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汶川地震发生后,受阴雨天气的影响,光学遥感影像在救灾决策中的作用受到了很大的限制,而SAR图像由于其全天候的特点成为这次抗震救灾前期遥感信息保障十分重要的数据源.采用ENVISAT的ASAR作为数据源,利用多时相的雷达数据的幅度及相位信息对映秀及周边地区做了地震灾害识别,其中利用震前震后的幅度图像做比值变化检测,在映秀镇及紫坪铺水库等山区取得了较好的效果;利用相位信息做干涉处理得到的相干图像,经过失相干分析,发现建筑物的破坏等级与相干系数变化指数的大小高度相关.比较这两种方法,在都江堰等平原地区由于失相干现象不像山区那么严重,并且利用比值处理可以去除部分空间失相干及系统热噪声等带来的干扰因素,可以成为幅度图像的有益补充.结果表明,结合SAR幅度影像和干涉相干影像,可以在地震灾害评估中取得更好效果.随着极化干涉雷达技术的日益成熟,多时相幅度信息、相位信息等多特征SAR影像信息的融合会在救灾决策中发挥更大的作用. 相似文献
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《中国科学:地球科学(英文版)》2015,(1)
The Geoscience Laser Altimeter System(GLAS)accurately detects the vertical structural information of a target within its laser spot and is a promising system for the inversion of structural features and other biophysical parameters of forest ecosystems.Since the GLAS footprints are discontinuously distributed with a relativity low density,continuous vegetation height distributions cannot be mapped with a high accuracy using GLAS data alone.The MODIS BRDF product provides more forest structural information than other optical remote sensing data.This study aimed to map forest canopy heights over China from the GLAS and MODIS BRDF data.Firstly,the waveform characteristic parameters were extracted from the GLAS data by the method of wavelet analysis,and the terrain index was calculated using the ASTER GDEM data.Secondly,the model reducing the topographic influence was constructed from the waveform characteristic parameters and terrain index.Thirdly,the final canopy height estimation model was constructed from the neural network combining the canopy height estimated with the GLAS point and the MODIS BRDF data,and applied to get the continuous canopy height map over China.Finally,the map was validated by the measured data and the airborne Li DAR data,and the validation results indicated that forest canopy heights can be estimated with high accuracy from combined GLAS and MODIS data. 相似文献
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The technique of seismic amplitude-versus-angle inversion has been widely used to estimate lithology and fluid properties in seismic exploration. The amplitude-versus-angle inversion problem is intrinsically ill-posed and generally stabilized by the use of L2-norm regularization methods but with drawback of smoothing important boundaries between adjacent layers. In this study, we propose a sparse Bayesian linearized solution for amplitude-versus-angle inversion problem to preserve the sharp geological interfaces. In this regard, a priori constraint term with two regularization functions is presented: the sparse constraint regularization and the low-frequency model information. In addition, to obtain high-resolution reflectivity estimation, the model parameters decorrelation technique combined with dipole decomposition method is employed. We validate the applicability of the presented method by both synthetic and real seismic data from the Gulf of Mexico. The accuracy improvement of the presented method is also confirmed by comparing the results with the commonly used Bayesian linearized amplitude-versus-angle inversion. 相似文献
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在已有研究成果的基础上,为了适应物性参数剧烈变化的复杂模型并满足联合反演的要求,开发了速度和电阻率随机分布共网格单元模型的建模技术.基于这种统一的物性随机分布的网格介质模型,利用有限元方法和改进的射线追踪法分别正演计算大地电磁场和地震走时,结合改进的模拟退火算法,研究实现了电阻率和速度随机分布条件下的大地电磁与地震资料的同步联合反演.对物性界面不完全一致和物性变化剧烈的带地形复杂模型的试验,表明了该方法在精细反演复杂电阻率和速度结构方面的效果,克服了以往研究局限于简单模型的不足.对地震资料品质差的地区开展的实际资料联合反演,表明了方法的适用性,先验信息约束下的联合反演提高了反演精度. 相似文献
