基于全極化雷達(dá)影像反演壟行結(jié)構(gòu)土壤濕度
發(fā)布時(shí)間：2018-08-03 18:27
【摘要】：土壤濕度作為氣候與環(huán)境干旱化的指示因子，是全球變化研究中的重要監(jiān)測(cè)內(nèi)容之一。土壤濕度不僅影響土壤理化特性與植被生長，更直接影響了糧食的質(zhì)量和產(chǎn)量，嚴(yán)重制約著農(nóng)牧業(yè)的發(fā)展。全球水資源的空間分布與耕地的分布尤為矛盾，40%的耕地面積位于干旱區(qū)，直接影響到全球10億人口的生計(jì)。因此，土壤濕度的動(dòng)態(tài)監(jiān)測(cè)對(duì)干旱預(yù)警以及作物估產(chǎn)具有重要的意義。 傳統(tǒng)的基于點(diǎn)測(cè)量的方法很難對(duì)土壤濕度進(jìn)行宏觀的動(dòng)態(tài)監(jiān)測(cè)，通過遙感的可見光-近紅外，熱紅外和微波波段監(jiān)測(cè)土壤濕度已有近50年的歷史。微波波段可以穿透云霧和一定深度的土壤，是能夠定量化反演土壤濕度的最佳波段。被動(dòng)微波法的空間尺度過大，不適宜農(nóng)業(yè)領(lǐng)域的研究，本文選擇主動(dòng)微波法。主動(dòng)微波法反演土壤濕度的基本原理是，雷達(dá)的回波強(qiáng)度主要受到土壤介電常數(shù)和表面粗糙度的影響，而土壤水分是影響土壤介電常數(shù)最主要的因素，以此來建立回波強(qiáng)度和土壤濕度的定量關(guān)系。起壟耕種的方式在全球都是普遍采用的，這種周期性地表是隨機(jī)地表的一種特殊形式。目前常用的土壤濕度反演模型對(duì)周期性地表的適用性較差。中國北方的旱田作物（如玉米、大豆、高粱等）絕大多數(shù)都是采用起壟的耕種方式。本文研究區(qū)位于吉林省公主嶺市境內(nèi)，在松遼平原的東部，以種植玉米、大豆等旱田作物為主。本文分析了周期性地表散射的機(jī)理，模擬了雷達(dá)參數(shù)、地表參數(shù)和壟行結(jié)構(gòu)參數(shù)對(duì)不同極化后向散射系數(shù)的影響，結(jié)合實(shí)測(cè)采樣數(shù)據(jù)和全極化RADARSAT-2雷達(dá)影像數(shù)據(jù)，深入開展了基于主動(dòng)微波法提取周期性地表土壤濕度的研究，并取得了如下創(chuàng)新性研究成果： 1、周期性隨機(jī)地表與平坦隨機(jī)地表之間的根本區(qū)別在于，當(dāng)雷達(dá)脈沖入射到周期性地表時(shí)，通過周期性改變局地入射角的值而改變回波的強(qiáng)度。在不同方位角（即壟向與脈沖入射方向的夾角）狀態(tài)下，模擬局地入射角在一個(gè)周期內(nèi)的變化，分析后向散射系數(shù)對(duì)方位角的響應(yīng)規(guī)律。證明在同極化模式下，后向散射系數(shù)在方位角為90o（觀測(cè)方向垂直于壟向）時(shí)出現(xiàn)最大值，在方位角為0o或180o（觀測(cè)方向平行于壟向）時(shí)出現(xiàn)最小值，而交叉極化對(duì)方位角的響應(yīng)不敏感。 2、在不同極化方式下，模擬波長、入射角、壟高、壟距、土壤濕度、表面粗糙度對(duì)后向散射系數(shù)的影響。研究發(fā)現(xiàn)，波長越短，土壤濕度和表面粗糙度越大，后向散射系數(shù)越大，這個(gè)規(guī)律不會(huì)因?yàn)橹芷谛缘乇矶淖�。在HH極化模式下，隨著土壤濕度的增大，M值（方位角為90o與0o的后向散射系數(shù)的差值，用來衡量后向散射系數(shù)對(duì)方位角的敏感程度）緩慢變大然后趨于飽和；隨著粗糙度的增加，M值迅速降低并趨于飽和；隨著波長的增加，M值緩慢增加并趨于飽和。VV極化對(duì)方位角的敏感性則不受波長、土壤濕度和粗糙度的影響。方位角響應(yīng)函數(shù)的形態(tài)在不同入射角和A/T參數(shù)（1/2的壟高與壟距的比值）下是不同的，通�？捎谜液瘮�(shù)或一元二次函數(shù)進(jìn)行模擬。而且在不同入射角下，M值對(duì)A/T的響應(yīng)規(guī)律也不同。無論參數(shù)如何變化，不同極化對(duì)方位角的敏感性始終滿足：HHVVVH。 3、當(dāng)波長為5.55cm（C波段），入射角為45o時(shí)，在不同極化方式和不同土壤參數(shù)狀態(tài)下，模擬150個(gè)采樣點(diǎn)的后向散射系數(shù)。研究發(fā)現(xiàn)，壟高（或A/T的值）在一定范圍內(nèi)變化時(shí)，不影響后向散射系數(shù)的整體分布規(guī)律，此時(shí)可忽略壟高變化的影響。因此，去除方位角的影響是解決周期性地表土壤濕度反演的關(guān)鍵。