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Spatiotemporal variability of soil moisture in arid vegetation communities using MODIS vegetation and dryness indices

Among the methods devised to delineate soil and water information, optical/thermal remote sensing offers great capabilities by providing spatiotemporally multi-scale data and products like surface dryness indices. In this context, the present study utilized the MODIS-based TVDI, iTVDI, and VDI indices to scrutinize the effect of dryness on soil moisture in three vegetation communities: Artemisia spp. (sagebrush), Astragalus spp. (astragale) and grassland in central Iran during a wet (2004) and a dry year (2008). The MOD13A2, MOD11A2, and MOD09A1 products acquired on DOYs (day of the year) 97, 129, 161, and 193 were used to extract dryness and vegetation indices. The downscaled 32-day interval PERSIANN-CCS products and field-measured soil moisture were used to appraise the validity of indices. The results showed statistically significant relationships (P < .05) between iTVDI and cumulative precipitation and soil moisture in all vegetation communities and on most DOYs, suggesting iTVDI as an effective indicator to monitor dryness status. Foremost among the vegetation indices, NDVI was found as a good complementary indicator to estimate vegetation-soil moisture conditions due to exhibiting stronger linear associations with precipitation, particularly in grassland during the wet (R2 = 0.81) and the dry (R2 = 0.72) year. The lowest values of dryness indices were observed in western and southern parts of the study area. In general, it was concluded that side by side assessment of vegetation and dryness indices was a more promising approach to dryness assessment and management over arid and semi-arid rangelands.

Journal Papers
Month/Season: 
January
Year: 
2020