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1 Introduction Thermal inertia is a bulk property that shows the re- sistance of a material to an input or output of heat. This plays a very important role in certain geological and hydrological studies, and climate modeling. In the 1970s, a simple thermal inertia model was proposed by Watson et al.[1―3]. Pratt (1979)[4] improved the thermal inertia model based on application tests where more factors were considered such as solar ra- diance, thermal conductivity effect, average humidity of g… 相似文献
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In order to couple spatial data from frequency‐domain helicopter‐borne electromagnetics with electromagnetic measurements from ground geophysics (transient electromagnetics and radiomagnetotellurics), a common 1D weighted joint inversion algorithm for helicopter‐borne electromagnetics, transient electromagnetics and radiomagnetotellurics data has been developed. The depth of investigation of helicopter‐borne electromagnetics data is rather limited compared to time‐domain electromagnetics sounding methods on the ground. In order to improve the accuracy of model parameters of shallow depth as well as of greater depth, the helicopter‐borne electromagnetics, transient electromagnetics, and radiomagnetotellurics measurements can be combined by using a joint inversion methodology. The 1D joint inversion algorithm is tested for synthetic data of helicopter‐borne electromagnetics, transient electromagnetics and radiomagnetotellurics. The proposed concept of the joint inversion takes advantage of each method, thus providing the capability to resolve near surface (radiomagnetotellurics) and deeper electrical conductivity structures (transient electromagnetics) in combination with valuable spatial information (helicopter‐borne electromagnetics). Furthermore, the joint inversion has been applied on the field data (helicopter‐borne electromagnetics and transient electromagnetics) measured in the Cuxhaven area, Germany. In order to avoid the lessening of the resolution capacities of one data type, and thus balancing the use of inherent and ideally complementary information content, a parameter reweighting scheme that is based on the exploration depth ranges of the specific methods is proposed. A comparison of the conventional joint inversion algorithm, proposed by Jupp and Vozoff ( 1975 ), and of the newly developed algorithm is presented. The new algorithm employs the weighting on different model parameters differently. It is inferred from the synthetic and field data examples that the weighted joint inversion is more successful in explaining the subsurface than the classical joint inversion approach. In addition to this, the data fittings in weighted joint inversion are also improved. 相似文献
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地面磁共振法(MRS)因具有定性、定量分析地下水能力,而备受关注.传统磁共振地层含水量反演多采用均匀半空间模型,忽略电阻率分布信息对结果的影响.针对这一问题,本文基于多层电介质中磁共振响应理论,提出MRS与瞬变电磁(TEM)联合反演方法,通过电阻率分布信息对含水量反演过程的实时修正,提高了解释结果的准确度.反演算法采用自适应遗传算法(AGA)进行,基于繁殖规则,动态调整交叉概率和变异概率,解决了标准遗传算法易未成熟收敛而难以得到全局最优解问题.模型数据表明,含噪10%情况下,联合反演仍能较准确地反映地下含水单元模型结构,对比MRS单独反演优势明显.同时,内蒙古白旗野外观测数据联合反演结果与钻井资料基本一致,充分验证了AGA反演算法的实用性及MRS-TEM联合反演的实际意义. 相似文献
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对流层延迟是全球导航卫星系统(Global Navigation Satellite System,GNSS)导航定位中的重要误差源,其量值主要受气象条件影响.采用传统对流层建模思路,利用GPT2模型来提供相对准确的气温、气压和相对湿度,然后利用Saastamoinen模型来计算天顶对流层延迟,由此构建了GPT2+Saas模型;采用新的对流层建模思路,直接针对天顶对流层延迟的时空特性建模,构建了与GPT2+Saas模型相匹配的GZTDS格网模型.以GGOS Atmosphere格网数据为参考,GPT2+Saas模型(Bias:0.2cm;RMS:4.2cm)和GZTDS模型(Bias:0.2cm;RMS:3.7cm)较UNB3m模型精度分别提升34%和43%.以IGS(International GNSS Service)数据为参考,GPT2+Saas(Bias:0.5cm;RMS:4.7cm)和GZTDS(Bias:-0.3cm;RMS:3.8cm)相对UNB3m模型精度分别提升10%和27%.针对GPT2+Saas模型在少数测站出现精度异常的情况进行了研究,探讨了可能的原因.在两种不同思路构建的精化对流层模型中,GZTDS模型不仅表现出更高的精度,而且在时间稳定性和地理稳定性上也表现出优越性. 相似文献
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ZHOU Xuan YANG XiaoFeng LI ZiWei YU Yang BI HaiBo MA Sheng LI XiaoFeng 《中国科学:地球科学(英文版)》2013,56(11):1977-1987
