Non-stationary and unequally spaced NDVI time series analyses by the LSWAVE software

Change detection within non-stationary and unequally spaced remote sensing time series has become a key methodology for a broad range of environmental applications. A new method of analysing vegetation variation over lands is proposed. Four regions in northern Tunisia with various characteristics are selected, and a non-stationary and unequally spaced Normalized Difference Vegetation Index (NDVI) time series is obtained for each region since 2000. The Landsat 7 remote sensing satellite imagery with insignificant cloud-shadow coverage is used to calculate the NDVI after atmospheric correction. The Least-Squares Wavelet (LSWAVE) software is implemented to rigorously analyse each NDVI time series and study the relationship between the vegetation of olive trees and temperature/precipitation in one of the regions. To investigate possible effects of temperature on the green cover caused by increasing water salinity, the coherency between the NDVI and sea surface temperature time series is also shown in the region of Lake Ichkeul in Tunisia.