技术领域Technical Field
本发明属于图像处理技术领域，具体涉及一种基于大气校正C波段InSAR数据的土壤湿度估算方法。The invention belongs to the technical field of image processing, and in particular relates to a soil moisture estimation method based on atmospheric correction C-band InSAR data.
背景技术Background technique
合成孔径雷达(SAR)，是一种主动式的对地观测系统，全天时、全天候对地实施观测、并具有一定的地表穿透能力。因此，SAR系统在灾害监测、环境监测、海洋监测、资源勘查、农作物估产、测绘和军事等方面的应用上具有独特的优势。其中，土壤水分反演是SAR图像应用的一个热点。Synthetic Aperture Radar (SAR) is an active earth observation system that can observe the earth around the clock and in all weather conditions and has a certain surface penetration capability. Therefore, the SAR system has unique advantages in disaster monitoring, environmental monitoring, ocean monitoring, resource exploration, crop yield estimation, mapping and military applications. Among them, soil moisture inversion is a hot topic in SAR image applications.
传统的土壤湿度测量手段是利用仪器或者烘干等等手段实地进行采样测量，这种方式不仅费时费力，而且成本高、适用范围小，很难推广到大区域。SAR(合成孔径雷达)的发射解决了这些问题，在近几十年对土壤含水量的研究成果表明，土壤水分含量会对雷达的信号散射造成很大的影响，两者具有相关性，通过SAR提取土壤水分可以大大提高反演的可靠性和准确性。The traditional method of measuring soil moisture is to use instruments or drying to conduct sampling measurements on site. This method is not only time-consuming and labor-intensive, but also costly and has a small scope of application, making it difficult to promote to a large area. The launch of SAR (Synthetic Aperture Radar) solves these problems. Research results on soil moisture in recent decades have shown that soil moisture content has a great impact on radar signal scattering, and the two are correlated. Extracting soil moisture through SAR can greatly improve the reliability and accuracy of inversion.
闭合相位或相位三元组是可以从三个SAR图像计算的三个干涉图的干涉相位的代数和。为三个共同配准的SAR图像的每个像素计算相位三元组。值得注意的是，闭合阶段对地表变形、大气延迟或地形误差不敏感，由此提供了一种估算土壤水分的方法。相位不一致可用于估计土壤水分值。然而，闭合相位的模型反演是不确定的，即使闭合相位与相干幅度相结合，也有产生不同的结果。这意味着不同的土壤水分值组合在一个三元组中会产生相似的闭合阶段。The closure phase or phase triplet is the algebraic sum of the interferometric phases of three interferograms that can be calculated from three SAR images. The phase triplet is calculated for each pixel of the three co-registered SAR images. It is noteworthy that the closure phase is insensitive to surface deformation, atmospheric delay or topographic errors, thereby providing a method to estimate soil moisture. Phase inconsistencies can be used to estimate soil moisture values. However, model inversion of the closure phase is uncertain, even when the closure phase is combined with the coherence amplitude, it produces different results. This means that different combinations of soil moisture values in a triplet will produce similar closure phases.
在没有地形变形和适当去除大气相位延迟(APD)的情况下，从干涉相位直接反演土壤水分比使用闭合相位和相干性效果更好。差分干涉技术在测量土壤水分时的主要限制是合成孔径雷达(SAR)信号的时间去相关，特别是在植被和农业地区，以及大气路径延迟(APD)的印记。In the absence of terrain deformation and with proper removal of atmospheric phase delay (APD), direct inversion of soil moisture from the interferometric phase performs better than using closed phase and coherence. The main limitations of differential interferometry in measuring soil moisture are the temporal decorrelation of synthetic aperture radar (SAR) signals, especially in vegetated and agricultural areas, and the imprint of atmospheric path delay (APD).
发明内容Summary of the invention
发明目的：为了克服现有技术中存在的不足，提供一种基于大气校正C波段InSAR数据的土壤湿度估算方法，定量地将InSAR数据与土壤湿度联系起来，利用SAR干涉图像得到大气相位延迟，从而去除了大气对InSAR相位的影响，只保留了土壤湿度对InSAR相位的影响，从而有效提高了土壤湿度的反演精度。Purpose of the invention: In order to overcome the deficiencies in the prior art, a soil moisture estimation method based on atmospherically corrected C-band InSAR data is provided, which quantitatively links InSAR data with soil moisture, and uses SAR interferometric images to obtain atmospheric phase delay, thereby removing the influence of the atmosphere on the InSAR phase and retaining only the influence of soil moisture on the InSAR phase, thereby effectively improving the inversion accuracy of soil moisture.
