基于目标分解的全极化雷达数据估算生物量相关参数方法研究
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摘要
使用微波遥感中的合成孔径雷达技术进行树木生物量相关参数的估算是生物量估算方法中运用较多的方法。目前使用的合成孔径雷达雷达估算生物量的方法中,通常只借助相位信息建立干涉影像对的相位关系同树木植被特性之间的关系式,或者把树木植被整体看做一种均匀分布的介质,分析回波信号强度,求解树木的有关特性。这两种方法没有有效地结合利用雷达影像中的强度和相位信息,不能详细地描述树木植被和电磁波作用的过程,无法正确地描述植被覆盖不完全的区域。这种区域对应于影像中的混合像元情况。对于使用振幅的方法,虽然有详尽的模型描述电磁波和地物的作用,但是由于模型涉及到电磁学原理而过于复杂、参数众多而无法求解。虽然有的利用相位信息的方法通过引入多余的干涉像对,可以求解表示植被覆盖情况的参数,但是这种方法提高了对雷达数据获取的要求,而且确定树高还需要精确的DEM。目标分解是简单可行、又能完整地利用雷达影像的相位和振幅信息详尽地描述成像过程的雷达数据处理方法。使用它进行植被生物量相关参数估计可以解决其他方法在混合像元存在时无法精确处理的问题。
目标分解方法通过对全极化回波的分析,利用回波中各种“垂直”或者具有分量唯一性的散射类型分量来反推和电磁波作用的物体的性质,是分析电磁波和物体共同作用的辐射传输理论和波动理论的有机结合。但是目标分解方法现有的应用主要是解决分类识别问题,没有发挥其在定量遥感分析中的作用。
总的来说,针对不同应用背景的目标分解方法有多种,其中针对植被存在的方法是Freeman-Durden分解。这种分解方法通过三种散射来描述电磁波和植被的作用。本文对已有的抽象表示实际场景的模型进行研究,建立适于表示非均匀植被分布的场景模型,分析电磁波与抽象的植被元素之间的作用,将Freeman-Durden分解分量细化,提出模型公式,将三分量数值和选取的生物量相关参数之间对应起来。这个过程中利用了一些经验模型公式。在使用目标分解方法求解分量过程中,通过分析得到更详尽的表述过程,补足经验模型不能详尽描述电磁波和植被之间的作用过程的缺点。在分析分解分量的形成过程中,本文建立了生物量相关参数和分解分量之间的关系。
为了使Freeman-Durden分解的分量数值能更好地用于定量分析,作者对分解分量求解过程中由于使用有限视数(窗口数)而导致的误差进行了分析,寻找需要改正的分量,并借助Monte Carlo方法模拟数据,实现对需要修正分量的改正。通过实验证明,经过改正后的分解分量数据更符合实际情况。
本文中通过模拟软件获取一系列和实际应用的真实数据获取条件(传感器的工作波段、入射角以及实际场景的地表粗糙度、树木是针叶林还是阔叶林等情况)相似的植被覆盖量不同的模拟数据组,来求解模型参数。在本文实验中,求得的表示具有一定散射特性的回波通过冠层时转换为体散射的数值参数为零,因此不需要考虑这个作用过程。此时可以使用正文中叙述的更合理的方法重新求解模型参数。
最后使用本文提出的模型公式和求得的模型参数计算全极化雷达影像植被覆盖区域的生物量相关参数数值,将结果和相应区域的实测数据对比,验证模型的有效性。首先通过实地测量中的定向点找寻植被覆盖实验区域在光学影像的位置,然后通过光学影像和全极化雷达影像数据配准得到区域在雷达影像上的位置。由于测量条件的限制,通过比较测量区域中生物量相关参数的量测和计算平均值实现模型验证。结果表明,对于Freeman-Durden分解算法能直接求取分解分量数值的绝大多数像素,使用本文的生物量相关参数估算模型进行生物量相关参数计算结果精度很高,能满足实际应用的需要。虽然对于其中一个参数的求解无法精确定量地验证,对比它与模拟数据场景的对应数值,以及定性分析实际场景和求解数值的结果表明,这个参数的求解数值符合实际情况。此外这个参数也可以由可以验证的参数通过树木结构等先验知识求取,不影响模型使用的有效性。总的来说,本文的模型可以得到很好的结果,使用它进行生物量相关参数的估算可以解决混合像元生物量相关参数的求解问题。
It is an efficient and effective way to use microwave remote sensing methods for biomass estimation. Most used methods at present usually only make use of either phase information in establishing relationship between biomass related parameters and interfered phase values of image pairs, or to establish relation or amplitude information to reconstruct forest characters by taking forest as a whole uniformly distributed layer through which the microwave signals have traveled. They cannot make use of amplitude and phase information together to gain a specific description of interaction between trees and electromagnetic waves, thus when coming to the case of fractional areas of trees, which corresponding to mixing pixel in an image, these methods will not function well. For the methods employing amplitude information, although there are ways to describe the interaction progress in more detail, the models generated based on theories of electromagnetics, and are complicated with too many parameters to apply. For methods using phase information only, by introducing more interfermetric image pairs, parameter represent areas not fully covered be forest, but more images are required and accurate DEM is required for calculating tree heights. The method makes fully use of both amplitude and phase information while is simple enough for applications is target decomposition. This makes target decomposition can be used to solve the problem caused by incomplete description of mixing pixel, and suitable for biomass related parameter estimation.
