A dinâmica da vegetação e a sensibilidade à chuva em três regiões do norte do Pantanal Mato-Grossense
The wet areas of the Pantanal provide important services such as water and carbon storage, improved water quality, and climate regulation. Analysis and monitoring of vegetated land and precipitation on a regional scale using remote sensing data can provide important inform...
| Autores: | , , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | Brasil |
| Recursos: | Associação Brasileira de Engenharia Sanitária e Ambiental (ABES) |
| Repositorio: | Revista Brasileira de Ciências Ambientais (Online) |
| Idioma: | inglés |
| OAI Identifier: | oai:ojs.www.rbciamb.com.br:article/1132 |
| Acesso em linha: | https://www.rbciamb.com.br/Publicacoes_RBCIAMB/article/view/1132 |
| Access Level: | acceso abierto |
| Palavra-chave: | NDVI; wavelet; correlação cruzada; sazonalidade. NDVI; wavelet; cross-correlation; seasonality. |
| Resumo: | The wet areas of the Pantanal provide important services such as water and carbon storage, improved water quality, and climate regulation. Analysis and monitoring of vegetated land and precipitation on a regional scale using remote sensing data can provide important information for the preservation of the landscape and biodiversity of the region. Thus, the purpose was to analyze characteristics of the green cycle of the vegetated surface and to what extent the vegetated surface responds to the variability of precipitation in the Pantanal. The areas include the regions of Cáceres (CAC), Poconé (POC), and Barão de Melgaço (BAM) in Mato Grosso. Time series of accumulated precipitation (PPT) and NDVI (Normalized Difference Vegetation Index) were used for the period from 2000 to 2016, obtained on NASA’s Giovanni platform (National Aeronautics and Space Administration). The analysis of the wavelet transform was applied for NDVI data and there was cross-correlation analysis for PPT and NDVI data. The results showed that the highest correlation between PPT and NDVI was positive with a 1-month lag, but was significant with a lag of up to 3 months. The wavelet analyses showed that the largest wavelet powers occurred at the frequency between 0.5 and 1.3 years, i.e., the NDVI series presented the main variances on the approximately annual scale, indicating that these characteristics are important aspects of local phenology variability, such as cumulative green throughout the year and generalized senescence. |
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