技术方案：为实现上述目的，本发明提供一种基于大气校正C波段InSAR数据的土壤湿度估算方法，包括如下步骤：Technical solution: To achieve the above object, the present invention provides a soil moisture estimation method based on atmospheric correction C-band InSAR data, comprising the following steps:
S1：对SAR图像进行去噪处理；S1: De-noising of SAR images;
S2：以步骤S1中去噪后的SAR图像作为输入图像，处理N幅SAR图像的时间序列，计算出N-1幅干涉图像；S2: using the SAR image after denoising in step S1 as the input image, processing the time series of N SAR images, and calculating N-1 interference images;
S3：以步骤S2中输出的干涉图像作为输入图像，根据Sentinel-1图像和其他外部数据进行APD相位估计，并且进行APD相位校准；S3: using the interference image output in step S2 as an input image, performing APD phase estimation based on the Sentinel-1 image and other external data, and performing APD phase calibration;
这里需要说明的是哨兵1号(sentinel-1)由两颗极轨卫星A星和B星组成。两颗卫星搭载的传感器为合成孔径雷达(SAR)，属于主动微波遥感卫星，传感器搭载C波段。It should be noted here that Sentinel-1 consists of two polar-orbiting satellites, A and B. The sensors carried by the two satellites are synthetic aperture radars (SAR), which are active microwave remote sensing satellites, and the sensors are equipped with C band.
S4：建立分析模型用于提供土壤水分变化与干涉相位和相干性之间的直接关系；S4: Develop an analytical model to provide a direct relationship between soil moisture changes and interferometric phase and coherence;
S5：根据步骤S2中输出的SAR图像干涉相位数据和步骤S3中输出的APD相位之间的差值，得出InSAR数据的剩余相位，将其作为输入代入到步骤S4中土壤水分变化与干涉相位之间的分析模型，得出土壤湿度。S5: According to the difference between the SAR image interference phase data output in step S2 and the APD phase output in step S3, the residual phase of the InSAR data is obtained, and it is substituted as input into the analysis model between soil moisture change and interference phase in step S4 to obtain soil moisture.
本发明还包括步骤S6，所述步骤S6具体为：将土壤水分的实测值根据步骤S4中的分析模型转换为相位和相干值，再将SAR数据干涉相位中的APD相位结果移除，得到剩余相位，将两者进行比较，进行精度评估。The present invention also includes step S6, which specifically includes: converting the measured value of soil moisture into phase and coherence value according to the analysis model in step S4, then removing the APD phase result in the SAR data interference phase to obtain the remaining phase, comparing the two, and performing accuracy evaluation.
进一步地，所述步骤S1具体为：在提取土壤湿度之前通过滤波器对SAR图像进行滤波处理。Furthermore, the step S1 specifically includes: filtering the SAR image through a filter before extracting soil moisture.
进一步地，所述步骤S2中N-1幅干涉图像的计算方法为：Furthermore, the calculation method of the N-1 interference images in step S2 is:
A1：使用菊花链策略选择SAR图像对进行堆栈生成，取t时刻和t+Δt时刻的两幅SAR图像；A1: Use the daisy chain strategy to select SAR image pairs for stack generation, taking two SAR images at time t and time t+Δt;
A2：使用精确轨道和外部DEM进行配准；A2: Use precise orbits and external DEM for registration;
A3：计算获取到干涉图：同一区域的两幅SAR图像的时间差Δt在最小化时可以去除地形变化对SAR图像的相位影响，在这种情况下，两幅SAR图像的相位差主要与SAR图像的采集时间之间APD的时间变化有关，因此可以依靠两幅SAR图像之间的相位差值得到干涉图像，从而得到干涉相位图。A3: Calculate and obtain the interference pattern: When the time difference Δt between two SAR images of the same area is minimized, the phase effect of terrain changes on the SAR image can be removed. In this case, the phase difference between the two SAR images is mainly related to the time change of APD between the acquisition time of the SAR images. Therefore, the interference image can be obtained based on the phase difference between the two SAR images, thereby obtaining the interference phase pattern.
