INFLUENCE OF TEMPERATURE AND PRECIPITATION ON THE ANNUAL VARIATION OF VEGETATION INDEX IN THE SEMIDECIDUOUS SEASONAL FOREST AREA, IN THE SOUTHWEST OF PARANÁ, BRAZIL
Vegetation indices (VIs) are designed to enhance the vegetation signal and minimize variations in solar irradiance and the effects of the plant canopy substrate. The time series of vegetation cover images present different frequency components, such as seasonal variations and long and short-term flu...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | Brasil |
| Institución: | Universidade Federal de Roraima (UFRR) |
| Repositorio: | Revista geográfica acadêmica |
| Idioma: | portugués |
| OAI Identifier: | oai:oai.revista.ufrr.br:article/8099 |
| Acceso en línea: | https://revista.ufrr.br/rga/article/view/8099 |
| Access Level: | acceso abierto |
| Palabra clave: | NDVI - normalized difference vegetation index RENDVI - red edge normalized difference vegetation index EVI - enhanced vegetation index Sensoriamento remoto Satélite RapidEye Geografia Física Sistemas de Informações Geográficas |
| Sumario: | Vegetation indices (VIs) are designed to enhance the vegetation signal and minimize variations in solar irradiance and the effects of the plant canopy substrate. The time series of vegetation cover images present different frequency components, such as seasonal variations and long and short-term fluctuations, influenced mainly by climatic factors such as temperature and precipitation. Thus, the work aims to evaluate the influence of temperature and precipitation on the annual variation of NDVI (normalized difference vegetation index), RENDVI (red edge normalized difference vegetation index) and EVI (enhanced vegetation index), in an area of semideciduous seasonal forest, which covers part of the municipalities of Marmeleiro and Renascença, in the southwest of the State of Paraná. Seven images from the RapidEye satellite (level 3A) available for the year 2018 without cloud cover were used. Seasonal variation demonstrated that the highest values of vegetation IVs were found in summer, since temperature and precipitation contribute to raising them in the study area, with the response to temperature being faster than to precipitation. The EVI showed a better correlation with the minimum average temperature and the average temperature, because it is more influenced by the leaf area index (LAI), which is controlled by the seasons. On the other hand, NDVI and RENDVI are more influenced by precipitation and showed a greater correlation with accumulated precipitation between 30 and 60 days prior to imaging. |
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