Fechar
Metadados

@MastersThesis{Bandoria:2021:InDaMu,
               author = "Bandoria, Marcelo Cardoso da Silva",
                title = "Din{\^a}micas de regenera{\c{c}}{\~a}o florestal na Mata 
                         Atl{\^a}ntica: integra{\c{c}}{\~a}o de dados multi-sensores e 
                         medidas de campo",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2021",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2020-04-30",
             keywords = "sentinel-2 MSI, Landsat TM, ETM+ e OLI, sensoriamento remoto 
                         multiespectral, DAP, IAF, serrapilheira, regenera{\c{c}}{\~a}o 
                         da Mata Atl{\^a}ntica, multispectral remote sensing, DBH, LAI, 
                         litter, regeneration of the Atlantic Forest.",
             abstract = "Desmatamento e degrada{\c{c}}{\~a}o florestal s{\~a}o processos 
                         que impactam diretamente os estoques de carbono, biodiversidade, 
                         reservas h{\'{\i}}dricas e o clima, promovendo ampla perda de 
                         servi{\c{c}}os ecossist{\^e}micos. Na conven{\c{c}}{\~a}o de 
                         Paris, o Brasil assumiu ratificado atrav{\'e}s da 
                         Contribui{\c{c}}{\~a}o Nacionalmente Determinada (NDC), de 
                         restaurar e reflorestar 12 milh{\~o}es de hectares de florestas 
                         at{\'e} 2030. Grande parte dessas a{\c{c}}{\~o}es devem se dar 
                         no bioma Mata Atl{\^a}ntica e metodologias baseadas em imagens 
                         satelitais contribuir{\~a}o para o monitoramento e 
                         verifica{\c{c}}{\~a}o do acordo. Apesar dos grandes 
                         avan{\c{c}}os t{\'e}cnicos sobre metodologias de mapeamento de 
                         desmatamento, a detec{\c{c}}{\~a}o dos diferentes graus de 
                         regenera{\c{c}}{\~a}o florestal, s{\~a}o ainda incipientes. 
                         Nesse sentido, o presente trabalho teve por objetivos identificar, 
                         por meio de invent{\'a}rios de campo (resolu{\c{c}}{\~a}o 
                         CONAMA no 1 de 1994) e sensoriamento remoto orbital as diferentes 
                         idades de fragmentos de Mata Atl{\^a}ntica na Esta{\c{c}}{\~a}o 
                         Experimental Solo Planta Atmosfera de S{\~a}o Francisco Xavier 
                         (EESPA-SFX), localizada no munic{\'{\i}}pio de S{\~a}o 
                         Jos{\'e} dos Campos, SP, administrada pelo Laborat{\'o}rio de 
                         Ecohidrologia (LabEcoh/CCST-INPE). Atrav{\'e}s de produtos de 
                         sistemas sensores multiespectrais (Landsat TM; ETM +; OLI) 
                         analisou-se mudan{\c{c}}as temporais (1984-2019) e investigou-se 
                         processos em escala m{\'e}dia-pequena (Sentinel-2 A e B MSI) 
                         (2019) sobre parcelas em regenera{\c{c}}{\~a}o da 
                         vegeta{\c{c}}{\~a}o da Mata Atl{\^a}ntica. A metodologia 
                         baseou-se em {\'{\I}}ndices de Vegeta{\c{c}}{\~a}o simples e 
                         ajustados (NDVI, EVI e SAVI) e fra{\c{c}}{\~o}es espectrais 
                         (vegeta{\c{c}}{\~a}o, solo e sombra) obtidas pelo Modelo Linear 
                         de Mistura Espectral. Foram associadas medidas de SR e dados de 
                         campo, de crescimento de tronco, {\'{\I}}ndice de {\'A}rea 
                         foliar e produ{\c{c}}{\~a}o de serrapilheira, obtidos em 2019 na 
                         {\'a}rea (EESPA-SFX). Os resultados apontam que as metodologias 
                         combinadas de SR e levantamento in situ permitiram identificar as 
                         idades aproximadas de tr{\^e}s {\'a}reas em diferentes 
                         est{\'a}gios de regenera{\c{c}}{\~a}o, a saber, Ri 
                         (regenera{\c{c}}{\~a}o inicial) com cerca de 7 anos, Rm 
                         (regenera{\c{c}}{\~a}o intermedi{\'a}ria) com cerca de 20 anos 
                         e, Ra (regenera{\c{c}}{\~a}o avan{\c{c}}ada), com > 40 anos. A 
                         an{\'a}lise interanual, EVI e SAVI do Landsat mostraram 
                         diferen{\c{c}}as significativas (p < 0,05) entre essas 
