Abstract:RESUMOEste trabalho objetivou determinar o balanço radiativo na bacia hidrográfica do rio Tapacurá -PE, área com presença intensa de nebulosidade, por meio de produtos MODIS dos satélites Terra (MOD11A1 e MOD09GA) e Aqua (MYD11A1 e MYD09GA). Instalou-se uma estação meteorológica experimental no período de janeiro/2010 a agosto/2011, destinada ao monitoramento de dados meteorológicos complementares ao processamento do saldo radiativo, além do cômputo in loco do mesmo. O saldo de radiação instantâneo estimado co… Show more
“…Except for the model developed by Bastiaanssen (2018), these other models were specifically developed for the Caatinga. However, the model of Bastiaanssen (1998) has been widely used to estimate LAI in this region (e.g., Bezerra et al, 2014;Oliveira et al, 2015;Santos et al, 2017 For Eqs. 6 to 9, we used the same Landsat dataset produced for the models calibrations; for the MODIS MCD15A2H/A3H products, we used all images for the entire study period (total of 830 candidate images).…”
Leaf Area Index (LAI) models that consider all phenological stages have not been developed for the Caatinga, the largest seasonally dry tropical forest in South America. LAI models that are currently used show moderate to high covariance when compared to in situ data, but they often lack accuracy in the whole spectra of possible values and do not consider the impact that the stems and branches have over LAI estimates, which is of great influence in the Caatinga. In this study, we develop and assess PAI (Plant Area Index) and LAI models by using ground-based measurements and satellite (Landsat) data. The objective of this study was to create and test new empirical models using a multi-year and multi-source of reflectance data. The study was based on measurements of photosynthetic photon flux density (PPFD) from above and below the canopy during the periods of 2011–2012 and 2016–2018. Through iterative processing, we obtained more than a million candidate models for estimating PAI and LAI. To clean up the small discrepancies in the extremes of each interpolated series, we smoothed out the dataset by fitting a logarithmic equation with the PAI data and the inverse contribution of WAI (Wood Area Index) to PAI, that is the portion of PAI that is actually LAI (LAI_C). LAI_C can be calculated as follows: LAI_C=1-(WAI⁄PAI)). We subtracted the WAI values from the PAI to develop our in situ LAI dataset that was used for further analysis. Our in situ dataset was also used as a reference to compare our models with four other models used for the Caatinga, as well as the MODIS-derived LAI products (MCD15A3H/A2H). Our main findings were as follows: (i) Six models use NDVI (Normalized Difference Vegetation Index), SAVI (Soil-Adjusted Vegetation Index) and EVI (Enhanced Vegetation Index) as input, and performed well, with r2 ranging from 0.77 to 0.79 (PAI) and 0.76 to 0.81 (LAI), and RMSE with a minimum of 0.41 m2 m-2 (PAI) and 0.40 m2 m-2 (LAI). The SAVI models showed values 20% and 32% (PAI), and 21% and 15% (LAI), smaller than those found for the models that use EVI and NDVI, respectively; (ii) the other models (ten) use only two bands, and in contrast to the first six models, these new models may abstract other physical processes and components, such as leaves etiolation and increasing protochlorophyll. The developed models used the near-infrared band, and they varied only in relation to the inclusion of the red, green, and blue bands. (iii) All previously published models and MODIS-LAI underperformed against our calibrated models. Our study was able to provide several PAI and LAI models that realistically represent the phenology of the Caatinga.