根據(jù)平均土壤參數(shù)計(jì)算方位角響應(yīng)曲線，發(fā)現(xiàn)采樣點(diǎn)到響應(yīng)曲線的距離只與土壤濕度和粗糙度有關(guān)，以此建立差值距離和比值距離參數(shù)，去除了方位角的影響。在實(shí)際應(yīng)用中，地表參數(shù)平均值往往未知，研究表明對(duì)采樣點(diǎn)分布規(guī)律進(jìn)行擬合的曲線可替代方位角響應(yīng)曲線。 4、基于RADARSAT-2全極化雷達(dá)數(shù)據(jù)，隨機(jī)提取影像上303個(gè)采樣點(diǎn)，分析不同極化模式下，后向散射系數(shù)對(duì)方位角的響應(yīng)函數(shù)。實(shí)測(cè)的響應(yīng)規(guī)律與理論模擬的規(guī)律基本一致。選取50個(gè)實(shí)測(cè)采樣點(diǎn)中的34個(gè)點(diǎn)進(jìn)行建模，另外16個(gè)點(diǎn)作為檢驗(yàn)點(diǎn)。在不同極化模式下，建立特征參數(shù)與土壤濕度和粗糙度的定量關(guān)系，通過其中兩種極化方式的方程進(jìn)行聯(lián)立可以消去粗糙度參數(shù)，獲取土壤濕度的反演模型。然而此模型的精度甚至不及單極化線性模型的精度。本文通過直接模擬土壤濕度和其中兩個(gè)特征參數(shù)的定量關(guān)系，粗糙度參數(shù)不參與擬合，模型的精度得到了明顯提高。 5、研究發(fā)現(xiàn)，當(dāng)雷達(dá)入射方向垂直或近似垂直于壟向時(shí)，地塊易出現(xiàn)異常高亮度值，即相干散射亮斑。前面建立的經(jīng)驗(yàn)?zāi)Ｐ蛯?duì)散射亮斑區(qū)域的反演明顯是不適用的。本文通過雷達(dá)實(shí)測(cè)值和Oh模型模擬的隨機(jī)地表后向散射系數(shù)，建立了周期性地表與平坦隨機(jī)地表之間的同極化誤差函數(shù)。誤差函數(shù)修正后的交叉極化比q一定程度上去除了方位角的影響，但未去除相干散射亮斑的影響；修正后的同極化比p同時(shí)去除了方位角和相干散射亮斑的影響。最終選取同極化比和交叉極化后向散射系數(shù)與土壤參數(shù)的關(guān)系式，利用LUT表搜索法求解土壤濕度，反演結(jié)果去除了相干散射亮斑的影響。 6、提出了通過修正后Oh模型和經(jīng)驗(yàn)?zāi)Ｐ吐?lián)合反演土壤濕度的方法。Oh模型對(duì)相干散射亮斑區(qū)域的反演具有明顯的優(yōu)勢(shì)，但由于Oh模型受到參數(shù)取值范圍的限制，尤其對(duì)濕度較大地塊的反演精度較差，而經(jīng)驗(yàn)?zāi)Ｐ瓦m用的地表參數(shù)范圍更寬。16個(gè)檢驗(yàn)點(diǎn)反演值與實(shí)測(cè)值誤差的平均值是0.0220cm3/cm3，，相關(guān)系數(shù)為0.9706，均方根誤差為0.0258cm3/cm3。4個(gè)位于相干散射亮斑區(qū)域的檢驗(yàn)點(diǎn)與其他12個(gè)檢驗(yàn)點(diǎn)的反演精度無明顯差異。證明了本文提出的經(jīng)驗(yàn)?zāi)Ｐ团cOh模型聯(lián)合反演壟行結(jié)構(gòu)土壤濕度的方法是有效和可靠的。
[Abstract]:Soil moisture, as an indicator of climate and environmental droughts, is one of the important monitoring contents in the study of global change. Soil moisture affects not only the physical and chemical characteristics of soil and the growth of vegetation, but also the quality and yield of grain, which seriously restricts the development of agriculture and animal husbandry. The spatial distribution of total water resources and the distribution of cultivated land are particularly important. Contradiction, 40% of the cultivated land is in the arid area, which directly affects the livelihoods of the 1 billion population in the world. Therefore, the dynamic monitoring of soil moisture is of great significance to the early warning of drought and the crop yield estimation.