进一步地，所述步骤S3中APD的估计方法为：Furthermore, the APD estimation method in step S3 is:
在两个SAR图像的采集之间没有明显的地表形变的情况下，可以假设APD对干涉相位φ的影响：In the case where there is no significant surface deformation between the acquisition of two SAR images, the effect of APD on the interferometric phase φ can be assumed to be:
其中，ΔφAPD为大气延迟引起的相位贡献，λ为雷达波长；Where ΔφAPD is the phase contribution caused by atmospheric delay, and λ is the radar wavelength;
给定为了最小化时间基线而产生的N幅干涉图的时间序列，可以计算到t时刻的APD：Given a time series of N interferograms generated to minimize the time baseline, the APD at time t can be calculated:
其中i,j为像素坐标，和/>为日期t+1和t的大气相位延迟。Where i,j are pixel coordinates, and/> is the atmospheric phase delay between date t+1 and t.
进一步地，所述步骤S3中APD相位校准的方法为：Furthermore, the method for APD phase calibration in step S3 is:
本发明提出一种四参数线性回归模型，引入APD的低频空间分布信息，并用一组全球导航卫星系统台站对其进行校准；The present invention proposes a four-parameter linear regression model, introduces the low-frequency spatial distribution information of APD, and calibrates it with a group of global navigation satellite system stations;
系统方程为：The system equation is:
其中a1,...,a4是要估计的参数，是像素(i,j)的测地坐标。where a1 ,...,a4 are the parameters to be estimated, are the geodesic coordinates of pixel (i,j).
进一步地，所述步骤S4中分析模型的表达如下：Furthermore, the analysis model in step S4 is expressed as follows:
假设电磁波在土壤中的差分传播与土壤湿度水平对表层垂直波数的影响有关，将土壤模型化为具有复介电常数ε′的均匀有耗介质层，垂直波数k′Z为：Assuming that the differential propagation of electromagnetic waves in the soil is related to the influence of soil moisture level on the vertical wave number of the surface layer, the soil is modeled as a uniform lossy dielectric layer with a complex dielectric constant ε′, and the vertical wave number k′Z is:
其中ω、μ为角速度、介电常数，kx为视线方向的波数；Where ω and μ are the angular velocity and dielectric constant, and kx is the wave number in the line of sight direction;
干涉相位为：The interference phase is:
相干性为：The coherence is:
进一步地，所述步骤S5中土壤湿度的获取方法为：Furthermore, the method for obtaining soil moisture in step S5 is:
估计的土壤湿度是通过最小化一个代价函数来获得的，该函数表示测量的干涉相位与模型预测的相位之间的失拟，土壤湿度的函数为：The estimated soil moisture is obtained by minimizing a cost function that represents the lack of fit between the measured interferometric phase and the phase predicted by the model, as a function of soil moisture:
其中，N1为干涉图数，φ(mυi,mυj)和γ(mυi,mυj)分别为模型预测的相位值和相干值。Where N1 is the number of interference patterns, φ(mυi ,mυj ) and γ(mυi ,mυj ) are the phase value and coherence value predicted by the model, respectively.
进一步地，所述步骤S6中精度评估的具体方法为：Furthermore, the specific method of the accuracy assessment in step S6 is:
首先根据土壤水分变化与干涉相位和相干性之间的分析模型，将土壤湿度的实测值转换为相位和相干值，从而避免了在反演相位时获得错误的土壤湿度；计算具有不同多视窗的APD结果，并将其从干涉相位中移除，以得出剩余相位，通过对剩余相位和土壤湿度实测数据的相位和相干值进行比较得到土壤水分反演精度。Firstly, according to the analytical model between soil moisture change and interference phase and coherence, the measured values of soil moisture are converted into phase and coherence values, thereby avoiding obtaining erroneous soil moisture when inverting the phase. The APD results with different multi-windows are calculated and removed from the interference phase to obtain the residual phase. The soil moisture inversion accuracy is obtained by comparing the residual phase with the phase and coherence values of the measured soil moisture data.