The traditional method of Synthetic Aperture Radar(SAR)wind field retrieval is based on an empirical relation between the near surface winds and the normalized radar backscatter cross section to estimate wind speeds,where this relation is called the geophysical model function(GMF).However,the accuracy rapidly decreases due to the impact of rainfall on the measurement of SAR and the saturation of backscattered intensity under the condition of tropical cyclone.Because of no available instrument synchronously monitoring rain rate on the satellite platform of SAR,we have to derive the precipitation of the SAR observation time from non-simultaneous passive microwave observations of rain in combination with geostationary IR images,and then use the model of rain correction to remove the impact of rain on SAR wind field measurements.For the saturation of radar backscatter cross section in high wind speed conditions,we develop an approach to estimate tropical cyclone parameters and wind fields based on the improved Holland model and the SAR image features of tropical cyclone.To retrieve the low-to-moderate wind speed,the wind direction of tropical cyclone is estimated from the SAR image using wavelet analysis.And then the maximum wind speed and the central pressure of tropical cyclone are calculated by a least square minimization of the difference between the improved Holland model and the low-to-moderate wind speed retrieved from SAR.In addition,wind fields are estimated from the improved Holland model using the above-mentioned parameters of tropical cyclone as input.To evaluate the accuracy of our approach,the SAR images of typhoon Aere,typhoon Khanun,and hurricane Ophelia are used to estimate tropical cyclone parameters and wind fields,which are compared with the best track data and reanalyzed wind fields of the Joint Typhoon Warning Center(JTWC)and the Hurricane Research Division(HRD).The results indicate that the tropical cyclone center,maximum wind speed,and central pressure are generally consistent with the best track data,and wind fields agree well with reanalyzed data from HRD. 相似文献
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光滑地面毁伤程度评估非常重要，目前评估方法主要是基于光学图像，可是在恶劣的气候或环境条件下，很难获得光学图像，合成孔径雷达（SAR）克服了这个缺点. SAR图像是地表结构和电特征等地球物理参数的映射，通过SAR图像反演地表结构参数，可以推测出光滑地面毁伤程度. 本文以几何光学模型（GOM）为基础，建立神经网络反演模型，以获得光滑地表面受损后的粗糙度参数：表面均方根高度（σ）和表面相关长度（l），并进一步评估光滑地表面受损程度. 实验结果表明该方法可行. 相似文献
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ZHANG Renhua WANG Jinfeng ZHU Caiying SUN Xiaomin & ZHU Zhilin .Institute of Geographical Sciences Natural Resources Chinese Academy of Sciences Beijing China .Institute of Surveying Mapping Information Engineering University of the Chinese People''''s Liberation Army Zhengzhou China 《中国科学D辑(英文版)》2004,47(12):1134-1146
The research for the land surface fluxes has madea quiet great progress for its breakthroughs in the fieldof regional or global interactions between land surfaceand atmosphere. However, many remote sensing mod-els for estimating the land surface fluxes need the pa-rameters of surface momentum, heat, resistance ofwater vapor at a referenced height, which are the func-tion of aerodynamic surface roughness zad. It hasbeen validated that the retrieval of the land surfacefluxes is very sensitive to… 相似文献
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叶面积指数(LAI)是分析冠层结构最常用的参数之一,它控制着植被的生物物理过程,如光合、呼吸、蒸腾、碳循环和降水截获等,因此快速、可靠和客观地评价LAI非常重要.本文发展了激光穿透指数(LPI)的简化计算方法,首次利用校正后的回波强度计算出LPI,以LPI为变量基于Beer-Lambert定律实现了甘肃大野口研究区森林LAI反演,并且与原始回波强度和回波数反演LAI的精度进行对比,结果发现通过距离和角度校正后的回波强度值能提高LAI反演精度.为了评价模型的可靠性和泛化性能,用留一法交叉验证程序(LOOCV)对最佳反演模型进行了验证,表明该模型没有过度拟合,具有很好的泛化能力.最后,用没有参加建模的16个实测LAI对预测值进行精度验证(R2=0.810,RMSE=0.198),发现校正后的回波强度反演山区森林LAI精度较高.本文还对激光雷达LAI反演结果与传统光学TM影像的反演结果进行了对比分析,结果表明机载激光雷达反演LAI精度(R2=0.825,RMSE=0.165)高于光学TM遥感数据(R2=0.605,RMSE=0.257),因此,可用激光雷达数据实现研究区的高精度LAI反演,为生态环境研究提供可靠的基础数据. 相似文献
