Banca de DEFESA: MICKAELLE MARIA DE ALMEIDA PEREIRA
Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.STUDENT : MICKAELLE MARIA DE ALMEIDA PEREIRA
DATE: 26/02/2024
TIME: 09:00
LOCAL: https://meet.google.com/kpg-tkiy-sba
TITLE:
Application of functional data analysis to CH4, CO2 and N2O emissions from different land uses
KEY WORDS:
functional curves, derivatives, flow, GHGs, land use change.
PAGES: 83
BIG AREA: Ciências Agrárias
AREA: Agronomia
SUMMARY:
Inadequate management of agricultural systems, as well as changes in soil cover, are significant factors in increasing greenhouse gases (GHGs). There are statistical tools to measure the flow of GHGs, based on the temporal variation in concentration as a function of time. However, these analyzes may not cover characteristics arising from the variation and randomness present in the phenomenon. Therefore, functional data analysis (FDA) consolidates a new perspective for deriving models and optimizing techniques in exploratory data analysis, expressing notable potential in the study of variations in a given variable in relation to time, taking into account both continuous variation (linear or non-linear) and its randomness. The objective of the study is to evaluate the dynamics and complexity of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) emissions in four types of land use (extensive pasture, intensive pasture, sugarcane row and inter-row of sugarcane) using FDA techniques from univariate and multivariate perspectives. Initially, gas flow estimates were measured using the following models: linear, exponential and functional. It can be seen that the functional model uses the gas variation itself throughout the time interval, managing to have a good representation for the flow, both for variations in the linear and non-linear structure of the gases. Then, the data were analyzed using functional statistical methods. Discrete observations were restructured as functions using B-splines smoothing. Consequently, derivatives of the functions were applied to calculate the variation in concentrations as a function of time (flows), noting great variability in land use, alternating between effluxes and inflows. Considering the gas analysis together, the first three multivariate functional principal components (MFPCA) cumulatively captured more than 90% of the total variation present in the data. Cluster analysis, referring to the scores of the main components, separated the observations into four groups. Therefore, the FDA application demonstrates that it is capable of capturing the behavior of the studied phenomenon, encompassing the continuous nature of the system. Therefore, it accurately represents the process of gas exchange between soil and atmospheric air.
COMMITTEE MEMBERS:
Externa à Instituição - JANAÍNA BRAGA DO CARMO - UFSCAR
Externo ao Programa - 2578994 - JOSE ROMUALDO DE SOUSA LIMA - nullInterno - ***.221.388-** - LUIZ ANTONIO MARTINELLI - USP
Presidente - PAULO JOSE DUARTE NETO
Interno - TIAGO ALESSANDRO ESPINOLA FERREIRA