Isprs Journal of Photogrammetry and Remote Sensing | 2019

Wavelet approach applied to EVI/MODIS time series and meteorological data

 
 
 

Abstract


Abstract The aim of this study was to describe the phenology of different types of grasslands from the Pampa and Mata Atlântica biomes in the southern region of Brazil and its relation with meteorological variables, in a time series of EVI/MODIS data using the Wavelet approach (Transform – WT - and Coherence - WC). There is a lack of studies focusing on how climate variability influences the phenology of different Brazilian Pampa grassland typologies. This information is essential to describe the spatio-temporal dynamics of grasslands and contribute to actions of sustainable management and conservation strategies, threatened by crops, forestry, and expansion of overgrazed cattle farms. A series of EVI/MODIS acquired from February 2000 to December 2014, totaling 342 images, were sampled for each of the 10 grassland typologies at the study area. Mean EVI data and the WT indicated when and where changes in the grassland phenological dynamics occurred. The WC, applied to the EVI/MODIS time series with (i) rainfall and (ii) air temperature, helped to identify the correlation between the data. Two well - defined cycles were identified: annual, ranging from 1 to 23 observations, and interannual, from 92 to 184 observations. The different grassland typologies showed similar phenological patterns, although some spatial dependency was observed and related to the different soil and terrain morphometry at the study area. The influence of those abiotic factors on the grassland vegetation, phenological events and their expression on the EVI was also spatially dependent and strongly linked to weather conditions (e.g., the permanence of humidity after rainfall in shallow soils) and climate. The correlation between EVI and air temperature was stronger in the annual cycle for all grassland typologies. For the interannual cycles, El Nino and La Nina events caused higher correlation between EVI data and rainfall.

Volume 147
Pages 335-344
DOI 10.1016/J.ISPRSJPRS.2018.11.024
Language English
Journal Isprs Journal of Photogrammetry and Remote Sensing

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