| With the development of economy and growing population, irrational use of land resources led to the emergence of ecological problems like land quality degradation. Soil salinization is considered as the prior land quality degradation course in arid and semi-arid area. Therefore,accessing to saline soil physical and chemical characteristics information timely, accurately and dynamically is crucial for governing saline soil, prevent further degradation and sustainable development of agriculture.Traditional soil salinization surveillance uses field sentinel survey method, this consumes more time and energy, with less survey pointsand poor representation, real-time monitoring of a large area cannot be achieved.Using modern remote sensing technology to monitor salinization, with this, large scale, real-time and dynamic monitoring can be achieved. But optical sensing means has certain limitations; it depends on the spectral response characteristics feature of land surface. Microwave remote sensing can compensate for the lack of optical remote sensing in the study of soil salinization. Soil water content and electric conductivity are the main soil characteristicparameters, accessing to them is the critical research process of soil salinity surveyIn this paper, delta oasis of the northern margin of the Tarim Basin in Xinjiang region-Ugan-Kuqa River chosen as study area, Mutual conditionality between soil moisture, electric conductivity and soil salt content have been analyzed.With radar remote sensing, soil moisture information has been extracted, more accurate information on soil conductivity has been obtained using accurate and rapid measurement device-electromagnetic induction EM38,and established salt index multi-platform with remote sensing data, remote sensing inversion model and combined multivariate data. The results showed that:(1) Comparing several vegetation scattering model, according to the study area geographic characteristics with relief plat and sparse vegetation, choose more suitable vegetation scattering model witch is "water-cloud"model that can describe the ground soil backscattering characters even better. After removing the vegetation effect, study the ground backscattering characters, calculate the back scattering coefficient. Correlation analysis has been made to understand the relationship between backscattering coefficient of for different polarization and soil water content. Result shows that HH polarization mode is more sensitive to the soil water content. At last using the relationship between backscattering coefficient of HH polarization and measured soil water content, build the soil water content inversion model.(2) According to the relationship between soil salinity and vertical mode and horizontal electrical conductivity achieved by using the electromagnetic induction instrument EM38, determined the vertical mode electrical conductivity. Introduce the comprehensive index of spectral response (COSRI), build the soil electrical conductivity inversion model by the relationship between ground measured electrical conductivity and COSRI.(3) Correlation analysis has been made among salinity Index, soil water content, and soil conductivity. Soil salinity as the dependent variable, soil water content and soil electrical conductivity as independent variables, build the Synergy Monitoring Model of Remote Sensing and Electromagnetic Induction of soil salinization.(4) Based on fieldsoil salinitymeasurementsampling points, extractthe predictive value of image data, Pearsoncorrelation analysisshowed that, Pearson value of thecorrelation coefficient ofO.842,0.001bytheconfidence intervalfor thesignificant correlation.Use the results compare with the previous model of laboratory SI-ALBEDO feature space model, Pearson value of synergy model0.842is bigger than0.788of latter model and the standard deviation is0.04less than latter0.10. Therefore conclude that synergy monitoring model is feasible, better than the previous model of laboratory to extract more accurate information. |
PDF Full Text Request