Abstract
Agricultural drought is one of most damaging agricultural hazards worldwide that can bring significant agricultural losses and water scarcity. The use of satellite images for monitoring agricultural drought has received increasing research attention and has also been applied at both the regional and global scales. In this paper, the land surface temperature (LST) and radiance products of the new Sentinel-3A SLSTR (sea and land surface temperature radiometer) launched by European Space Agency (ESA) are used for the first time for estimating the vegetation temperature condition index (VTCI), which in turn is used for monitoring agricultural drought in the Hetao Plain of Inner Mongolia, China. This paper initially analyzes the correlation between LST and normalized difference vegetation index (NDVI) by using time series time MODIS LST and NDVI products under different vegetation growth conditions. The findings reveal that VTCI can only be used in warm seasons (late spring and summer periods) when negative correlations between LST and NDVI are observed. Therefore, VTCI images are captured in the study area between July and August 2017 by using Sentinel-3A SLSTR LST and NDVI and are utilized for drought investigation. These images reveal that the average VTCI of the cultivated land pixels in the study area has increased from 0.4511 on July 28 to 0.5229 on August 12 before declining to 0.4710 on August 18 due to the rainfall in the first period, thereby indicating that VTCI has a timely response to rainfall. Meanwhile, cross-comparison of VTCI values from Sentinel-3A SLSTR shows high consistency in terms of spatial distribution with that estimated from EOS MODIS products. The difference between these indices ranged from −0.1 to 0.1 for most points, especially in the cultivated land cover. Overall, the findings support the use of the LST and NDVI products of Sentinel-3A SLSTR in monitoring agricultural drought.
Highlights
Agricultural drought is a natural hazard and a complex worldwide phenomenon (Wilhite and Glantz, 1985; Smith and Katz, 2013) that is closely related to water security and crop production and can even lead to significant economic losses, especially for developing countries (Wilhite, 2005; Godfray et al, 2010). Wilhite and Glantz (1985) categorized droughts into meteorological, hydrological, agricultural, and socioeconomic droughts, whose severity is influenced by their intensity, duration, spatial coverage, and local socioeconomic level
When combined with the land surface temperature (LST) and normalized difference vegetation index (NDVI) retrieved from satellite data, vegetation temperature condition index (VTCI) may provide more valuable information for agricultural drought monitoring, especially in large-scale areas and regions with insufficient ground monitoring stations or infrastructure
This work combined the VTCI obtained from Sentinel-3A Sea and Land Surface Temperature Radiometer (SLSTR) LST with NDVI to monitor agricultural drought in the Hetao Plain and obtained reasonable results
Summary
Agricultural drought is a natural hazard and a complex worldwide phenomenon (Wilhite and Glantz, 1985; Smith and Katz, 2013) that is closely related to water security and crop production and can even lead to significant economic losses, especially for developing countries (Wilhite, 2005; Godfray et al, 2010). Wilhite and Glantz (1985) categorized droughts into meteorological, hydrological, agricultural, and socioeconomic droughts, whose severity is influenced by their intensity, duration, spatial coverage, and local socioeconomic level. Given that VNIR and SWIR images can be used to calculate various vegetation (e.g., NDVI and Enhanced Vegetation Index, EVI) and water indices (e.g., NDWI) while TIR images are suitable for estimating LST, it is hypothesized that SLSTR observations have potential to monitor agricultural drought. This potential has not been previously evaluated and reported in the literature.
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