Publications

Xu, MY; Yao, N; Hu, AN; de Goncalves, LGG; Mantovani, FA; Horton, R; Heng, L; Liu, G (2022). Evaluating a new temperature-vegetation-shortwave infrared reflectance dryness index (TVSDI) in the continental United States. JOURNAL OF HYDROLOGY, 610, 127785.

Abstract
Accurate dryness monitoring is important for formulating reasonable response measures to reduce social and economic losses caused by drought. The land surface temperature (LST), shortwave infrared (SWIR) reflectance, and vegetation index (VI) are popular remote sensing (RS) indices that can be individually used to characterize surface dryness. Given the interactions of these factors, limitations are inevitably associated with using a single factor. Integrated dryness indices that combine LST or SWIR reflectance with the VI have thus been successively proposed and applied for dryness monitoring and soil moisture (SM) retrieval work. However, the advantages of these three indicators have not yet been combined to construct a more comprehensive dryness index. In this study, we integrated the LST, enhanced vegetation index (EVI), and SWIR reflectance and developed an integrated satellite-based dryness index with simple calculations, called the temperature vegetation shortwave infrared reflectance dryness index (TVSDI). The proposed TVSDI was thoroughly assessed in the continental United States (CONUS) using the following data: the soil moisture active passive (SMAP) SM; six commonly used dryness indices (i.e., temperature vegetation soil moisture dryness index (TVMDI), temperature vegetation dryness index (TVDI), modified perpendicular dryness index (MPDI), perpendicular dryness index (PDI), standardized precipitation evapotranspiration index (SPEI), and standardized precipitation index (SPI)); in situ SM data collected from 24 Cosmic-ray neutron probe (CRNP) sites covering different climates, soil types, and land cover types; and the United States Drought Monitor (USDM) maps. The results demonstrated that the TVSDI was significantly correlated with SMAP SM (R = -0.75, p < 0.01) and exhibited better performance than the use of LST, EVI, and SWIR reflectance individually. Moreover, the TVSDI and the other six commonly used dryness indices exhibited good spatiotemporal consistency, all with consistency areas > 60%. The evaluation based on in situ SM from 24 CRNP sites indicated that the TVSDI exhibited more stability and accuracy than other satellite-based agricultural dryness indices (TVMDI, MPDI, PDI, and TVDI). Moreover, the spatial patterns of TVSDI maps were not only well-matched with SMAP SM maps but also provided more detailed spatial information. TVSDI maps could capture more dryness and drought variations in natural ecosystems and areas with less intensive human activities than USDM maps. Furthermore, the application of the TVSDI for dryness monitoring in the CONUS revealed that the dryness distributions differed greatly across different geographic regions at monthly and annual scales. In conclusion, the TVSDI was found to be a reliable and accurate satellite-based dryness index.

DOI:
10.1016/j.jhydrol.2022.127785

ISSN:
1879-2707