Target decomposition is the method to analyze return signals represented in canonical scattering mechanisms, or summary of components whose values are unique, to get characters of objects. This kind of methods is a result of good cooperation of radiative transfer method and wave approach in reconstructing object properties. But main applications employing target decomposition is limited in classifying and recognition problems, and is not yet contributing to quantitive remote sensing applications.
Generally, there are specific target decomposition methods for different application background. The most suitable one for forest case is Freeman-Durden decomposition, which divide the interaction of forest areas with electromagnetic waves into three kinds of scattering. In the research of this PhD thesis, existed models gained by extracting scenes of forests are studied and main kinds of interactions, which occurs between electromagnetic waves and elements in those models involving fractional areas of forests, are selected and analyzed, and are matched to components of Freeman-Durden decomposition. Then by employing existed experience models and proper approximations forwarded by the author which relate results of those interactions and biomass related parameters, the three component are expressed in detail. Finally, equations with biomass related parameters and components of Freeman-Durden decomposition are established which form the model proposed in this thesis.
To make values of Freeman-Durden decomposition component more accurately gained for quantitive applications, first errors caused during decomposition by employing limited looks to estimate covariance matrix are analyzed, then data gained by simulation based on of Monte Carlo theories is used to find correction methods. Experiment shows that corrected component values are in better accordance with ground scenes.
The way in this thesis to retrieve model parameters is to employ simulated data generated by setting environments as similar as possible to application scene, including sensor parameters and type of forests. In this progress, under the condition of experiments in this thesis, the parameter representing change from other kind of scattering to volume scattering appears to be zero. Thus another stricter approach has been used to solve model parameters.
Finally, the proposed model is verified by comparing results got by applying it to quad-pol radar images and ground truth data. The corresponding areas of ground surveyed zone on images are gained by finding the place on optical data by GPS pad measured data, then match the optical data to radar images. For the restriction by ground truth data, averaged results are used for comparison. Although for one set of parameter can not be verified for the ground truth was not able to get, a qualitive analysis has been done for it, and its corresponding simulated data are of the same order of magnitude, this parameter can be taken as well generated from the model. Even if it cannot be accurately generated, since relation between it and other parameters which has been verified, this will not affect the performance of the model proposed. Results finally show that the model proposed can act with high accuracy for pixels whose Freeman-Durden decomposition component values can be gained directly from image data, while for those pixels whose values have to be changed due to existed Freeman-Durden decomposition progress to meet the condition of this decomposition. Thus in all, this model can generate good results and is suitable for solving mixing pixel biomass related parameter retrieving problems.
目标分解方法通过对全极化回波的分析,利用回波中各种“垂直”或者具有分量唯一性的散射类型分量来反推和电磁波作用的物体的性质,是分析电磁波和物体共同作用的辐射传输理论和波动理论的有机结合。但是目标分解方法现有的应用主要是解决分类识别问题,没有发挥其在定量遥感分析中的作用。
总的来说,针对不同应用背景的目标分解方法有多种,其中针对植被存在的方法是Freeman-Durden分解。这种分解方法通过三种散射来描述电磁波和植被的作用。本文对已有的抽象表示实际场景的模型进行研究,建立适于表示非均匀植被分布的场景模型,分析电磁波与抽象的植被元素之间的作用,将Freeman-Durden分解分量细化,提出模型公式,将三分量数值和选取的生物量相关参数之间对应起来。这个过程中利用了一些经验模型公式。在使用目标分解方法求解分量过程中,通过分析得到更详尽的表述过程,补足经验模型不能详尽描述电磁波和植被之间的作用过程的缺点。在分析分解分量的形成过程中,本文建立了生物量相关参数和分解分量之间的关系。
为了使Freeman-Durden分解的分量数值能更好地用于定量分析,作者对分解分量求解过程中由于使用有限视数(窗口数)而导致的误差进行了分析,寻找需要改正的分量,并借助Monte Carlo方法模拟数据,实现对需要修正分量的改正。通过实验证明,经过改正后的分解分量数据更符合实际情况。
本文中通过模拟软件获取一系列和实际应用的真实数据获取条件(传感器的工作波段、入射角以及实际场景的地表粗糙度、树木是针叶林还是阔叶林等情况)相似的植被覆盖量不同的模拟数据组,来求解模型参数。在本文实验中,求得的表示具有一定散射特性的回波通过冠层时转换为体散射的数值参数为零,因此不需要考虑这个作用过程。此时可以使用正文中叙述的更合理的方法重新求解模型参数。
最后使用本文提出的模型公式和求得的模型参数计算全极化雷达影像植被覆盖区域的生物量相关参数数值,将结果和相应区域的实测数据对比,验证模型的有效性。首先通过实地测量中的定向点找寻植被覆盖实验区域在光学影像的位置,然后通过光学影像和全极化雷达影像数据配准得到区域在雷达影像上的位置。由于测量条件的限制,通过比较测量区域中生物量相关参数的量测和计算平均值实现模型验证。结果表明,对于Freeman-Durden分解算法能直接求取分解分量数值的绝大多数像素,使用本文的生物量相关参数估算模型进行生物量相关参数计算结果精度很高,能满足实际应用的需要。虽然对于其中一个参数的求解无法精确定量地验证,对比它与模拟数据场景的对应数值,以及定性分析实际场景和求解数值的结果表明,这个参数的求解数值符合实际情况。此外这个参数也可以由可以验证的参数通过树木结构等先验知识求取,不影响模型使用的有效性。总的来说,本文的模型可以得到很好的结果,使用它进行生物量相关参数的估算可以解决混合像元生物量相关参数的求解问题。