The traditional method based on point measurement is difficult to make a macro dynamic monitoring of soil moisture. It has a history of nearly 50 years to monitor soil moisture through the visible light infrared, thermal infrared and microwave bands of remote sensing. The microwave band can penetrate the clouds and a certain depth of soil. It is the best wave band for the quantitative inversion of soil moisture. The spatial scale of the wave method is too large and is not suitable for the research in the field of agriculture. In this paper, the active microwave method is chosen. The basic principle of the active microwave method for the inversion of soil moisture is that the echo intensity of the radar is mainly influenced by the dielectric constant and surface roughness of the soil, and the soil moisture is the main factor affecting the dielectric constant of soil and soil. The quantitative relationship between wave intensity and soil moisture. The mode of ridging and cultivation is generally adopted all over the world. This periodic surface is a special form of random surface. The current commonly used inversion model of soil moisture is less applicable to periodic surface. Most of the dryfield crops (such as corn, soybeans, sorghum, etc.) in northern China are most of them In this paper, the study area is located in the Gongzhuling city of Jilin Province, in the eastern part of the Songliao plain to grow maize and soybean and other dryland crops. This paper analyses the mechanism of periodic surface scattering, and simulates the effects of radar parameters, surface parameters and ridging structure parameters on different polarization backscattering coefficients. The research on the extraction of periodic surface soil moisture based on active microwave method is carried out by measuring sampling data and fully polarizing RADARSAT-2 radar image data, and the following innovative research results have been obtained.