                         {\'a}reas. Atrav{\'e}s da reamostragem simples e 
                         itera{\c{c}}{\~a}o de 10000 vezes, o discernimento 
                         alcan{\c{c}}ou 95% de credibilidade. Esse resultado sugere que os 
                         dados Landsat foram sens{\'{\i}}veis na detec{\c{c}}{\~a}o de 
                         processos de regenera{\c{c}}{\~a}o florestal em paisagens 
                         heterog{\^e}neas, na escala do presente trabalho. Foram 
                         selecionadas um conjunto de imagens Sentinel-2 MSI sobre o ano de 
                         2019 e extra{\'{\i}}dos os IVs, ajustada uma biblioteca 
                         espectral para as {\'a}reas estudadas e extra{\'{\i}}das as 
                         fra{\c{c}}{\~o}es espectrais de cada parcela, que foram 
                         comparados aos resultados das medidas de campo. Na an{\'a}lise 
                         intra-anual, o NDVI do Sentinel-2 se mostrou mais 
                         sens{\'{\i}}vel para detec{\c{c}}{\~a}o dos diferentes 
                         est{\'a}gios (p < 0,05). A vari{\'a}vel incremento acumulado 
                         explicou o EVI em 17% para Rm e o NDVI em 34% para Ra. A 
                         vari{\'a}vel IAF explicou o EVI em 21% para Rm, o NDVI em 20% 
                         para Rm e o SAVI em 18% para Rm. Em rela{\c{c}}{\~a}o {\`a}s 
                         fra{\c{c}}{\~o}es espectrais a parcela P apresentou 
                         separabilidade em todas as fra{\c{c}}{\~o}es. Destacamos que a 
                         fra{\c{c}}{\~a}o solo apenas n{\~a}o separou as parcelas Ri e 
                         Ra. Em termos de caracter{\'{\i}}sticas e evolu{\c{c}}{\~a}o 
                         dos processos nos 3 est{\'a}gios sucessionais as medidas de 
                         tronco apontam que a taxa de crescimento da 
                         regenera{\c{c}}{\~a}o inicial {\'e} maior em 
                         rela{\c{c}}{\~a}o {\`a}s outras parcelas. A Biomassa Acima do 
                         Solo (BAS) calculada foi maior na Ra em rela{\c{c}}{\~a}o aos 
                         outros est{\'a}gios, e apresentou diferen{\c{c}}a entre Rm e Ra. 
                         Ainda sob reamostragem simples, as vari{\'a}veis {\'{\I}}ndice 
                         de {\'A}rea Foliar (IAF) e serrapilheira diferenciam as parcelas 
                         Ri e Ra, sob 95% de credibilidade. Verificou-se sincronicidade 
                         entre as vari{\'a}veis de incremento acumulado e IAF sobre a 
                         parcela Ri, o que sugere sincronismo entre crescimento de tronco e 
                         folhas sobre a {\'a}rea. O cruzamento com dados de campo apontou 
                         que na parcela Ri, a BAS e incremento acumulado, explicam 
                         respectivamente 22% da varia{\c{c}}{\~a}o da fra{\c{c}}{\~a}o 
                         sombra, o IAF e a serrapilheira, explicam respectivamente 22% e 
                         17% a fra{\c{c}}{\~a}o solo (valor-p < 0,05). J{\'a} na parcela 
                         Rm a BAS e IAF, explicaram respectivamente 18% e 23% da 
                         varia{\c{c}}{\~a}o das fra{\c{c}}{\~o}es solo e sombra 
                         (valor-p < 0,05), o incremento acumulado e serrapilheira n{\~a}o 
                         apresentaram valores significativos para nenhuma 
                         fra{\c{c}}{\~a}o espectral. Na parcela Ra o incremento acumulado 
                         e IAF, explicam respectivamente 76% e 13% as fra{\c{c}}{\~o}es 
                         solo e vegeta{\c{c}}{\~a}o (valor-p < 0,05), IVs e 
                         fra{\c{c}}{\~o}es sob intervalo de credibilidade de 95%. Em 
                         linhas gerais, esse estudo mostrou que, apesar das 
                         limita{\c{c}}{\~o}es, foi poss{\'{\i}}vel driblar o desafio de 
                         associar medidas por SR e medidas in situ em fragmentos de 
                         florestas em diferentes est{\'a}gios de regenera{\c{c}}{\~a}o e 
                         usar SR orbital, por meio de IVs tanto do Landsat quanto do 
                         Sentinel-2, quando tratamentos apropriados s{\~a}o aplicados. 