It is an efficient and effective way to use microwave remote sensing methods for biomass estimation. Most used methods at present usually only make use of either phase information in establishing relationship between biomass related parameters and interfered phase values of image pairs, or to establish relation or amplitude information to reconstruct forest characters by taking forest as a whole uniformly distributed layer through which the microwave signals have traveled. They cannot make use of amplitude and phase information together to gain a specific description of interaction between trees and electromagnetic waves, thus when coming to the case of fractional areas of trees, which corresponding to mixing pixel in an image, these methods will not function well. For the methods employing amplitude information, although there are ways to describe the interaction progress in more detail, the models generated based on theories of electromagnetics, and are complicated with too many parameters to apply. For methods using phase information only, by introducing more interfermetric image pairs, parameter represent areas not fully covered be forest, but more images are required and accurate DEM is required for calculating tree heights. The method makes fully use of both amplitude and phase information while is simple enough for applications is target decomposition. This makes target decomposition can be used to solve the problem caused by incomplete description of mixing pixel, and suitable for biomass related parameter estimation.
Target decomposition is the method to analyze return signals represented in canonical scattering mechanisms, or summary of components whose values are unique, to get characters of objects. This kind of methods is a result of good cooperation of radiative transfer method and wave approach in reconstructing object properties. But main applications employing target decomposition is limited in classifying and recognition problems, and is not yet contributing to quantitive remote sensing applications.
Generally, there are specific target decomposition methods for different application background. The most suitable one for forest case is Freeman-Durden decomposition, which divide the interaction of forest areas with electromagnetic waves into three kinds of scattering. In the research of this PhD thesis, existed models gained by extracting scenes of forests are studied and main kinds of interactions, which occurs between electromagnetic waves and elements in those models involving fractional areas of forests, are selected and analyzed, and are matched to components of Freeman-Durden decomposition. Then by employing existed experience models and proper approximations forwarded by the author which relate results of those interactions and biomass related parameters, the three component are expressed in detail. Finally, equations with biomass related parameters and components of Freeman-Durden decomposition are established which form the model proposed in this thesis.
To make values of Freeman-Durden decomposition component more accurately gained for quantitive applications, first errors caused during decomposition by employing limited looks to estimate covariance matrix are analyzed, then data gained by simulation based on of Monte Carlo theories is used to find correction methods. Experiment shows that corrected component values are in better accordance with ground scenes.
The way in this thesis to retrieve model parameters is to employ simulated data generated by setting environments as similar as possible to application scene, including sensor parameters and type of forests. In this progress, under the condition of experiments in this thesis, the parameter representing change from other kind of scattering to volume scattering appears to be zero. Thus another stricter approach has been used to solve model parameters.
Finally, the proposed model is verified by comparing results got by applying it to quad-pol radar images and ground truth data. The corresponding areas of ground surveyed zone on images are gained by finding the place on optical data by GPS pad measured data, then match the optical data to radar images. For the restriction by ground truth data, averaged results are used for comparison. Although for one set of parameter can not be verified for the ground truth was not able to get, a qualitive analysis has been done for it, and its corresponding simulated data are of the same order of magnitude, this parameter can be taken as well generated from the model. Even if it cannot be accurately generated, since relation between it and other parameters which has been verified, this will not affect the performance of the model proposed. Results finally show that the model proposed can act with high accuracy for pixels whose Freeman-Durden decomposition component values can be gained directly from image data, while for those pixels whose values have to be changed due to existed Freeman-Durden decomposition progress to meet the condition of this decomposition. Thus in all, this model can generate good results and is suitable for solving mixing pixel biomass related parameter retrieving problems.
引文
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