1, the fundamental difference between the periodic random surface and the flat random surface is that when the radar pulse is incident to the periodic surface, the intensity of the echo is changed by periodically changing the value of the local incidence angle. At the different azimuth angles (i.e. the angle between the ridges and the direction of the pulse incident), the change of the local incidence angle in a period is changed. The response law of the back scattering coefficient of the opposite angle is analyzed. It is proved that the maximum value of the backscattering coefficient at the azimuth angle is 90o (the direction of the ridge is perpendicular to the ridge) in the same polarization mode, and the minimum value occurs when the azimuth is 0o or 180o (the direction of the observation is parallel to the ridge direction), and the response of the cross polarization angle is insensitive.
2, under the different polarization mode, the influence of the simulated wavelength, incidence angle, ridge height, ridge distance, soil moisture and surface roughness on the backscattering coefficient. It is found that the shorter the wavelength, the greater the soil moisture and surface roughness, the greater the backscatter coefficient, the law will not change for the periodic surface. Under the HH polarization mode, with soil moisture With the increase of the M value (the difference between the azimuth and the backscattering coefficient of 90o and 0o), the sensitivity of the backscattering coefficient to the opposite angle of the backscattering coefficient becomes larger and then saturated; with the increase of the roughness, the M value decreases rapidly and tends to saturation; as the wavelength increases, the M value increases slowly and tends to the sensitivity of the saturation.VV polarization angle. It is not affected by wavelengths, soil moisture and roughness. The shape of the azimuth response function is different under different incidence angles and A/T parameters (the ratio of ridge height to ridge distance of 1/2), and usually can be simulated with sinusoidal function or one element two functions. And the response of M value to A/T is different at different incidence angles. The sensitivity of each other's angle is always satisfied: HHVVVH.
3, when the wavelength is 5.55cm (C band) and the incident angle is 45o, the backscattering coefficient of the 150 sampling points is simulated under different polarization modes and different soil parameters. It is found that the overall distribution of the backscatter coefficient is not affected by the ridge height (or the value of A/T) in a certain range, and the influence of the ridge height change can be ignored. Therefore, Removing the influence of azimuth angle is the key to solving the soil moisture inversion on the periodic surface. According to the calculation of the azimuth response curve according to the average soil parameters, it is found that the distance from the sampling point to the response curve is only related to the soil moisture and roughness. In this way, the difference distance and the ratio distance parameters are established, and the influence of the azimuth angle is removed. In practical application, the effect of the azimuth angle is removed. The average value of surface parameters is often unknown, and the study shows that the curve fitting the distribution of sampling points can replace the azimuth response curve.
4, based on the RADARSAT-2 fully polarized radar data, the 303 sampling points on the image are randomly extracted and the response function of the backscatter coefficient in different polarization modes is analyzed. The measured response law is basically the same as that of the theoretical simulation. 34 points of the 50 measured sampling points are chosen to be modeled and the other 16 points are used as the test points. In the same polarization mode, the quantitative relationship between characteristic parameters and soil moisture and roughness is established. Through the equation of two polarization modes, the roughness parameters can be eliminated and the inversion model of soil moisture is obtained. However, the precision of the model is not even more accurate than the single polarization linear model. The quantitative relationship between the two characteristic parameters, roughness parameters do not participate in fitting, the accuracy of the model has been significantly improved.
5, it is found that when the direction of the radar is perpendicular to the ridge or perpendicular to the ridge direction, it is easy to have an abnormal high brightness value, that is, the coherent scattering bright spot. The empirical model established in front of the radar is not suitable for the inversion of the scattered spot area. In this paper, the period of the radar measured values and the random surface backscattering coefficients of the random surface of the Oh model are established. The same polarization error function between the ground surface and the flat random surface. The cross polarization ratio modified by the error function Q does not affect the azimuth angle to a certain extent, but does not remove the influence of the coherent scattering bright spot; the modified same polarization ratio p simultaneously removes the influence of the azimuth and the coherent scattering bright spot. Finally, the same polarization ratio and intersection are selected. The relationship between polarization backscattering coefficient and soil parameters is solved by LUT table searching method. The influence of coherent scattering speckles is removed from the inversion results.