本发明建立了InSAR数据和土壤湿度之间的联系，利用c波段合成孔径雷达(SAR)干涉测量(InSAR)技术处理c波段合成孔径雷达(SAR)图像，生成校正后的土壤湿度图，并利用Sentinel-1干涉图的时间序列获得的大气相位延迟(APD)图，来分解APD和土壤湿度对Sentinel-1干涉图的影像，从而有效提升了土壤湿度反演精度。The present invention establishes a connection between InSAR data and soil moisture, uses C-band synthetic aperture radar (SAR) interferometry (InSAR) technology to process C-band synthetic aperture radar (SAR) images, generates a corrected soil moisture map, and uses the atmospheric phase delay (APD) map obtained from the time series of Sentinel-1 interferograms to decompose the images of APD and soil moisture on the Sentinel-1 interferograms, thereby effectively improving the soil moisture inversion accuracy.
有益效果：本发明与现有技术相比，定量地将InSAR数据与土壤湿度联系起来，利用SAR干涉图像得到大气相位延迟，从而去除了大气对InSAR相位的影响，只保留了土壤湿度对InSAR相位的影响，从而有效提高了土壤湿度的反演精度。Beneficial effects: Compared with the prior art, the present invention quantitatively links InSAR data with soil moisture, and uses SAR interferometric images to obtain atmospheric phase delay, thereby removing the influence of the atmosphere on the InSAR phase and retaining only the influence of soil moisture on the InSAR phase, thereby effectively improving the inversion accuracy of soil moisture.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
图1为本发明的方法流程示意图。FIG1 is a schematic flow chart of the method of the present invention.
具体实施方式Detailed ways
下面结合附图和具体实施例，进一步阐明本发明，应理解这些实施例仅用于说明本发明而不用于限制本发明的范围，在阅读了本发明之后，本领域技术人员对本发明的各种等价形式的修改均落于本申请所附权利要求所限定的范围。The present invention is further explained below in conjunction with the accompanying drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. After reading the present invention, various equivalent forms of modifications to the present invention by those skilled in the art all fall within the scope defined by the claims attached to this application.
本发明提供一种基于大气校正C波段InSAR数据的土壤湿度估算方法，如图1所示，其包括如下步骤：The present invention provides a soil moisture estimation method based on atmospheric correction C-band InSAR data, as shown in FIG1 , which comprises the following steps:
S1：对SAR图像进行去噪处理：S1: De-noising of SAR images:
在提取土壤湿度之前通过滤波器对SAR图像进行滤波处理。The SAR images are filtered by a filter before extracting soil moisture.
S2：以步骤S1中去噪后的SAR图像作为输入图像，处理N幅SAR图像的时间序列，计算出N-1幅干涉图像：S2: Using the SAR image after denoising in step S1 as the input image, process the time series of N SAR images and calculate N-1 interferometric images:
N-1幅干涉图像的计算方法为：The calculation method of N-1 interference images is:
A1：使用菊花链策略选择SAR图像对进行堆栈生成，取t时刻和t+Δt时刻的两幅SAR图像；A1: Use the daisy chain strategy to select SAR image pairs for stack generation, taking two SAR images at time t and time t+Δt;
A2：使用精确轨道和外部DEM进行配准；A2: Use precise orbits and external DEM for registration;
A3：计算获取到干涉图：同一区域的两幅SAR图像的时间差Δt在最小化时可以去除地形变化对SAR图像的相位影响，在这种情况下，两幅SAR图像的相位差主要与SAR图像的采集时间之间APD的时间变化有关，因此可以依靠两幅SAR图像之间的相位差值得到干涉图像，从而得到干涉相位图。A3: Calculate and obtain the interference pattern: When the time difference Δt between two SAR images of the same area is minimized, the phase effect of terrain changes on the SAR image can be removed. In this case, the phase difference between the two SAR images is mainly related to the time change of APD between the acquisition time of the SAR images. Therefore, the interference image can be obtained based on the phase difference between the two SAR images, thereby obtaining the interference phase pattern.
S3：以步骤S2中输出的干涉图像作为输入图像，根据Sentinel-1图像和其他外部数据进行APD相位估计，并且进行APD相位校准：S3: Using the interference image output in step S2 as the input image, perform APD phase estimation based on the Sentinel-1 image and other external data, and perform APD phase calibration:
APD的估计方法为：The APD estimation method is:
在两个SAR图像的采集之间没有明显的地表形变的情况下，可以假设APD对干涉相位φ的影响：In the case where there is no significant surface deformation between the acquisition of two SAR images, the effect of APD on the interferometric phase φ can be assumed to be:
其中，ΔφAPD为大气延迟引起的相位贡献，λ为雷达波长；Where ΔφAPD is the phase contribution caused by atmospheric delay, and λ is the radar wavelength;
给定为了最小化时间基线而产生的N幅干涉图的时间序列，可以计算到t时刻的APD：Given a time series of N interferograms generated to minimize the time baseline, the APD at time t can be calculated:
其中i,j为像素坐标，和/>为日期t+1和t的大气相位延迟。Where i,j are pixel coordinates, and/> is the atmospheric phase delay between date t+1 and t.
