Submitted by Jadson Francisco de Jesus SILVA (jadson@uefs.br) on 2018-03-02T22:16:44Z No. of bitstreams: 1 clovesvilasboas_disserta??o_mestrado_2017.pdf: 2913418 bytes, checksum: bb279ced1f535288e5f541d897d80a7d (MD5) / Made available in DSpace on 2018-03-02T22:16:44Z (GMT). No. of bitstreams: 1 clovesvilasboas_disserta??o_mestrado_2017.pdf: 2913418 bytes, checksum: bb279ced1f535288e5f541d897d80a7d (MD5) Previous issue date: 2017-02-17 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / There is a great need for the development of more efficient systems for monitoring the dynamics of atmospheric carbon so that there is a better understanding of the interactions between the biosphere and the atmosphere. However, it is critical that these technologies have high coverage and low cost. In the vegetation, the process of biomass generation through photosynthesis is a determining factor in the way a vegetated area will appear radiometrically in the satellite images, therefore, the remote sensing becomes an alternative to the monitoring of this dynamics, having a High coverage and have a low cost. The objective of this work is to analyze the dynamics of CO2 fluxes in the Caatinga Biome by means of multispectral remote sensing, verifying the potential of multispectral images in the detection of CO2 fluxes in areas of preserved Caatinga and in a regenerated state. The study was carried out in areas of Caatinga in the municipality of Petrolina-PE and Araripina-PE, areas that are monitored by micrometeorological stations. The methodology adopted was based on the modeling of the Carbon Forest Sequestration Index (CO2flux) that measures the efficiency of the carbon sequestration process by vegetation, and proposes the integration of the Normalized Difference Vegetation Index (NDVI) with the Index of Photochemical Reflectance (PRI). For the database, 22 OLI (Landsat-8) multispectral scenes were used together with field-measured meteorological data to verify the relationship between the variables analyzed. The results showed that the vegetation of the Caatinga has seasonal variations in CO2 flows in regions with different vegetation types. The CO2flux index can be applied to determine the CO2 fluxes, presenting better adjustments when the CO2 data are compared using the 1 pixel reading in the image, showing to be more efficient in relation to the analysis with the footprint in. However, based on spectral models of vegetation, it was possible to determine the dynamics of CO2 flows in areas of preserved Caatinga and in regeneration state using data extracted from multispectral sensors. / H? uma grande necessidade no desenvolvimento de sistemas mais eficazes para o monitoramento da din?mica do carbono atmosf?rico, para que haja uma melhor compreens?o das intera??es entre a biosfera e a atmosfera. No entanto, ? fundamental que essas tecnologias possuam alta cobertura e um baixo custo. Na vegeta??o, o processo de gera??o de biomassa por meio da fotoss?ntese ? um fator determinante na forma como uma ?rea vegetada ir? aparecer radiometricamente nas imagens de sat?lite, portanto, o sensoriamento remoto vem a ser uma alternativa para o monitoramento dessa din?mica, por ter uma alta cobertura e possuir um baixo custo. O objetivo deste trabalho ? analisar, por meio de sensoriamento remoto multiespectral, a din?mica dos fluxos de CO2 no Bioma Caatinga, verificando o potencial das imagens multiespectrais na detec??o dos fluxos de CO2 em ?reas de Caatinga preservada e em estado de regenera??o. O estudo foi desenvolvido em ?reas de Caatinga no munic?pio de Petrolina-PE e Araripina-PE, ?reas monitoradas por esta??es micrometeorol?gicas. A metodologia adotada foi a partir da modelagem do ?ndice de Sequestro Florestal de Carbono (CO2flux) que mede a efici?ncia do processo de sequestro de carbono pela vegeta??o, e que prop?e a integra??o do ?ndice de Vegeta??o por Diferen?a Normalizada (NDVI) com o ?ndice de Reflect?ncia Fotoqu?mica (PRI). Foram utilizadas, para a base de dados, 22 cenas multiespectrais do sensor OLI (Landsat-8) juntamente com dados meteorol?gicos medidos em campo, a fim de verificar a rela??o entre as vari?veis analisadas. Os resultados mostraram que a vegeta??o da Caatinga tem varia??es sazonais nos fluxos de CO2 nas regi?es com diferentes tipos de vegeta??o. O ?ndice CO2flux pode ser aplicado para a determina??o os fluxos de CO2, apresentando melhores ajustes quando os dados de CO2 s?o comparados utilizando a leitura de 1 pixel na imagem, mostrando ser mais eficiente em rela??o a analise com as ?reas de influ?ncia (footprint) em rela??o aos pontos amostrais, no entanto, os dados de footprint apresentaram tamb?m correla??es significativas. Portanto, baseado nos modelos espectrais de vegeta??o foi poss?vel determinar a din?mica dos fluxos de CO2 em ?reas de Caatinga preservada e em estado de regenera??o utilizando dados extra?dos de sensores multiespectrais.

<p>Thermal and multispectral imagery can provide users with insights into the water stress status and evapotranspiration demand of crops. However, traditional platforms, such as satellites, for these thermal and multispectral sensors are limited in their usefulness due to low spatial and temporal resolution. Small unmanned aircraft system (UAS) have the potential to have similar sensors installed and provide canopy temperature and reflectance information at spatial and temporal resolutions more useful for crop management; however, most of the existing research on the calibration or the estimation of water status were established based on the satellite platforms either for the sensors calibration or water status quantification. There is, therefore, a need to develop methods specifically for UAS-mounted sensors. In this research, a pixel-based calibration and an atmospheric correction method based on in-field approximate blackbody sources were developed for an uncooled thermal camera, and the higher accurate vegetative temperature acquired after calibration was used as inputs to an algorithm developed for high-resolution thermal imagery for calculating crop latent heat flux. At last, a thermal index based on the Bowen ratio is proposed to quantify the water deficit stress in a crop field, along with this, a method for plot-level analysis of various vegetation and thermal indices have been demonstrated to illustrate its broad application to genetic selection. The objective was to develop a workflow to use high-resolution thermal and multispectral imagery to derive indices that can quantify crops water status on a plot level which will facilitate the research related to breeding selection.</p> <p>The camera calibration method can effectively reduce the root mean square error (RMSE) and variability of measurements. The pixel-based thermal calibration method presented here was able to reduce the measurement uncertainty across all the pixels in the images, thus improving the accuracy and reducing the between-pixel variability of the measurements. During field calibration, the RMSE values relative to ground reference targets for two flights in 2017 were reduced from 6.36°C to 1.24°C and from 4.56°C to 1.32°C, respectively. The latent heat flux estimation algorithm yields an RMSE of 65.23 W/m² compared with the ground reference data acquired from porometer. The Bowen ratio has a high correlation with drought conditions quantified using the soil moisture index, stomatal conductance, and crop water stress index (CWSI), which indicates the potential of this index to be used as a water deficit stress indicator. The thermal and multispectral indices on a plot level displayed will facilitate the breeding selection.</p>

No description available.