Controles abióticos de uma savana amazônica : uma abordagem de sensoriamento remoto multisensor

• Ano de defesa: 2022
• Autor(a) principal: Naissinger, Bruna Mendel
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Roraima; Brasil; PRPPG - Pró-reitoria de Pesquisa e Pós-Graduação; PRONAT - Programa de Pós-Graduação em Recursos Naturais; UFRR
• Palavras-chave em Português: Bacia sedimentar do Tacutu; Radar de abertura sintética; Modelo Linear de Mistura Espectral; Modelagem de Equações Estruturais; MLME; SEM; Tacutu sedimentary; Basin; Structural Equation Modeling; Linear Spectral Mixing; LSU; Synthetic Aperture Radar; SAR; CNPQ::CIENCIAS BIOLOGICAS
• Link de acesso: http://repositorio.ufrr.br:8080/jspui/handle/prefix/852

Savannas support great biodiversity and high levels of species endemism, occurring worldwide, including in the midst of the dense Amazon rainforest, where they play an important role as recharge areas for the Amazon watershed, which, given its continental dimensions, plays a central role in the hydrological cycle. Despite their importance, the ecological health of these ecosystems is threatened by the expansion of agribusiness and the advance of global warming. The parameters that control the large-scale distribution of savannas in the Amazon are still poorly understood. This paper presents the verification and quantification of direct and indirect controls of abiotic variables on the photosynthetic activity of the vegetation, represented by the Normalized Difference Vegetation Index (NDVI) in a time series of 5 years, in a clipping that includes the Tacutu Sedimentary Basin in Brazil, whose origin and deposition is associated with the evolution of the Guiana Savannas. The abiotic variables used were lithologies (rocks), landforms, altitude, slope, climate (precipitation and temperature), inundation frequency, and soil parameters: Cation Exchange Capacity (CEC), Soil Organic Carbon Stock (SOCS), bulk density, and sand percentage. A confirmatory Structural Equation Modeling (SEM) analysis was applied to investigate hypothesized causal relationships in a path diagram. Nine Sentinel-2 multispectral images from 2017 to 2021, ALOS PALSAR radar images and NASADEM digital elevation model were used to construct the Flood Frequency and relief shape of the river plains by means of Linear Spectral Unmixing (LSU) and fusion of optical and Synthetic Aperture Radar (SAR) images in open source software. The results showed that NDVI varied 60% between dry and wet periods. The current configuration of the landscape, expressed predominantly by the Sedimentary Formation Boa Vista and the products of its reworking, arranged in long planing surfaces, resulting from successive cycles of erosion and deposition, punctuated by residual reliefs (inselbergs) indirectly affect the NDVI, that is, rocks and relief forms affect the soils, which affect the NDVI. The variables with direct effect explained 48% of the variation in NDVI, with bulk density having the largest effect due to the presence of cohesive horizons that hinder root establishment and water drainage in soils. The fertility indicators (CEC and SOCS) had a negative effect because the soils are acidic and with high exchangeable aluminum content. The effect of precipitation is positive, and the effect of flood frequency is negative, and these hydroedaphic constraints are also evidenced by the positive effect of sand concentration in the soils. This approach demonstrated the relevance of landscape evolution, soil, and climate on the spatial and temporal distribution of vegetation cover.