Quantificação de carbono em áreas de florestas nativas com uso de sensoriamento remoto

Abstract

This dissertation comprises two interdependent chapters. In the first chapter, I carried out a systematic literature review, focusing on articles on forest restoration, ecological restoration, carbon and remote sensing up to November 2022. The systematic review was conducted using the Web of Science database. Exclusion and inclusion criteria were applied, resulting in 38 studies that were analyzed based on information such as place of publication, location of the study, type of vegetation, type of restoration, type of satellites and modeling used in the scientific articles. In the second chapter, an area undergoing restoration using the direct sowing method was monitored from 2018 to 2022, and each year the vegetation indices (NDVI, SAVI, EVI, PRI and CO2Flux) were analyzed to understand the behavior and growth of the restored vegetation in each year. At the same time, forest inventory data collected by the SemeAR/UFSCar Research Group was used. Using this data, it was possible to calculate the total biomass (t.dm/ha) and the carbon stock in the trees and in the stratum (tCO2e), establishing relationships with the vegetation indices by means of a multiple linear regression analysis using the Stepwise technique in RStudio. The main results of this work include: (i) mapping research into forest restoration, ecological restoration, carbon and remote sensing; (ii) calculating the carbon stock and biomass for the study area, restored using the direct seeding technique; and (iii) comparing the forest inventory data with the information generated by the vegetation indices, highlighting the relationship between these indices and the information on the carbon stock.