APD相位校准的方法为：The method for APD phase calibration is:
本发明提出一种四参数线性回归模型，引入APD的低频空间分布信息，并用一组全球导航卫星系统台站对其进行校准；The present invention proposes a four-parameter linear regression model, introduces the low-frequency spatial distribution information of APD, and calibrates it with a group of global navigation satellite system stations;
系统方程为：The system equation is:
其中a1,...,a4是要估计的参数，是像素(i,j)的测地坐标。where a1 ,...,a4 are the parameters to be estimated, are the geodesic coordinates of pixel (i,j).
S4：建立分析模型用于提供土壤水分变化与干涉相位和相干性之间的直接关系：S4: Develop an analytical model to provide a direct relationship between soil moisture changes and interferometric phase and coherence:
分析模型的表达如下：The analysis model is expressed as follows:
假设电磁波在土壤中的差分传播与土壤湿度水平对表层垂直波数的影响有关，将土壤模型化为具有复介电常数ε′的均匀有耗介质层，垂直波数k′Z为：Assuming that the differential propagation of electromagnetic waves in the soil is related to the influence of soil moisture level on the vertical wave number of the surface layer, the soil is modeled as a uniform lossy dielectric layer with a complex dielectric constant ε′, and the vertical wave number k′Z is:
其中ω、μ为角速度、介电常数，kx为视线方向的波数；Where ω and μ are the angular velocity and dielectric constant, and kx is the wave number in the line of sight direction;
干涉相位为：The interference phase is:
相干性为：The coherence is:
S5：根据步骤S2中输出的SAR图像干涉相位数据和步骤S3中输出的APD相位之间的差值，得出InSAR数据的剩余相位，将其作为输入代入到步骤S4中土壤水分变化与干涉相位之间的分析模型，得出土壤湿度：S5: According to the difference between the SAR image interference phase data output in step S2 and the APD phase output in step S3, the residual phase of the InSAR data is obtained, and it is substituted as input into the analysis model between soil moisture change and interference phase in step S4 to obtain soil moisture:
土壤湿度的获取方法为：The method to obtain soil moisture is:
估计的土壤湿度是通过最小化一个代价函数来获得的，该函数表示测量的干涉相位与模型预测的相位之间的失拟，土壤湿度的函数为：The estimated soil moisture is obtained by minimizing a cost function that represents the lack of fit between the measured interferometric phase and the phase predicted by the model, as a function of soil moisture:
其中，N1为干涉图数，φ(mυi,mυj)和γ(mυi,mυj)分别为模型预测的相位值和相干值。Where N1 is the number of interference patterns, φ(mυi ,mυj ) and γ(mυi ,mυj ) are the phase value and coherence value predicted by the model, respectively.
S6：将土壤水分的实测值根据步骤S4中的分析模型转换为相位和相干值，再将SAR数据干涉相位中的APD相位结果移除，得到剩余相位，将两者进行比较，进行精度评估。S6: Convert the measured value of soil moisture into phase and coherence value according to the analysis model in step S4, then remove the APD phase result in the SAR data interference phase to obtain the residual phase, compare the two and conduct accuracy assessment.
精度评估的具体方法为：The specific method of accuracy assessment is:
首先根据土壤水分变化与干涉相位和相干性之间的分析模型，将土壤湿度的实测值转换为相位和相干值，从而避免了在反演相位时获得错误的土壤湿度；计算具有不同多视窗的APD结果，并将其从干涉相位中移除，以得出剩余相位，通过对剩余相位和土壤湿度实测数据的相位和相干值进行比较得到土壤水分反演精度。Firstly, according to the analytical model between soil moisture change and interference phase and coherence, the measured values of soil moisture are converted into phase and coherence values, thereby avoiding obtaining erroneous soil moisture when inverting the phase. The APD results with different multi-windows are calculated and removed from the interference phase to obtain the residual phase. The soil moisture inversion accuracy is obtained by comparing the residual phase with the phase and coherence values of the measured soil moisture data.
