On utilization ofa priori knowledge in inversion of remote sensing models

Satellite remote sensing deals with a complex system coupling atmosphere and surface. Any physical model with reasonable precision needs several to tens of parameters. Without a priori knowledge of these parameters, Proposition 3 of Verstraete et al. requires the number of independent observations to be greater than the number of unknown parameters. This requirement can hardly be satisfied even in the coming EOS era. As Tarantola pointed out, the inversion problems in geoscience are always underdetermined in some sense. In order to make good use of every kind of a priori knowledge for effectively extracting information from remote sensing observations, the right question to set is as follows:Given an imperfect model and a certain amount ofa priori information on model parameters, in which sense should one modify thea priori information, given the actual observation with noise?A priori knowledge of physical parameters can be presented in different ways such as physical limits, global statistical means and variance fora certain landcover type, or previous statistics and temporal variation of a specific target. When sucha priori knowledge can be expressed as joint probability density. Bayessian theorem can be used in the inversion to obtain posterior probability densities of parameters using newly acquired observations. There is no prerequirement on how many independent observations must be made, and the knowledge gained merely depends on the information content of the new observations. Some specific problems about knowledge accumulation and renewal are also discussed.     

基于无人机和卫星遥感影像的升金湖草滩植被地上生物量反演

湿地植被地上生物量是衡量湿地生态系统健康状况的重要指标,对于珍稀水禽越冬繁殖、全球碳循环、生态净化具有重要意义,是生态学与遥感解译的研究热点之一.针对于地上生物量的测算,卫星遥感数据覆盖范围广但其空间分辨率较低,无人机遥感数据空间分辨率高但采集范围小,同时受湿地面积、观测系统及外界环境等条件的影响,使得遥感影像地上生物量反演更加复杂和困难.本研究基于无人机和高分一号数据对升金湖草滩植被地上生物量反演进行研究,结合升金湖保护区4个样区无人机可见光影像与相应样区实测样本数据,建立地上生物量与可见光波段、多种可见光植被指数的线性、幂函数、多项式、对数回归模型,并通过可决系数（R²）、平均绝对误差（MAE）和均方根误差（RMSE）对模型进行精度评价,选择最优模型对无人机影像进行地上生物量反演;通过可见光波段反演得到的生物量,与高分一号WFV归一化差分植被指数（Normalized Difference Vegetation Index,NDVI）影像相结合进行回归建模,获取整个升金湖草滩植被地上生物量分布.结果表明,利用无人机红光波段建立的多项式方程对地上生物量反演有着最高模拟精度,R²=0.86、预测精度MAE=111.33 g/m²、RMSE=145.42 g/m²,且红光波段生物量反演方法得到的结果与实际生物量分布一致性较高,高分一号WFV NDVI与无人机反演生物量构建的多项式模型为最优模型,R²为0.91.本研究利用无人机和高分一号数据进行生物量反演研究,整合多源遥感数据优点,以获取更加丰富和准确的信息,进而提高地上生物量反演精度,为湿地监测和湿地恢复管理提供数据和技术支撑,具有重要研究意义和应用价值.     

Review of snow water equivalent microwave remote sensing

Accurate quantitative global scale snow water equivalent information is crucial for meteorology, hydrology, water cycle and global change studies, and is of great importance for snow melt-runoff forecast, water resources management and flood control. With land surface process model and snow process model, the snow water equivalent can be simulated with certain accuracy, with the forcing data as input. However, the snow water equivalent simulated using the snow process models has large uncertainties spatially and temporally, and it may be far from the needs of practical applications. Thus, the large scale snow water equivalent information is mainly from remote sensing. Beginning with the launch of Nimbus-7 satellite, the research on microwave snow water equivalent remote sensing has developed for more than 30 years, researchers have made progress in many aspects, including the electromagnetic scattering and emission modeling, ground and airborne experiments, and inversion algorithms for future global high resolution snow water equivalent remote sensing program. In this paper, the research and progress in the aspects of electromagnetic scattering/emission modeling over snow covered terrain and snow water equivalent inversion algorithm will be summarized.     

