Abstract
Abstract. Drought is one of the frequent natural disasters in Shandong province, which is characterized by high frequency and wide range. In response to frequent droughts that are not monitored in time, monitoring the changes of drought is of great significance to agricultural production and social development. This study used the Temperature-Vegetation-soil Moisture Dryness Index (TVMDI) model, combined with the optical MODIS land surface temperature, vegetation index, surface albedo data and microwave FY-3B soil moisture data, to monitor the drought of Shandong province in 2016. The precipitation and temperature data of weather station were used to validate the monitoring results. The results show that, in 2016, the drought in Shandong province mainly occurred in winter and spring, and the drought in summer was alleviated. From the perspective of space, the northern Shandong and the Shandong peninsula areas are relatively humid with less drought time, while the local areas in the central and southern Shandong province suffer from severe drought with longer drought time. From the perspective of correlation with meteorological factors, the average correlation coefficient between TVMDI and precipitation can reach 0.45, and the average correlation coefficient between TVMDI and temperature can reach 0.63.
Highlights
Drought is a frequent natural disaster in China
The correlation coefficient (R2) between FY-3B original monthly soil moisture data and the measured precipitation is 0.83, while the correlation coefficient (R2) between the downscaling soil moisture results and the measured precipitation is 0.86.The results show that the soil moisture still maintains a good accuracy after downscaling
There are several other indices that are insensitive to variations of soil moisture, such as the Soil Adjusted Vegetation Index (SAVI) and the Modified Soil Adjusted Vegetation Index (MSAVI)[8].By analyzing the correlation between PVI, modified soil adjusted vegetation index (MSAVI) and normalized difference vegetation index (NDVI), as shown in figure 4, it was found that MSAVI had a higher correlation
Summary
Drought is a frequent natural disaster in China. It damages the agricultural production and ecological environment, and seriously affects the social production and life of human beings. Amani et al pointed out that soil moisture (SM) was a direct indicator of drought, while land surface temperature (LST) and vegetation status were indirect indicators of drought. These three variables are related variables, and one of them change will cause change in the other two. Based on the MODIS LST, vegetation index, surface albedo and the microwave FY-3B soil moisture data, this paper used TVMDI model to study the drought situation in Shandong province in 2016. Using optical remote sensing MODIS data and downscaled FY-3B soil moisture data, a three-dimensional feature space composed of normalized surface temperature, vegetation index and soil moisture, namely TVMDI, is constructed. The results can provide a help for drought analysis, disaster prevention and mitigation in Shandong province
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