Spatiotemporal relationships between remotely sensed soil moisture and NDVI in semi-arid areas of Morocco by coupling SMOS and MODIS products

Soil moisture is the most important parameter for vegetation growth and greenness in arid and semi-arid ecosystems. The objective of this study is to evaluate the effects of soil moisture variations on vegetation conditions in the center of the Beni Mellal-Khénifra region (Morocco). The data used to achieve these objectives are as follows: the time series of the Normalized Difference Vegetation Index (NDVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the time series of SMOS data products (soil moisture and ocean salinity). These data cover the growing season (2017–2018). The relationship between soil moisture and NDVI is calculated based on Lag (10-day back); the underlying reason that has been the current state of NDVI can be affected by the state of soil moisture a few periods back. Results clearly showed the lagged effect of soil moisture on the condition of crops (cereals). The results indicate that NDVI is strongly related to soil moisture which reaches maximum positive correlations of 0.53. Therefore, this approach tested in this study could be used as an effective tool for monitoring and mapping the effect of soil moisture on vegetation. It can be applied by farmers for crop management and monitoring.