data from georeferenced images of the study area, the vegetation indices MSAVI (Modified Soil-Adjusted Vegetation Index) and NDVI (Normalized Difference Vegetation Index) were obtained. The volume and biomass estimation using remote sensing variables were carried out through the adjustment of sigmoidal models by regression analysis, which used a combination of the average values of the vegetation indices and the basal area of the plot/hectares as an independent variable. The fit statistics and the accuracy of the tested models presented consistent results to estimate forest production. The results showwd that indices derived from remote sensing techniques associated with forest variables information could accurately estimate the volume and biomass of Eucalyptus spp. plantations.

Vegetation Monitoring and Post-Fire Recovery: A Case Study in the Centre Inland of Portugal

“…These indices use the most sensitive spectral bands that allow highlighting a particular target (e.g., land cover and/or its change and temporal trend). Nowadays, the most popular spectral indices in use are the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR), respectively, to monitor vegetation productivity [11][12][13][14][15][16] and to detect burned areas and their severity [2][3][4]9,[17][18][19]. These indices have also been incorporated in time series analysis to systematically detect burned areas and monitor long-term vegetation recovery [9,[20][21][22][23][24][25].…”

Modeling Biomass and Nutrients in a Eucalyptus Stand in the Cerrado

“…The model was developed by relating the variables of diameter and height based on the formula for the volume of a cylinder, which results in almost always accurate and non-biased estimates. In addition to volume, this model was used to estimate aboveground biomass and carbon stock [18][19][20].…”

APRENDIZADO DE MÁQUINA E REGRESSÃO LINEAR NA ESTIMATIVA DO VOLUME DE Eucalyptus NA AMAZÔNIA ORIENTAL

“…Inúmeros artigos têm comparado o modelo de Schumacher e Hall com outros modelos e técnicas para o ajuste de equações para o Eucalyptus sp. (REGO et al, 2019;ALMEIDA et al, 2020;MATTOS et al, 2020;MENDES et al, 2020) Um fator determinante no ajuste de um modelo é sua aplicabilidade, ou seja, a utilização deste em práticas cotidianas, sem que seja necessário grande desprendimento de tempo e técnicas avançadas, neste ponto em específico, o modelo de Schumacher e Hall é superior aos demais, pois, os parâmetros ajustados podem ser aplicados sem grandes empecilhos em campo, denotando que este modelo é simples e possui acurácia e precisão nas estimativas (Tabela 2).…”