The utility of combining optical and thermal images in monitoring agricultural drought in semiarid mediterranean environments

Agricultural drought in a typical semiarid Mediterranean environment is investigated during the growing seasons of 1997 through 2020 using a combination of optical and thermal sensors onboard Landsat satellites. The combination of the Normalized Difference Vegetation Index – Land Surface Temperature (NDVI- LST) space was able to distinguish between drought and non-drought years. A distinct trapezoidal shape was clearly defined during non-drought years, reflecting the strong negative correlation between NDVI and LST. The NDVI-LST space was poorly defined for drought-stricken years with no clear link between the two parameters. The non-universal relationship between LST and NDVI was addressed using the Monin- Obukhov similarity formulation which shows that the widely observed convergence of LST at high NDVI values could be explained by the asymptotic nature of LST against surface roughness length for non-stressed vegetation. The NDVI-LST space was compared with seasonal and annual precipitation and different SPI windows to check the ability of the remote sensing metric to identify drought. A high correlation exists between the NDVI-LST space on the one hand and the 9- month, annual precipitation, the SPI-6, SPI-9 and SPI-12 windows, with correlation coefficients of 0.74, 0.76, 0.76, 0.80, and 0.80, respectively, which are statistically significant.