A new method for dynamic inversion of anisotropic equations

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磁化强度矢量反演方程及二维模型正反演研究

导了磁化强度矢量层析成像方程,并与磁化强度标量层析成像方程进行了对比. 使该矢量层析成像方程既适用于三维的也适用于二维,既适用于使用磁场垂直分量资料,也适用于使用磁场总强度资料. 本文采用改进的高斯-赛德尔迭代求解磁化强度矢量层析成像方程,在求解方程中引进了与深度有关的权系数. 并对二维模型开展了正反演研究. 当模型层数为二层,且每层51个柱体时,采用零初始模型就能获得较好的磁化强度垂直分量和水平分量反演结果,除了异常体边部外,磁化方向比较可靠. 当模型层数为五层,且每层51个柱体时,采用零初始模型不能得到较好结果,改用接近背景值的均匀初始模型,反演的磁化强度垂直分量和水平分量大致接近真实,但不能刻划某些细节.     

On MSDT inversion with multi-angle remote sensing data

With the wavelet transform, image of multi-angle remote sensing is decomposed into multi-resolution. With data of each resolution, we try target-based multi-stages inversion, taking the inversion result of coarse resolution as the prior information of the next inversion. The result gets finer and finer until the resolution of satellite observation. In this way, the target-based multi-stages inversion can be used in remote sensing inversion of large-scaled coverage. With MISR data, we inverse structure parameters of vegetation in semiarid grassland of the Inner Mongolia Autonomous Region. The result proves that this way is efficient.     

A PRELIMINARY STUDY ON THE METHOD OF SEISMIC INTENSITY ASSESSMENT BASED ON RESIDENTIAL BUILDING DATA AND HIGH RESOLUTION REMOTE SENSING IMAGES

After destructive earthquakes, the assessment result of seismic intensity is an important decision-making basis for emergency rescue, recovery and reconstruction. This job requires higher timeliness by government and society. Because remote sensing technology is not affected by the terrible traffic conditions on the ground after the earthquake, large-scale seismic damage information in the earthquake area can be collected in a short time by the remote sensing image. The remote sensing technique plays a more and more important role in rapid acquisition of seismic damage information, emergency rescue decision-making, seismic intensity assessment and other work. On the basis of previous studies, this paper proposes a new method to assess seismic intensity by using remote sensing image, i.e. to interpret the building collapse rate of a residential quarter after an earthquake by high-resolution remote sensing images. If there already are detailed building data and building structure vulnerability matrix data of a residential area, we can calculate the building collapse rate under any intensity values in this residential area by using the theory of earthquake damage prediction. Assuming that the building collapse rate interpreted by remote sensing is equal to the building collapse rate predicted by using the existing data, it will be easy to calculate the actual seismic intensity of the residential area in this earthquake event. Based on this idea, according to the relevant standard specifications issued by China Earthquake Administration, this paper puts forward some functional models, such as the calculation model of building collapse rate based on remote sensing, the data matrix model of residential building structure, the prediction function matrix model of residential building collapse rate and the prediction model of residential building collapse rate. A formula for calculating seismic intensity by using remote sensing interpretation of collapse rate is also proposed. To test and verify the proposed method, this paper takes two neighboring blocks of Jiegu Town after the Yushu M7.1 earthquake in Qinghai Province as an example. The building structure matrix of the study block was constructed by using pre-earthquake 0.6m resolution satellite remote sensing image(QuickBird, acquired on November 6, 2004), post-earthquake 0.2m aerial remote sensing image(acquired by National Bureau of Surveying and Mapping, April 15, 2010) and some field investigation data. The building collapse rate in the two blocks was calculated by using the interpretation results of seismic damage from the Remote Sensing Technology Coordinating Group of China Seismological Bureau. The seismic damage matrix of building structures in Yushu area is constructed by using the abundant scientific data of the scientific investigation team of the project “Comprehensive Scientific Investigation of the Yushu M7.1 Earthquake in Qinghai Province” of China Seismological Bureau. On this basis, the collapse rate prediction function of different structures in Yushu area is constructed. According to the prediction function of collapse rate and the building structure matrix of the two blocks, the building collapse rate under different intensity values is predicted, and the curve of intensity-collapse rate function is drawn. By comparing the building collapse rate interpreted by remote sensing and the intensity-collapse rate function curve of this two blocks, the seismic intensity of both blocks are calculated to be the same value: Ⅸ degree, which is consistent with the results of the field scientific investigation of the earthquake. The validation shows that the method proposed in this paper can effectively avoid the influence caused by the difference of seismic performance of buildings and accurately evaluate seismic intensity when using remote sensing technique. The method has certain application value for earthquake emergency work.     