6, the method of combining the modified Oh model with the empirical model to inverse the soil moisture is proposed. The.Oh model has obvious advantages for the inversion of the coherent scattering spot area, but because the Oh model is limited by the range of parameter values, especially the inversion accuracy for the larger humidity plots, the surface parameter range of the empirical model is wider.1. The mean value of the error between the 6 test points and the measured value is 0.0220cm3/cm3, the correlation coefficient is 0.9706. The root mean square root error is 0.0258cm3/cm3.4 in the coherent scattering spot area, and there is no obvious difference between the test point and the other 12 test points. It is proved that the empirical model and the Oh model proposed in this paper are combined to inverse the ridge row structure soil. The method of soil moisture is effective and reliable.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：S152.7;P631.3
本文編號(hào)：2162595
[Abstract]:Soil moisture, as an indicator of climate and environmental droughts, is one of the important monitoring contents in the study of global change. Soil moisture affects not only the physical and chemical characteristics of soil and the growth of vegetation, but also the quality and yield of grain, which seriously restricts the development of agriculture and animal husbandry. The spatial distribution of total water resources and the distribution of cultivated land are particularly important. Contradiction, 40% of the cultivated land is in the arid area, which directly affects the livelihoods of the 1 billion population in the world. Therefore, the dynamic monitoring of soil moisture is of great significance to the early warning of drought and the crop yield estimation.
The traditional method based on point measurement is difficult to make a macro dynamic monitoring of soil moisture. It has a history of nearly 50 years to monitor soil moisture through the visible light infrared, thermal infrared and microwave bands of remote sensing. The microwave band can penetrate the clouds and a certain depth of soil. It is the best wave band for the quantitative inversion of soil moisture. The spatial scale of the wave method is too large and is not suitable for the research in the field of agriculture. In this paper, the active microwave method is chosen. The basic principle of the active microwave method for the inversion of soil moisture is that the echo intensity of the radar is mainly influenced by the dielectric constant and surface roughness of the soil, and the soil moisture is the main factor affecting the dielectric constant of soil and soil. The quantitative relationship between wave intensity and soil moisture. The mode of ridging and cultivation is generally adopted all over the world. This periodic surface is a special form of random surface. The current commonly used inversion model of soil moisture is less applicable to periodic surface. Most of the dryfield crops (such as corn, soybeans, sorghum, etc.) in northern China are most of them In this paper, the study area is located in the Gongzhuling city of Jilin Province, in the eastern part of the Songliao plain to grow maize and soybean and other dryland crops. This paper analyses the mechanism of periodic surface scattering, and simulates the effects of radar parameters, surface parameters and ridging structure parameters on different polarization backscattering coefficients. The research on the extraction of periodic surface soil moisture based on active microwave method is carried out by measuring sampling data and fully polarizing RADARSAT-2 radar image data, and the following innovative research results have been obtained.
1, the fundamental difference between the periodic random surface and the flat random surface is that when the radar pulse is incident to the periodic surface, the intensity of the echo is changed by periodically changing the value of the local incidence angle. At the different azimuth angles (i.e. the angle between the ridges and the direction of the pulse incident), the change of the local incidence angle in a period is changed. The response law of the back scattering coefficient of the opposite angle is analyzed. It is proved that the maximum value of the backscattering coefficient at the azimuth angle is 90o (the direction of the ridge is perpendicular to the ridge) in the same polarization mode, and the minimum value occurs when the azimuth is 0o or 180o (the direction of the observation is parallel to the ridge direction), and the response of the cross polarization angle is insensitive.
