Monitoramento ambiental da superfície da terra utilizando dados de satélite de órbita geoestacionária: estudo de caso com o meteosat second generation

• Autor(a) principal: Silveira Junior, Carlos Roberto da
• Data de Publicação: 2018
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/9687
• topic: Satélite geoestacionário; Meteosat-10; NDVI; NDWI; Gestationary sattelite; SANEAMENTO AMBIENTAL::QUALIDADE DO AR, DAS AGUAS E DO SOLO

Satellites of geostationary orbit, commonly used for meteorological monitoring, provide, in new series, the possibility of environmental monitoring of the vegetation, having the advantage of greater temporal resolution, when compared to polar orbiting satellite data. However, it is necessary to know the characteristics and limitations of the data in order to obtain the biophysical indicators. Therefore, the purpose of this work is to investigate and to know the potential of environmental indicators to monitor the surface of the earth from geostationary orbit satellite data, specifically Meteosat-10 of the MSG (Meteosat Second Generation) series, with a view to assess their temporal and spatial characteristics. In order to do so, we sought to identify the inherent challenges for obtaining biophysical indicators for Brazil, which has as main limitation the high viewing angle. As well as, analyzing the results of correction techniques (geometric and atmospheric) and band fusion to increase the correlation of NDVI (Normalized Difference Vegetation Index) with MODIS (Moderate Resolution Imaging Spectroradiometer). In order to identify the potential of the data, the NDVI and NDWI (Normalized Difference Water Index) indicators were used to monitor the environmental seasonality in the basin scale. The study database period was from 2013 to 2015. As a result the NDVI MSG, obtained in the interval from 10:00 to 12:00 am, presents a high correlation (p> 0.8) with the MOD09, being able to to obtain an image about the state of Goiás with 95% coverage of pixels in the interval of 12 days, while the MOD09 obtains in the interval of 16 days. However, the MSG cloud mask presents a high percentage of error (21%), showing cloud when the MOD09 pixels mark the entire area as cloud-free. The use of the panchromatic band in the band fusion operation did not add to the results. Likewise, the geometric correction is a fine adjustment that, in these analyzes, did not present an increase in the correlation of the data. On the other hand, the atmospheric correction maintains the correlation of the data and increases the value of the NDVI, approaching more to the value NDVI MODIS. In an analysis of major components and unsupervised classification the NDVI MSG was superior to NDVI MOD13, with substantial agreement for annual agriculture (K = 0.73) and considerable for pasture (K = 0.35) and natural vegetation (K = 0, 34). By analyzing the seasonality of river basins, one can identify and understand seasonal patterns in different regions and classes of use. The NDVI and NDWI presented a higher correlation with the precipitation of two months ago (r > 0.84) and high correlation with each other (r > 0.94), with NDWI being more sensitive to the abstraction of seasonal behavior, allowing identification tendencies in some basin of Goias state. The results demonstrate the potential of biophysical vegetation indicators from geostationary satellite Meteosat-10 to monitor the land cover.