变密度声波方程多参数全波形反演策略

多参数全波形反演中各参数之间的相互耦合增加了反演的非线性程度.通过分析各参数之间的相互影响,提出合理的多参数反演策略是解决该问题的有效途径.本文从变密度声波方程出发,首先研究了密度在速度反演中的重要作用,然后分析了速度对密度反演的影响程度,进而提出了一种有利于速度、密度分步联合反演的策略.第一步,利用给定的初始模型对速度、密度进行同时反演,得到比较可靠的速度反演结果;第二步,利用第一步反演得到的速度和给定的初始密度作为初始模型,继续进行双参数同时反演,这样可以同时得到比较可靠的速度、密度反演结果.为了进一步提高反演精度,将第二步反演得到的速度、密度作为初始模型,再进行下一轮双参数联合反演.二维理论模型实验结果充分说明了本文提出的这种反演策略的有效性.     

活动断裂调查中的高分辨率遥感技术应用方法研究

本文系统分析了高分辨率遥感在活动断裂调查中应用的技术现状、工作流程,梳理了各类遥感数据的要求、适用条件和处理方法,总结了活动断裂的遥感解译方法、解译要素和测量参数,并通过实例解析了一些典型的断错地貌,给出了相应的遥感特征. 基于资源三号卫星的立体像对和影像,判读了大青山活动断裂的几何特征和活动特性. 结果表明: 人工改造较大的地区宜收集早期遥感影像,利用不同波段间地物光谱的差异来增强隐伏活动断裂的信息,使用空间增强方法来识别断层陡坎等线性构造;雷达数据多极化分解是检测隐伏构造信息的有效方法;由宏观信息向局部信息追踪是活动断裂解译的有效途径;将遥感影像与数字高程模型(DEM)联合可进行活动断层参数的高精度测量. 本文结果可为活动断裂大比例尺、定量调查提供参考.      

Inversion of controlled‐source electromagnetic data using a model‐based approach

A two‐and‐half dimensional model‐based inversion algorithm for the reconstruction of geometry and conductivity of unknown regions using marine controlled‐source electromagnetic (CSEM) data is presented. In the model‐based inversion, the inversion domain is described by the so‐called regional conductivity model and both geometry and material parameters associated with this model are reconstructed in the inversion process. This method has the advantage of using a priori information such as the background conductivity distribution, structural information extracted from seismic and/or gravity measurements, and/or inversion results a priori derived from a pixel‐based inversion method. By incorporating this a priori information, the number of unknown parameters to be retrieved becomes significantly reduced. The inversion method is the regularized Gauss‐Newton minimization scheme. The robustness of the inversion is enhanced by adopting nonlinear constraints and applying a quadratic line search algorithm to the optimization process. We also introduce the adjoint formulation to calculate the Jacobian matrix with respect to the geometrical parameters. The model‐based inversion method is validated by using several numerical examples including the inversion of the Troll field data. These results show that the model‐based inversion method can quantitatively reconstruct the shapes and conductivities of reservoirs.     

The potential information in the temperature difference between shadow and sunlit of surfaces and a new way of retrieving the soil moisture

The thermal inertia and plant water stress index are often adopted to estimate soil moisture available for crops or plants. However, it is not very easy to obtain two temporal temperatures for thermal inertia model and air temperature for the plant water stress mode. Shadows of ground objects are often referred to noise on visible and near infrared remote sensing. But the difference of temperature between shadows and sunlit contains rich information concerning with heat-water status for soil. This paper presented a new way to excavate just by temperature difference usually between shadow and sunlit surface. Experiments validated the ideal. We can adopt thermal camera to measure the differences in the field measurements. However, we must use inversion based on multianglar thermal infrared remote sensing data in airborne and spaceborne. An inverting model was also presented by using Monte-Carlo and the least square method. Results show that this way is feasible.     

