AUTHOR=Sonia  , Sunita  , Ghosh Tathagata , Amari Abdelfattah , Yadav Virendra Kumar , Osman Haitham , Sahoo Dipak Kumar , Patel Ashish 

TITLE=Appraisal of long-term responsiveness of normalized difference vegetation index to climatic factors using multiscale time–frequency decomposition in an arid environment

JOURNAL=Frontiers in Earth Science

VOLUME=Volume 11 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2023.1265292

DOI=10.3389/feart.2023.1265292

ISSN=2296-6463

ABSTRACT=An arid climate is one of the unique conditions that have a significant impact on the growth of crops and natural vegetation. The Normalized Difference Vegetation Index (NDVI) is a crucial remotely sensed measurement of greenishness due to its strong correlation with crop and vegetation growth and productivity. In the present study, the spatiotemporal dynamics of NDVI were analyzed over a time period of 2000 to 2021 in the segment of the arid western plain zone of Rajasthan, India. NDVI time series data as well as data related to climatic factors, viz. precipitation, soil moisture, evapotranspiration, and 2m air temperature were collected from the Giovanni, Goddard Earth Science. Mann-Kendall trend test and Sen's slope helped in depicting long-term continuous time-frequency trend while Karl Pearson correlation analysis depicted the significant relationship between all the factors except 2m air temperature. Seasonal and mean monthly results of all the factors showed considerable coherence with NDVI except 2m air temperature. The multiscale time-frequency decomposition or wavelet analysis depicted 5 th month to the 7 th month and the 9 th month to the 15 th month of the cycle, showing the significance of the cropping pattern as well as the natural vegetation growth cycle. The crosswavelet analysis further depicted important coherence, leading, and lagging phases among climatic factors and NDVI. Our research provided significant insights into the long-term variability and coherence of various climatic factors with NDVI that are applicable on regional and global scales.