Influence of El Niño / La Niña phenomena on the vegetation of the Atlantic Forest biome
Name: RITA DE CÁSSIA FREIRE CARVALHO
Publication date: 18/02/2020
Advisor:
Name |
Role |
|---|---|
| ALEXANDRE ROSA DOS SANTOS | Advisor * |
Examining board:
| Name |
Role |
|---|---|
| ALEXANDRE ROSA DOS SANTOS | Advisor * |
| HENRIQUE MACHADO DIAS | Internal Examiner * |
| TELMA MACHADO DE OLIVEIRA PELUZIO | External Examiner * |
Summary: The Atlantic Forest is known worldwide as one of the most important biomes in Brazil, rich in biodiversity and also one of the most endangered on the planet. Weather events such as El Niño and La Niña can affect the weather conditions in some regions of the planet, leading to abnormal temperature increases, droughts and heavy rainfall. In biomes such as the Atlantic Forest, climate change such as rising temperatures or decreasing rainfall can influence the increase or decrease of vegetation. Remote sensing, geoprocessing and geographic information systems techniques allow the assessment of vegetation conditions associated with climate variables such as rainfall and temperature in large areas such as the Atlantic Forest. In this context, the objective of this study is to evaluate the behavior of vegetation cover in the Mata Atlântica biome, state of Espírito Santo, during the occurrence of El Niño and La Niña climate events, through the use of vegetation indices and analysis of the use and land occupation. Land use and land cover maps were used to analyze the spatial and temporal dynamics of land cover changes. In addition, images of Normalized Difference Vegetation Index (NDVI) and Vegetation Enhancement Index (EVI) images were used for cluster analysis and correlation with land surface temperature and precipitation between 2002 2017. According to the results, the biennium that presented more vegetation increase was 2004-2005, years without occurrence of El Niño/La Niña. The biennium that presented the most vegetation decrease was 2016-2017, the years that presented the lowest and highest precipitation values of temperature and strong occurrence of climatic events.
Keywords: Remote Sensing, NDVI, Climate Factors, ENSO, Vegetation Indexes.