2, under the different polarization mode, the influence of the simulated wavelength, incidence angle, ridge height, ridge distance, soil moisture and surface roughness on the backscattering coefficient. It is found that the shorter the wavelength, the greater the soil moisture and surface roughness, the greater the backscatter coefficient, the law will not change for the periodic surface. Under the HH polarization mode, with soil moisture With the increase of the M value (the difference between the azimuth and the backscattering coefficient of 90o and 0o), the sensitivity of the backscattering coefficient to the opposite angle of the backscattering coefficient becomes larger and then saturated; with the increase of the roughness, the M value decreases rapidly and tends to saturation; as the wavelength increases, the M value increases slowly and tends to the sensitivity of the saturation.VV polarization angle. It is not affected by wavelengths, soil moisture and roughness. The shape of the azimuth response function is different under different incidence angles and A/T parameters (the ratio of ridge height to ridge distance of 1/2), and usually can be simulated with sinusoidal function or one element two functions. And the response of M value to A/T is different at different incidence angles. The sensitivity of each other's angle is always satisfied: HHVVVH.
3, when the wavelength is 5.55cm (C band) and the incident angle is 45o, the backscattering coefficient of the 150 sampling points is simulated under different polarization modes and different soil parameters. It is found that the overall distribution of the backscatter coefficient is not affected by the ridge height (or the value of A/T) in a certain range, and the influence of the ridge height change can be ignored. Therefore, Removing the influence of azimuth angle is the key to solving the soil moisture inversion on the periodic surface. According to the calculation of the azimuth response curve according to the average soil parameters, it is found that the distance from the sampling point to the response curve is only related to the soil moisture and roughness. In this way, the difference distance and the ratio distance parameters are established, and the influence of the azimuth angle is removed. In practical application, the effect of the azimuth angle is removed. The average value of surface parameters is often unknown, and the study shows that the curve fitting the distribution of sampling points can replace the azimuth response curve.
4, based on the RADARSAT-2 fully polarized radar data, the 303 sampling points on the image are randomly extracted and the response function of the backscatter coefficient in different polarization modes is analyzed. The measured response law is basically the same as that of the theoretical simulation. 34 points of the 50 measured sampling points are chosen to be modeled and the other 16 points are used as the test points. In the same polarization mode, the quantitative relationship between characteristic parameters and soil moisture and roughness is established. Through the equation of two polarization modes, the roughness parameters can be eliminated and the inversion model of soil moisture is obtained. However, the precision of the model is not even more accurate than the single polarization linear model. The quantitative relationship between the two characteristic parameters, roughness parameters do not participate in fitting, the accuracy of the model has been significantly improved.
5, it is found that when the direction of the radar is perpendicular to the ridge or perpendicular to the ridge direction, it is easy to have an abnormal high brightness value, that is, the coherent scattering bright spot. The empirical model established in front of the radar is not suitable for the inversion of the scattered spot area. In this paper, the period of the radar measured values and the random surface backscattering coefficients of the random surface of the Oh model are established. The same polarization error function between the ground surface and the flat random surface. The cross polarization ratio modified by the error function Q does not affect the azimuth angle to a certain extent, but does not remove the influence of the coherent scattering bright spot; the modified same polarization ratio p simultaneously removes the influence of the azimuth and the coherent scattering bright spot. Finally, the same polarization ratio and intersection are selected. The relationship between polarization backscattering coefficient and soil parameters is solved by LUT table searching method. The influence of coherent scattering speckles is removed from the inversion results.
6, the method of combining the modified Oh model with the empirical model to inverse the soil moisture is proposed. The.Oh model has obvious advantages for the inversion of the coherent scattering spot area, but because the Oh model is limited by the range of parameter values, especially the inversion accuracy for the larger humidity plots, the surface parameter range of the empirical model is wider.1. The mean value of the error between the 6 test points and the measured value is 0.0220cm3/cm3, the correlation coefficient is 0.9706. The root mean square root error is 0.0258cm3/cm3.4 in the coherent scattering spot area, and there is no obvious difference between the test point and the other 12 test points. It is proved that the empirical model and the Oh model proposed in this paper are combined to inverse the ridge row structure soil. The method of soil moisture is effective and reliable.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：S152.7;P631.3
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