基于上述方案，本实施例中将上述方案进行实例应用，具体过程如下：Based on the above solution, this embodiment applies the above solution as an example, and the specific process is as follows:
步骤1：选择一个大小为N*N滑动的窗口，根据空间滤波原理，对输入的SAR图像进行均值滤波。Step 1: Select a sliding window of size N*N and perform mean filtering on the input SAR image according to the principle of spatial filtering.
步骤2：使用菊花链策略选择SAR图像对进行堆栈生成，取t时刻和t+Δt时刻的两幅SAR图像，Δt为6天；使用精确轨道和外部DEM进行配准；干涉图计算；地球曲率和地形效应去除；使用方位角为3，距离为3的窗口进行相干性估计；WGS84 UTM坐标参考系统的干涉图和相干地形校正和地理编码。输出像素分辨率约为20m。Step 2: Use the daisy chain strategy to select SAR image pairs for stack generation, take two SAR images at time t and time t+Δt, Δt is 6 days; use precise orbits and external DEM for registration; interferogram calculation; remove the earth curvature and terrain effects; use a window with an azimuth of 3 and a distance of 3 for coherence estimation; interferogram and coherence terrain correction and geocoding of the WGS84 UTM coordinate reference system. The output pixel resolution is about 20m.
步骤3：从Sentinel-1图像和其他外部数据估计大气相位延迟(APD)：Step 3: Estimate the atmospheric phase delay (APD) from Sentinel-1 images and other external data:
在两个SAR图像的采集之间没有明显的地表形变的情况下，可以假设APD是对干涉相位φ的主要影响：In the absence of significant surface deformation between the acquisition of two SAR images, it can be assumed that the APD is the main influence on the interferometric phase φ:
其中，ΔφAPD为大气延迟引起的相位贡献，λ为雷达波长；Where ΔφAPD is the phase contribution caused by atmospheric delay, and λ is the radar wavelength;
给定为了最小化时间基线而产生的N幅干涉图的时间序列，可以计算t时刻的APD：Given a time series of N interferograms generated to minimize the time baseline, the APD at time t can be calculated:
其中i,j为像素坐标，和/>为日期t+1和t的大气相位延迟。Where i,j are pixel coordinates, and/> is the atmospheric phase delay between date t+1 and t.
由此提出了一种四参数线性回归模型，引入APD的低频空间分布信息，并用一组全球导航卫星系统台站对其进行校准。A four-parameter linear regression model is proposed, which introduces the low-frequency spatial distribution information of APD and is calibrated using a set of GNSS stations.
系统方程为：The system equation is:
其中a1,...,a4是要估计的参数，是像素(i,j)的测地坐标。这四个参数是用已知的APD值估计的，所以至少需要四个全球导航卫星系统台站。where a1 ,...,a4 are the parameters to be estimated, are the geodetic coordinates of pixel (i, j). These four parameters are estimated using known APD values, so at least four GNSS stations are required.
步骤4：假设电磁波在土壤中的差分传播与土壤湿度水平对表层垂直波数的影响有关，将土壤模型化为具有复介电常数ε′的均匀有耗介质层。Step 4: Assuming that the differential propagation of electromagnetic waves in the soil is related to the effect of soil moisture level on the vertical wave number of the surface layer, the soil is modeled as a uniform lossy dielectric layer with a complex dielectric constant ε′.
垂直波数k′Z为：The vertical wave number k′Z is:
其中ω、μ为角速度、介电常数，kx为视线方向的波数。Where ω and μ are the angular velocity and dielectric constant, andkx is the wave number in the line of sight.
干涉相位为：The interference phase is:
相干性为：The coherence is:
步骤5：估计的土壤湿度是通过最小化一个代价函数来获得的，该函数表示测量的干涉相位与模型预测的相位之间的失拟，它是土壤湿度的函数：Step 5: The estimated soil moisture is obtained by minimizing a cost function that represents the lack of fit between the measured interferometric phase and the phase predicted by the model as a function of soil moisture:
其中，N1为干涉图数，φ(mυi,mυj)和γ(mυi,mυj)分别为模型预测的相位值和相干值。Where N1 is the number of interference patterns, φ(mυi ,mυj ) and γ(mυi ,mυj ) are the phase value and coherence value predicted by the model, respectively.