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Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
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地球物理反问题线性化处理之后, 各种反演算法归结为对病态线性方程组的求解. 为了快速准确地计算出地球物理参数, 本文提出了一种全新的基于LSQR算法的混合差分进化算法(Hybrid Differential Evolution Algorithm, HDE). 该算法利用LSQR算法给出DE算法的初始种群, 提高DE算法的计算速度和稳定性. 在不同噪声水平下, 对四种正则化方法Tikhonov、TSVD、LSQR和HDE的反演结果进行详细比较. 理论模型和实际数据反演的结果都表明: 改进的HDE算法应用于地球物理反问题的求解是成功的: 反演结果与原设定模型具有较高的相关性, 在稳定性和准确性上较常规的反演算法都具有一定的优势; 而且不需要给定正则化参数, 具有更强的实用性. 相似文献
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Hao Zhang XiaoWen Li ChunXiang Cao Hua Yang MengXu Gao Sheng Zheng Min Xu DongHui Xie HuiCong Jia Wei Ji Jian Zhao Wei Chen XiLiang Ni 《中国科学:地球科学(英文版)》2010,53(1):92-98
The spatial distribution of sub-pixel components has an impact on retrieval accuracy, and should be accounted for when inverting a three-dimensional adiative transfer model to retrieve leaf area index (LAI). To investigate this effect, we constructed three realistic scenarios with the same LAI values and other properties, except that the simulated plants had different distributions. We implemented the radiosity method to subsequently produce synthetic bidirectional reflectance factor (BRF) datasets based upon these simulated scenes. The inversion was conducted using these data, which showed that spatial distribution affects retrieval accuracy. The inversion was also conducted for LAI based on charge-coupled device (CCD) data from the Environment and Disaster Monitor Satellite (HJ-1), which depicted both forest and drought-resistant crop land cover. This showed that heterogeneity in coarse-resolution remote sensing data is the main error source in LAI inversion. The spatial distribution of global fractal dimension index, which can be used to describe the area of sub-pixel components and their spatial distribution modes, shows good consistency with the coarse resolution LAI inversion error. 相似文献
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基于随机森林的内陆湖泊水体有色可溶性有机物(CDOM)浓度遥感估算 总被引：3，自引：0，他引：3
水体中的有色可溶性有机物(CDOM)是湖泊生态系统中氮、磷等有机营养物质的重要来源,利用卫星遥感数据反演内陆水体中CDOM浓度一直是个挑战.因此本文基于滇池2009年9月、2017年4月以及太湖2016年7月的现场原位观测和室内实验,在分析水体固有光学特性的基础上,引入机器学习算法,建立了基于哨兵-3A OLCI传感器的我国内陆湖泊水体CDOM浓度随机森林反演模型.利用独立的验证数据集对所构建的随机森林模型及常用的波段比值模型、一阶微分模型、半分析模型、BP神经网络模型等的反演精度进行评价.结果表明:随机森林模型的均方根误差为0.14 m-1,平均相对误差为21%,与反演效果相对较好的BP神经网络模型相比,均方根误差降低了50%,平均相对误差降低了38%,反演精度得到了显著的提高.根据随机森林算法的特征重要性参数提供的各自变量影响力结果,发现B11(709 nm)和B6(560 nm)波段贡献率最大,是反演CDOM的敏感波段.最后将随机森林模型应用到滇池2017年4月12日、太湖2017年5月18日的哨兵-3A OLCI影像上,得到滇池、太湖水体CDOM浓度分布图.滇池CDOM浓度的分布特征大致符合东北、西南高,中西部低的趋势,且河口处的CDOM浓度高于湖泊水体,表明径流的输入给滇池水体带来了大量的CDOM.太湖CDOM浓度的分布特征大致符合西部高,湖心区和东部低的趋势.太湖西部以及北部梅梁湾受入湖河流影响较大,CDOM浓度较高,太湖开敞区远离河口处,受外源河流的影响逐渐减小,且由于湖水的不断稀释,CDOM浓度不断降低.太湖东部水生植物很多,湖水较为清澈,CDOM浓度较低. 相似文献
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针对重力与地震联合反演存在的问题,结合已有的研究成果,本文研究实现了速度和密度随机分布共网格单元模型的建模技术,以适应密度和速度剧烈变化的复杂模型及联合反演的计算要求.重力正演利用了该网格的二度半体模型,并进一步改进了地震走时的二维射线追踪计算方法,以适用于速度随机分布的网格介质.结合改进的模拟退火算法,实现了这种共网格条件下的重力与地震资料的同步联合反演.模型试验证明了重力与地震联合反演可以准确确定复杂物性界面的密度和速度结构,适用于物性界面不完全一致和物性变化剧烈的复杂模型,并且联合反演结果要优于单独的重力反演.带先验信息约束下的实际资料的联合反演,进一步证明了该方法的适用性和效果,可提高反演精度并减少多解性. 相似文献
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针对InSAR技术在形变监测领域中的应用,本文从分析D-InSAR的干涉机理对其约束条件出发,重点研究空间去相关和形变梯度这两个关键指标对形变信息提取的影响.研究针对不同系统参数的传感器来展开,并论证这两个因素对干涉测量的限制.本文的创新性工作主要集中在以下几个方面: (1)分析了各传感器参数下的临界坡度范围,进而确立了SAR传感器监测的无信息区域;(2)证明了在植被覆盖区,相干性分解必须考虑体散射分量,并依此对模型进行了修正;(3)明确了形变梯度与相位梯度的差异以及两者的函数关系,并将入射角引入形变梯度函数模型.(4)通过模拟数据和真实数据比较各传感器在不同条件下形变监测的优缺点,在统计分析的基础上进一步验证结论.本文的研究是对干涉测量条件的进一步补充,对于理解干涉成像机理、完善InSAR数值计算模型(形变梯度模型和相干性分解模型)以及帮助研究人员根据研究区域特征选择合适的InSAR数据具有一定的参考价值. 相似文献