                         Conclui-se que os dados derivados do sat{\'e}lite Sentinel-2 
                         apresentam o potencial para serem utilizados para 
                         verifica{\c{c}}{\~a}o do crescimento de florestas 
                         secund{\'a}rias, e podem ser utilizados para 
                         caracteriza{\c{c}}{\~a}o das diferentes idades e estruturas 
                         destas florestas. ABSTRACT: Deforestation and forest degradation 
                         are processes that directly impact carbon stocks, biodiversity, 
                         water reserves and the climate, promoting a wide loss of ecosystem 
                         services. At the Paris Convention, Brazil was ratified through the 
                         Nationally Determined Contribution (NDC), to restore and reforest 
                         12 million hectares of forests by 2030. Most of these actions 
                         should take place in the Atlantic Forest biome and methodologies 
                         based on satellite images will contribute to monitoring and 
                         verification of the agreement. Despite major technical advances in 
                         deforestation mapping methodologies, the detection of different 
                         degrees of forest regeneration is still incipient. In this sense, 
                         the objective of the present work was to identify, by means of 
                         field inventories (CONAMA resolution 1 of 1994) and remote orbital 
                         sensing, the different ages of fragments of the Atlantic Forest in 
                         the Experimental Soil Atmosphere Station of S{\~a}o Francisco 
                         Xavier (EESPA- SFX), located in the city of S{\~a}o Jos{\'e} dos 
                         Campos, SP, managed by the Ecohydrology Laboratory (LabEcoh / 
                         CCST-INPE). Through multispectral sensor system products (Landsat 
                         TM; ETM +; OLI), temporal changes (1984-2019) were analyzed and 
                         processes were investigated on a small-medium scale (Sentinel-2 A 
                         and B MSI) (2019) on regenerating parcels in Atlantic Forest 
                         vegetation. The methodology was based on simple and adjusted 
                         Vegetation Indices (NDVI, EVI and SAVI) and spectral fractions 
                         (vegetation, soil and shade) obtained by the Linear Spectral 
                         Mixture Model. Remote sensing measurements and field data, stem 
                         growth, leaf area index and litter production, obtained in 2019 in 
                         the (EESPA-SFX) were associated. The results show that the 
                         combined methodologies of SR and in situ survey allowed to 
                         identify the approximate ages of three areas in different stages 
                         of regeneration, namely, Ri (initial regeneration) with about 7 
                         years, Rm (intermediate regeneration) with about 20 years and, Ra 
                         (advanced regeneration), > 40 years. Landsat's interannual 
                         analysis, EVI and SAVI showed significant differences (pvalue 
                         <0.05) between these areas. Through simple resampling in 10000 
                         interactions, the confidence reached 95% credibility. This result 
                         suggests that the Landsat data were sensitive in the detection of 
                         forest regeneration processes in heterogeneous landscapes, on the 
                         scale of the present work. A set of Sentinel-2 MSI images for the 
                         year 2019 were selected, obtained by Google Earth Engine (GEE) and 
                         the IVs were extracted, a spectral library was adjusted for the 
                         studied areas and the spectral fractions of each plot were 
                         extracted, which were compared results of field measurements. In 
                         the intra-annual analysis, the Sentinel-2 NDVI was more sensitive 
                         for detecting the different stages (pvalue <0.05). The accumulated 
                         increment variable explained EVI in 17% for Rm and NDVI in 34% for 
                         Ra. The LAI variable explained EVI in 21% for Rm, NDVI in 20% for 
                         Rm and SAVI in 18% for Rm. In relation to spectral fractions, the 
                         P portion presented description in all fractions. We emphasize 
                         that the soil fraction did not separate the Ri and Ra plots. In 
                         terms of characteristics and evolution of the processes in the 3 
                         successional stages, the accumulated wood growth measures indicate 
                         that the growth rate of the initial regeneration is higher in 
                         relation to the other plots. The Above Ground Biomass (AGB) 
                         calculated was higher in Ra compared to the other stages, and 
                         showed a difference between Rm and Ra. Still under simple 
                         resampling, the Leaf Area Index (LAI) and litter variables 
                         differentiate the Ri and Ra plots, under 95% credibility. There 
                         was synchronicity between the accumulated increment and LAI 
                         variables on the Ri plot, which suggests synchrony between trunk 
                         and leaf growth over the area. The crossing with field data showed 
                         that in the Ri plot, the AGB and accumulated increment, 
                         respectively explain 22% of the variation of the shadow fraction, 
                         the LAI and the litter, respectively explain 22% and 17% of the 
                         soil fraction (p-value <0.05). In the Rm plot, AGB and LAI 
                         explained 18% and 23%, respectively, of the variation of soil and 
                         shade fractions (p-value <0.05), the accumulated wood growth and 
                         litter did not show significant values for any spectral fraction. 
                         In the Ra plot, the accumulated wood growth and LAI, respectively, 
                         account for 76% and 13% of the soil and vegetation fractions 
                         (p-value <0.05), IVs and fractions under a 95% credibility 
                         interval. In general, this study showed that, despite the 
                         limitations, it was possible to circumvent the challenge of 
                         associating measures by SR and measures in situ in forest 
                         fragments in different stages of regeneration and using orbital 
                         SR, through IVs - both from Landsat and of Sentinel-2, when 
                         appropriate treatments are applied. It is concluded that the data 
                         derived from the Sentinel-2 satellite have the potential to be 
                         used to verify the growth of secondary forests, and can be used to 
                         characterize the different ages and structures of these forests.",
            committee = "Galv{\~a}o, L{\^e}nio Soares (presidente) and Borma, Laura de 
                         Simone (orientadora) and Anderson, Liana Oighenstein (orientadora) 
                         and Monteiro Junior, Mauro Brum",
         englishtitle = "Dynamics of forest regeneration in the Atlantic Forest: 
                         integration of multi-sensor data and field measurements",
             language = "pt",
                pages = "179",
                  ibi = "8JMKD3MGP3W34R/42EKG7L",
                  url = "http://urlib.net/rep/8JMKD3MGP3W34R/42EKG7L",
           targetfile = "publicacao_FA provisoria.pdf",
        urlaccessdate = "12 abr. 2021"
}


Fechar