步骤6：精度评估：将导出的剩余相位与土壤水分测量值进行如下比较，首先根据土壤水分变化与干涉相位和相干性之间的分析模型，将土壤湿度的实测值转换为相位和相干值，从而避免了在反演相位时获得错误的土壤湿度；计算具有不同多视窗的APD结果，并将其从干涉相位中移除，以得出剩余相位，多视窗的计算采用了基于相干性的空间平均值，这样，相干性小于0.2的像素在多视窗计算时不被考虑；通过对剩余相位和土壤湿度实测数据的相位和相干值进行比较得到土壤水分反演精度。Step 6: Accuracy evaluation: The derived residual phase is compared with the soil moisture measurement value as follows: first, the measured soil moisture value is converted into phase and coherence values according to the analytical model between soil moisture change and interference phase and coherence, thereby avoiding obtaining erroneous soil moisture when inverting the phase; APD results with different multi-windows are calculated and removed from the interference phase to obtain the residual phase. The multi-window calculation uses a spatial average based on coherence, so that pixels with a coherence less than 0.2 are not considered in the multi-window calculation; the soil moisture inversion accuracy is obtained by comparing the residual phase with the phase and coherence values of the measured soil moisture data.
本实施例还提供一种基于大气校正C波段InSAR数据的土壤湿度估算系统，该系统包括网络接口、存储器和处理器；其中，网络接口，用于在与其他外部网元之间进行收发信息过程中，实现信号的接收和发送；存储器，用于存储能够在所述处理器上运行的计算机程序指令；处理器，用于在运行计算机程序指令时，执行上述共识方法的步骤。This embodiment also provides a soil moisture estimation system based on atmospherically corrected C-band InSAR data, the system comprising a network interface, a memory and a processor; wherein the network interface is used to realize signal reception and transmission in the process of sending and receiving information between other external network elements; the memory is used to store computer program instructions that can be run on the processor; the processor is used to execute the steps of the above-mentioned consensus method when running the computer program instructions.
本实施例还提供一种计算机存储介质，该计算机存储介质存储有计算机程序，在处理器执行所述计算机程序时可实现以上所描述的方法。所述计算机可读介质可以被认为是有形的且非暂时性的。非暂时性有形计算机可读介质的非限制性示例包括非易失性存储器电路(例如闪存电路、可擦除可编程只读存储器电路或掩膜只读存储器电路)、易失性存储器电路(例如静态随机存取存储器电路或动态随机存取存储器电路)、磁存储介质(例如模拟或数字磁带或硬盘驱动器)和光存储介质(例如CD、DVD或蓝光光盘)等。计算机程序包括存储在至少一个非暂时性有形计算机可读介质上的处理器可执行指令。计算机程序还可以包括或依赖于存储的数据。计算机程序可以包括与专用计算机的硬件交互的基本输入/输出系统(BIOS)、与专用计算机的特定设备交互的设备驱动程序、一个或多个操作系统、用户应用程序、后台服务、后台应用程序等。The present embodiment also provides a computer storage medium, which stores a computer program, and the method described above can be implemented when the processor executes the computer program. The computer readable medium can be considered to be tangible and non-temporary. Non-limiting examples of non-temporary tangible computer readable media include non-volatile memory circuits (such as flash memory circuits, erasable programmable read-only memory circuits or mask read-only memory circuits), volatile memory circuits (such as static random access memory circuits or dynamic random access memory circuits), magnetic storage media (such as analog or digital tapes or hard drives) and optical storage media (such as CDs, DVDs or Blu-ray discs), etc. The computer program includes processor executable instructions stored on at least one non-temporary tangible computer readable medium. The computer program may also include or rely on stored data. The computer program may include a basic input/output system (BIOS) that interacts with the hardware of a special-purpose computer, a device driver that interacts with a specific device of a special-purpose computer, one or more operating systems, user applications, background services, background applications, etc.
本领域内的技术人员应明白，本申请的实施例可提供为方法、系统、或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.
本申请是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。The present application is described with reference to the flowchart and/or block diagram of the method, device (system) and computer program product according to the embodiment of the present application. It should be understood that each process and/or box in the flowchart and/or block diagram, and the combination of the process and/or box in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for realizing the function specified in one process or multiple processes in the flowchart and/or one box or multiple boxes in the block diagram.
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
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