Temperature-Vegetation-soil Moisture Dryness Index (TVMDI)

Abstract While Soil Moisture (SM) can be used as a direct indictor of dryness, the Land Surface Temperature (LST) and vegetation status are indirectly related to SM, and consequently, affect the degree of dryness. Each of these three variables has been individually used to assess the dryness. Furthermore, a combination of the LST and vegetation information has also been applied for dryness estimation through the scatter-plot of the LST and Normalized Difference Vegetation Index (NDVI). However, a combination of these three variables has not been used to estimate the dryness. In this study, a 3 Dimensional (3D) space of the LST, Perpendicular Vegetation Index (PVI), and SM was developed to define a new dryness index named the Temperature-Vegetation-soil Moisture Dryness Index (TVMDI). The TVMDI was evaluated against in situ SM and soil temperature data, as well as the NDVI. The results demonstrated that the TVMDI values were highly correlated with the field soil temperature data and the NDVI (R = 0.78 and R = − 0.87, respectively). However, even though the dryness values estimated from the TVMDI were not highly correlated with the in situ SM data, the correlation was still acceptable (R = − 0.65). Furthermore, a comparison between the proposed index and several satellite-based dryness indices, including the Perpendicular Drought Index (PDI), Modified Perpendicular Drought Index (MPDI), Second Modified Perpendicular Drought Index (MPDI1), and Temperature-Vegetation Dryness Index (TVDI), concluded that the TVMDI was the most accurate index. Moreover, using the TVMDI and multi-temporal Landsat 8 images two dryness maps were produced for the Yanco area to show the effectiveness of the proposed index in depicting the temporal and spatial variation of dryness values for medium spatial resolution images. To show the effectiveness of the TVMDI in large scale applications, two dryness maps from the all of Australia and Iran were also produced using the MODerate Resolution Imaging Spectrometer (MODIS) data. Overall, it was concluded that the TVMDI had a high potential to map dryness over different regions, and is a promising index for early awareness of drought risk management.

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