“…Except for the model developed by Bastiaanssen (2018), these other models were specifically developed for the Caatinga. However, the model of Bastiaanssen (1998) has been widely used to estimate LAI in this region (e.g., Bezerra et al, 2014;Oliveira et al, 2015;Santos et al, 2017 For Eqs. 6 to 9, we used the same Landsat dataset produced for the models calibrations; for the MODIS MCD15A2H/A3H products, we used all images for the entire study period (total of 830 candidate images).…”
Leaf Area Index (LAI) models that consider all phenological stages have not been developed for the Caatinga, the largest seasonally dry tropical forest in South America. LAI models that are currently used show moderate to high covariance when compared to in situ data, but they often lack accuracy in the whole spectra of possible values and do not consider the impact that the stems and branches have over LAI estimates, which is of great influence in the Caatinga. In this study, we develop and assess PAI (Plant Area Index) and LAI models by using ground-based measurements and satellite (Landsat) data. The objective of this study was to create and test new empirical models using a multi-year and multi-source of reflectance data. The study was based on measurements of photosynthetic photon flux density (PPFD) from above and below the canopy during the periods of 2011–2012 and 2016–2018. Through iterative processing, we obtained more than a million candidate models for estimating PAI and LAI. To clean up the small discrepancies in the extremes of each interpolated series, we smoothed out the dataset by fitting a logarithmic equation with the PAI data and the inverse contribution of WAI (Wood Area Index) to PAI, that is the portion of PAI that is actually LAI (LAI_C). LAI_C can be calculated as follows: LAI_C=1-(WAI⁄PAI)). We subtracted the WAI values from the PAI to develop our in situ LAI dataset that was used for further analysis. Our in situ dataset was also used as a reference to compare our models with four other models used for the Caatinga, as well as the MODIS-derived LAI products (MCD15A3H/A2H). Our main findings were as follows: (i) Six models use NDVI (Normalized Difference Vegetation Index), SAVI (Soil-Adjusted Vegetation Index) and EVI (Enhanced Vegetation Index) as input, and performed well, with r2 ranging from 0.77 to 0.79 (PAI) and 0.76 to 0.81 (LAI), and RMSE with a minimum of 0.41 m2 m-2 (PAI) and 0.40 m2 m-2 (LAI). The SAVI models showed values 20% and 32% (PAI), and 21% and 15% (LAI), smaller than those found for the models that use EVI and NDVI, respectively; (ii) the other models (ten) use only two bands, and in contrast to the first six models, these new models may abstract other physical processes and components, such as leaves etiolation and increasing protochlorophyll. The developed models used the near-infrared band, and they varied only in relation to the inclusion of the red, green, and blue bands. (iii) All previously published models and MODIS-LAI underperformed against our calibrated models. Our study was able to provide several PAI and LAI models that realistically represent the phenology of the Caatinga.
“…Essa grande variação florestal e de ocupação no Cerrado, pode ser condicionante em fenômenos à superfície, já que as mudanças no uso e ocupação da terra em unidades de bacias hidrográficas podem provocar significativas alterações no balanço de energia (BE) e, por conseguinte, afetar a evapotranspiração, e antecedendo isso o Saldo de Radiação (Rn), que de acordo com Santos et al, (2014)resulta no balanço entre os fluxos radiativos descendentes (BOC) e ascendentes (BOL) que atuam na superfície; é responsável pelo controle da fotossíntese, evaporação, aquecimento do ar e do solo. Este balanço depende principalmente das condições atmosféricas, da radiação solar global, do albedo (poder de reflexão da superfície), temperatura e emissividade da superfície (Oliveira et al, 2015), apresentando variação temporal e espacial que impactam fortemente as trocas de calor e massa entre superfície e atmosfera.…”
O objetivo deste trabalho foi analisar por pontos amostrais o saldo de radiação instantâneo em diferentes usos da Terra na Área de Proteção Ambiental (APA) Rio Pandeiros no Norte de Minas Gerais em período seco e chuvoso (08/08/2016 e 27/10/2016). A escolha dessa área de estudo se deu pelo fato de ser uma APA, e, observa-se avanços significativos de ações antrópicasem seu território. Para auxiliar este trabalho, foram utilizadas técnicas de sensoriamento remoto e imagens do Landsat – 8 (OLI/TIRS). O saldo de radiação mostrou ter variação de acordo com cada uso da Terra estabelecido para análise, tendo maiores valores para corpos hídricos e em áreas de vegetação nativa. Destaca-se as áreas de Veredas com os maiores valores, tendo relação com suas características biológicas. A B S T R A C TThe objective this work was analyze by sample point the instantaneous net radiation in diferente land uses in the Environment Pretection Area (APA) River Pandeiros in the North Minas Gerais in period dry and rainy (08/08/2016 and 27/10/2016). The choice this study area by the fact of being a APA observe significant advances of anthropic actions in the distribuition territories. For help this work, was basidestechical of remote sensing and images of Landsat – 8 (OLI/TIRS). The net radiation showed varied accord in every land use establish for analyze, haved values high for body water and native vegetation. Pointed veredas areas in values high, haved relationship in yours biologicals characteristic.Keywords: Cerrado, APA River Pandeiros, Net radiationand Land uses.
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