Study Of Soil Moisture Retrival Based On MODIS Image Data In The Yellow River Delta

Soil moisture on the ground and atmosphere interface exchange of water and energyplay an important role in the process,which is crucial to the growth of crops at the same time,and affect the land degradation, vegetation coverage, climate, ecology, hydrology, agricultureand other fields of important parameters. Traditional drying of soil moisture monitoringmethods including weighing method, neutron probe detection method, the resistance methodand so on, although you can more accurately monitoring soil moisture content in a small area,but it requires great manpower and time, timeliness is not high, and can not fully reflect thesoil moisture content in large area,which can not be used in a wide range of soil moisturemonitoring. Compared with traditional soil moisture monitoring method of punching, effort,and to take plane,It do not have the disadvantages such as timeliness, by uesing the means ofremote sensing inversion of soil moisture can realize the real-time dynamic monitoring oflarge area, whole area therefore USES the means of remote sensing monitoring soil moisturecaused more and more people’s attention.We often use of remote sensing, aviation and satellite remote sensing research on soilmoisture monitoring, among them, the commonly used band includes visible light and nearinfrared, and microwave bands. Using remote sensing monitoring soil moisture, differentwavelengths are used by the inversion of soil moisture inversion method is different also, forremote sensing of soil moisture inversion study, the main use of remote sensing inversionmethod are as follows: considering the heat conduction balance apparent thermal inertiamethod, using the normalized difference vegetation index (NDVI) and the surface of theearth’s surface temperature (TS) method and TS/NDVI space model can be built based onmicrowave remote sensing inversion method. At home, since the1980s, using the method ofthermal inertia in NOAA/AVHRR images inversion of soil moisture has done a lot of work, aseries of achievements. But only the use of canopy temperature and vegetation index for soilmoisture inversion has certain limitation, combine the two, construct the NDVI and TS TVDIinverse model to calculate the soil moisture to eliminate the influence of soil background, soas to improve the inversion accuracy and TVDI method is the most widely used.This paper finishing for soil moisture remote sensing inversion study, sums up theprevious data, studied the soil moisture inversion model of several common, find out their respective advantages and disadvantages, so as to select the inversion model can meet theneeds of this study, namely the temperature vegetation index model TVDI model, then usingTVDI model inversion of soil moisture in the delta area of the Yellow River is studied.(1) satellite MODIS remote sensing data from NASA’s MODIS data products. First usingthe MODIS data processing software for data preprocessing, including geometric correction,projection transformation, the cutting data, etc., is obtained in this study the MOD13A2vegetation index (NDVI) and MOD11A2ground temperature data (TS).(2) MOD11A2data for eight days synthetic spatial resolution of1km of the groundtemperature data (TS), using the maximum synthesis synthesize eight days of LST data into16days of LTS data, and compared with the same period of vegetation index (NDVI) dataspatial model TS/NDVI, please investigate characteristics of space model and calculate theTVDI images in the study area, combining with weather stations measured data of soilmoisture inversion in the study area.(3) using the measured values of the soil moisture data verification, to improve theinspection accuracy of the inversion result by spatial interpolation methods validation. Andthe spatial and temporal distribution of soil moisture condition of Yellow River delta isanalyzed.Inversion results and comparative analysis of the measured data show that the use of theinversion model can better inversion of soil relative humidity, the average relative error ofmeasured values and the inversion value at about17%, and the inversion of the Yellow Riverdelta area of the overall trend of soil moisture and the space-time distribution features of soilmoisture in this region.