Modelagem da umidade do solo utilizando imagem de satélite para análise da variação do solo/vegetação em Floresta – PE

• Autor(a) principal: Silva , Rafael Araújo da
• Data de Publicação: 2018
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da Universidade Federal de Alagoas (UFAL)
• Texto Completo: http://www.repositorio.ufal.br/handle/riufal/4769
• topic: Meteorologia operacional; Satélites meteorológicos; Sensoriamento remoto; Imagem de satélite; Solo – Umidade - Medição; Operational Meteorology; Meteorological satellites; Remote sensing; Satellite Image; Soil - Moisture – Measurement; CNPQ::CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS::METEOROLOGIA

Soil moisture is a factor of great relevance for vegetation analysis, since it has influence on the development and growth of the plants, being the field measurement the most accurate and used for its determination. However, remote sensing estimation has been gaining increasing credibility through the validation of satellite data through indices and field measurements. In this context, the present work had the objective of evaluating the changes promoted by the humidity in the vegetation of the semi - arid region due to precipitation in Forest - PE, through albedo and vegetation indices (NDVI) and humidity (NDWI), calculated using the SEBAL algorithm. The normalized water difference index (NDWI), used for validation and correlation with soil moisture, was measured in the field in three micrometeorological stations in the areas of caatinga, deforested and palms in the depths of 0 - 60 cm, obtaining reliable values mainly in the most superficial layers of the soil. Positive values of NDWI were found, which indicates the presence of water in the plants, which can be related to rainy periods in the site. The negative values, which were obtained in greater quantity in this work, indicate dry vegetation or without presence of water, representing the low precipitation in the analyzed period. For the NDVI, only positive values representing energy absorption through chlorophyll were obtained in all the images, since the negative values for this index are for the presence of water bodies. In relation to the albedo, values above 30% of energy were found, being reflected to natural surfaces with vegetation, and being higher in the dry periods above 45% presenting for this time exposed soils or dry vegetation, causing in seasonal changes in the vegetation in precipitation or absence thereof. In the statistical part, linear regression and correlation between NDWI and soil moisture were obtained, which were used to extrapolate data from a NDWI seismic data to obtain soil moisture. It was possible to validate the data of the satellite images by the SEBAL algorithm, however the extrapolation of the humidity data through NDWI was not possible because negative values were obtained for soil moisture, and the soil has a moisture plot little. In addition, the NDWI is a sensitive index to the presence of water in the vegetation and not in the soil, in which it behaves indifferently with or without the presence of water