A kinematic‐wave‐based distributed watershed model using FEM,GIS and remotely sensed data

For the appropriate management of water resources in a watershed, it is essential to calculate the time distribution of runoff for the given rainfall event. In this paper, a kinematic‐wave‐based distributed watershed model using finite element method (FEM), geographical information systems (GIS) and remote‐sensing‐based approach is presented for the runoff simulation of small watersheds. The kinematic wave equations are solved using FEM for overland and channel flow to generate runoff at the outlet of the watershed concerned. The interception loss is calculated by an empirical model based on leaf area index (LAI). The Green‐Ampt Mein Larson (GAML) model is used for the estimation of infiltration. Remotely sensed data has been used to extract land use (LU)/land cover (LC). GIS have been used to prepare finite element grid and input files such as Manning's roughness and slope. The developed overland flow model has been checked with an analytical solution for a hypothetical watershed. The model has been applied to a gauged watershed and an ungauged watershed. From the results, it is seen that the model is able to simulate the hydrographs reasonably well. A sensitivity analysis of the model is carried out with the calibrated infiltration parameters, overland flow Manning's roughness, channel flow Manning's roughness, time step and grid size. The present model is useful in predicting the hydrograph in small, ungauged watersheds. Copyright © 2007 John Wiley & Sons, Ltd.     

基于可视化遥感的地震大区域灾情收集系统

地震现场与一般灾害现场不同,其受灾区域较大,常规的基于遥感信息进行灾情收集时,采集信息零散混乱无法形成可视化直观分析结果。为解决该问题,设计基于可视化遥感技术的地震大区域灾情收集系统,利用遥感信息采集大区域的优势,配合设计网络通信层、数据收集层、数据库层、GIS遥感平台层和应用层组成的系统硬件,采用GIS三维重构技术,对灾情进行可视化呈现。实验结果说明,系统最长响应时间为1.857 s,最大CPU占用率和消耗分别是80.8%和1 656 MB,信息可视化重现程度高。     

Application of ensemble kalman filter to geophysical parameters retrieval in remote sensing:A case study of kernel-driven BRDF model inversion

Remote sensing can provide multi-spatial resolution, multi-temporal resolution multi-spectral band and multi-angular data for the observation of land surface. At present, one of research focuses is how to make the best of these data to retrieve geophysical parameters in conjunction with their a priori knowledge and simul-taneously consider the influence of data uncertainties on inversion results[1-5]. The essence of remote sensing lies in inversion. It is difficult to precisely retrieve parame…     

基于非结构双网格的2D RMT双参数同步反演研究

Radio-magnetotelluric(RMT)是以无线电发射机为信号源的一种地球物理勘探方法,近年来被广泛应用于数米至数十米内的近地表工程和环境地球物理勘探.目前,各类电磁资料的反演均是以寻求满足目标拟合差的地下介质电阻率分布为目的.然而,对于勘探频率为10~300kHz的RMT数据,由介电常数所引起的波动场在总场中的比例可达20%以上,在这种情况下,忽略介电常数,仅通过电阻率参数的反演来进行数据拟合势必降低反演资料解释的准确性.为解决这一问题,本文研究了基于电阻率-介电常数的双参数同步反演算法.构建了一个全新的双参数目标函数,并推导了双参数反演迭代方程组;通过灵敏度分析,研究了电阻率和介电常数对正演响应的影响,并据此提出相对电导率的概念,统一了反演参数的灵敏度;通过理论模型分析了参考频率、双参数正则化因子对反演结果的影响,并给出了一般性的参数优选方案.此外,为了能够灵活处理复杂地形,本文采用非结构的正反演双网格进行模型离散,并通过局部加密技术保证反演的速度和精度.最后,对一带地形的理论模型分别进行了单参数和双参数反演,结果表明单参数反演无法正确反映出地电信息,而双参数反演能够准确得到异常的分布,验证了本文所开发的双参数反演程序的有效性.     

