Soil Moisture Inversion Based On Active Microwave Remote Sensing In Typical Black Soil Area

Land is an important basis for human beings to obtain material resources and means of production.All human life and production activities are inseparable from land participation.In the past tens of thousands of years,people have made use of land from shallow to deep,and human-land interaction has become more and more frequent,which can not be separated from the participation of water.Accurate irrigation and fert ilization in field arable land and real-time monitoring of soil moisture content in regional farmland are the basis for land protection and efficient management of cultivated land.As an indicator of drought change,soil moisture directly affects global food production and quality,which in turn restricts the development of agriculture and animal husbandry.Traditional soil moisture monitoring is based on soil moisture and temperature for a wide range of locations.Sampling process is time-consuming,labor-consuming and costly.The emergence of remote sensing technology provides a solution for fast acquisition of spatial and temporal distribution information of soil moisture in the field.Active microwave remote sensing has become the main method and reliable data source of regional soil moisture monitoring by virtue of its high sensitivity to soil moisture,all-weather and all-day observation ability,and is not affected by clouds,rain and fog.Therefore,the study of soil moisture has a certain guiding significance for regional arable land quality evaluation,crop yield estimation and precision irrigation.In this paper,Zhaoguang Farm in Heilongjiang Province is selected as the research area,and 8-meter resolution Radarsat-2 and 30-meter resolution DEM images are selected as data sources.To solve the problem of inaccurate correlation length of soil roughness factor measured in the field,a new empirical model for soil moisture prediction in black soil area is proposed.The Oh model is used to simulate the influence of surface parameters and system parameters on different polarization backscattering coefficients.Based on image data and field measurement data,an empirical model for soil moisture measurement in the study area is established.The relationshi p between soil moisture and topography is further discussed.The following conclusions are drawn:(1)Comparing the microwave scattering models,the Oh model is used to describe the microwave scattering characteristics of bare surface.Under different pola rization modes,the radar backscattering coefficient decreases with the increase of incident angle,increases with the increase of soil moisture and decreases with the increase of root mean square height.The correlation between image extraction value and simulation value is high,which lays a foundation for the later empirical model.(2)A method of joint inversion of soil moisture by Oh model and empirical model is proposed.The new model only has two unknown parameters(s and mv).Combining with the diff erence of VV and VH polarization backscattering coefficients to remove the influence of root mean square height,the surface soil moisture can be measured.(3)Compared with the measured data,the simulated values of verification points are generally smaller,the correlation coefficient is 0.655,and the average absolute error is 0.053 cm3/cm3,which shows that the empirical model proposed in this paper is effective.(5)Distribution indices were used to study the distribution characteristics of water data in different grade topographic factors.The results showed that the soil moisture level was dominant in the low elevation and small slope range,whereas the water drought level was dominant in the high elevation and steep slope areas.(6)The content of soil moisture in shady and slope was higher than that in sunny slope and the soil moisture content in the bottom was higher than that in the top.Within the limited elevation range,there is a positive correlation between soil water distribution area and ele vation.There is a negative correlation between soil water area and slope gradient at all levels.Soil water content is the highest on shady slope(west slope,Northwest slope),followed by sunny slope(southeast slope,South slope).