Abstract
Abstract. In order to further to improve the monitoring accuracy of soil moisture spatial and temporal changes in Guangxi, this paper uses MODIS, Landsat8, ASTER GDEM data and measured relative soil moisture data as data sources. According to the design idea of complementary advantages, the EVI value of Landsat8 image is partitioned, and the relative soil moisture is inverted by ATI model method in the area of EVI≤0.33, and the relative soil moisture is inverted by TVDI model in the area of EVI>0.33. The apparent thermal inertia model (ATI) and the temperature vegetation drought index model (TVDI) was used to invert the relative soil moisture in Guangxi. The results show that the temporal variation of relative soil moisture in the study area in 2017 is the change cycle from rising to falling: the rising period is from January to July, and the falling period is from August to December, in which the relative soil moisture reaches the peak in July. The minimum value are December; the relative soil moisture in the north of Guangxi are generally higher than that in southern Guangxi. The correlation between the relative soil moisture value of the ATI model and the TVDI model partition retrieval and the measured relative soil moisture data is higher, and the relative soil moisture retrieval effects is better.
Highlights
Soil moisture is one of the main parameters in the fields of climate, hydrology, ecology and agriculture
In the remote sensing monitoring of regional relative soil moisture, many scholars have established a number of relative soil moisture retrieval models, which are based on apparent thermal inertia (ATI)(Liu Z H et al .,2006; Ding Z H,. 2014; Ma C F et al,.2012 ) and temperature vegetation drought index (TVDI)( Gao P X et al .,2018; Gao Y P et al.,2017; Guo R N et al.,2018) .The retrieval model is a model that has been widely used and has high precision in recent years
The apparent thermal inertia model is only suitable for bare soil and low vegetation coverage area,while the temperature vegetation drought index model is only suitable for medium and high vegetation coverage area(Yan H B et al.,2017)
Summary
Soil moisture is one of the main parameters in the fields of climate, hydrology, ecology and agriculture It plays an important role in the exchange of matter and energy at the interface between the surface and the atmosphere. The relative soil moisture retrieval based on remote sensing technology is one of the main ways of soil moisture monitoring in the region today. In the remote sensing monitoring of regional relative soil moisture, many scholars have established a number of relative soil moisture retrieval models, which are based on apparent thermal inertia (ATI)(Liu Z H et al .,2006; Ding Z H,. The apparent thermal inertia model is only suitable for bare soil and low vegetation coverage area ,while the temperature vegetation drought index model is only suitable for medium and high vegetation coverage area(Yan H B et al.,2017). The remote sensing retrieval research of relative soil moisture in Guangxi by using the above models is mainly
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