基于GPU并行的时间域全波形优化共轭梯度法快速GPR双参数反演

探地雷达（GPR）时间域全波形反演计算量巨大,内存要求高,在微机上计算难度大.本文中作者基于GPU并行加速的维度提升反演策略,采用优化的共轭梯度法,避免了Hessian矩阵的计算,在普通微机上实现了时间域全波形二维GPR双参数（介电常数和电导率）快速反演.论文首先推导了二维TM波的时域有限差分法（FDTD）的交错网格离散差分格式及波场更新策略.然后,基于Lagrange乘数法,将约束问题转化为无约束最小问题,构建了共轭梯度法反演目标函数,采用Fletcher-Reeves公式与非精确线搜索Wolfe准则,确保了梯度方向修正因子及迭代步长选取的合理性.而GPU并行计算及维度提升反演策略的应用,数倍地提升了反演速度.最后,开展了3个模型的合成数据的反演实验,分别从观测方式、梯度优化及天线频率等方面,分析了这些因素对雷达全波形反演的影响,说明双参数的反演较单一的介电常数反演,能提供更丰富的信息约束,有效提高模型重建的精度.     

一种高效的基于交叉梯度结构约束的三维地震走时与直流电阻率联合反演策略

基于交叉梯度结构约束的不同数据的联合反演可以提高地球物理成像的可靠度,但是由于不同观测数据对地下介质的灵敏度不同以及不同反演系统灵敏度矩阵元素的数值可能存在较大的差异,导致构建和求解联合反演系统存在很大的挑战.针对以上问题,本文提出一种新的基于单独反演模型更新量与交叉梯度结构约束相结合的联合反演策略.该策略利用单独反演系统分别确定出各个模型的更新量,然后利用它们约束交叉梯度系统的反演,得出新的模型更新量.通过这样的方式,有效实现了数据拟合与结构约束的平衡,实现了基于交叉梯度联合反演的目标.新的联合反演策略不需要对原来单独反演程序修改即可实现联合反演,减小了联合反演实现的难度,极大地提高了联合反演的易实现性,而且避免了联合反演矩阵存储及结构过于复杂难以求解的问题.基于新的策略,本文首次实现了基于交叉梯度结构约束的三维地震走时与直流电阻率联合反演.合成模型测试表明,与单一成像相比,联合成像减少了地震走时反演中出现的干扰异常并提高了电阻率反演的分辨率.     

基于地质统计先验信息的储层物性参数同步反演

本文提出的储层物性参数同步反演是一种高分辨率的非线性反演方法,该方法综合利用岩石物理和地质统计先验信息,在贝叶斯理论框架下,首先通过变差结构分析得到合理的变差函数,进而利用快速傅里叶滑动平均模拟算法（Fast Fourier TransformMoving Average,FFT-MA）和逐渐变形算法（Gradual Deformation Method,GDM）得到基于地质统计学的储层物性参数先验信息,然后根据统计岩石物理模型建立弹性参数与储层物性参数之间的关系,构建似然函数,最终利用Metropolis算法实现后验概率密度的抽样,得到物性参数反演结果。并将此方法处理了中国陆上探区的一块实际资料,本方法的反演结果具有较高的分辨率,与测井数据吻合度较高;由于可以直接反演储层物性参数,避免了误差的累积,大大减少了不确定性的传递,且计算效率较高。     

基于空变阻抗约束的贝叶斯稀疏脉冲反演

常规的基于贝叶斯理论的稀疏脉冲反演中,各约束项的拉格朗日算子均采用的是恒定的常系数。反演实际资料发现,波阻抗反演剖面与钻井资料的油气显示并不能很好地对应。考虑到反演不同地震道数据时,低频趋势模型所起的约束作用应当不同。本文在常规反演的基础上做出了改进,假定阻抗约束系数是一个空间变量,由各地震道的实际地震数据与合成记录之间的振幅残差来确定该道的阻抗约束系数。实际资料应用表明,改进后的反演结果更稳定,能更准确地反映地下阻抗信息。