浅层高分辨率反射地震试验研究：以雄安新区第四系为例

雄安新区城市规划建设对地下空间的高精度勘探提出了高要求,作为具有高分辨率的地面物探方法,反射波地震勘探技术具有良好应用前景。本文探究了厚覆盖区条件下的高精度有效反射地震探测技术,并利用反射纵波技术在雄安新区进行提高浅层分辨率的地震勘探方法试验。根据实际探测目标,通过对比分析不同检波器、震源类型、道距大小及接收排列长度等不同采集因素试验效果,探究已有条件下适宜的震源类型和最佳采集参数。结合实际资料处理和分层解释,试验研究表明,采用高频检波器、选择可控震源激发效果最佳,针对试验目标,结合小道距、适当排列接收等措施,可有效提高厚覆盖区50~300 m深度内反射纵波地震勘探的纵向分辨率,试验获得了丰富的有效波组信息,为内部地层精细划分和解释提供了依据。该方法可为类似环境下城市地下空间的精细探测提供有益参考借鉴。     

大型GNSS观测网的并行计算

CGCS2000精化及其全球拓展需要采用最新的模型,处理长期积累的大型GNSS观测网数据,大型GNSS网联合、快速和协同解算是空间基准精化、维持与服务的重要技术方向.在大数据技术背景下,以并行计算、云计算为代表的高性能计算技术逐渐成为大规模数据处理的首选方法.针对海量、多源、异构GNSS数据在解算处理与平差分析等方面面...     

Quantizing and analyzing the feature information of coastal zone based on high-resolution remote sensing image

1Introduction With the development and application of remotesensing technology, people fromthe international re-mote sensing community have realized the issue thatwe have immoderately emphasized characteristics ofvast volume data and great detail of remot…     

海洋天然气水合物调查地震采集技术——调查初始阶段研究

地震调查方法在水合物中的应用分为两个主要阶段:调查初始阶段和调查深入阶段。调查初始阶段以“突出天然气水合物的四大主要识别标志(似海底反射、振幅空白带、穿层特征、振幅和速度结构异常)”为主要目的,为资料的处理、解释提供丰富的地震信息。从而圈定天然气水合物富集程度高、成藏条件好的“目标”靶区,开展深入调查,更好地展现“天然气水合物矿体立体上的形态特征”,了解“水合物矿体的厚度、顶底界面及富集程度”。文中从震源技术研究、高分辨率地震调查技术的调谐组合参数研究和野外施工方法等方面的内容出发,根据大量野外技术试验资料和有关科研成果,总结了在天然气水合物调查初始阶段的特点及相应的地震调查技术。     

Variation characteristics of evaporation in the Gulang River Basin during 1959-2013

Based on monthly evaporation of two meteorological stations in the Gulang River Basin of China, the inter-annual variation of evaporation during 1959-2013 were analyzed using Mann-Kendall and wavelet analysis. The results demonstrated that the annual evaporation show a fluctuating increase over the past 50 years approximately, with an average increase rate of 4.26 mm per decade. The overall trend was decrease-increase-decrease. According to the cumulative anomaly curve,the turning point of the annual evaporation occurred in 1979, in which the evaporation increased in the early stage and decreased in the later stage. Meanwhile, the seasonal variation of the evaporation shows that it decreased in Spring and Autumn, and increased in Summer and Winter, especially obvious for the later. The evaporation abruptly changed in Spring and Summer in 2008 and in Winter in 1994. In addition, all evaporation increased after the changes. However,the evaporation in Autumn abruptly changed in 1986 and 1999, which show a trend of increase-decrease-increase.Wavelet analysis shows that evaporation in Summer and wet season would decrease in the next few years, and in the other seasons would increase. Based on the aforementioned analysis, it can be concluded that increased evaporation is mainly induced by increase of evaporation in dry season, especially in Winter, and this trend to be continued in the future for the Gulang River Basin.     

Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.     

北斗卫星类型间偏差快速改正分析

针对北斗卫星类型间偏差（ISTB）导致载波相位差分高精度定位（RTK）的整周模糊度无法固定问题,本文提出了改进ISTB快速改正方法,在观测量层面仅利用1组不同卫星类型的载波相位差分观测量即可实现ISTB估计与改正,实际应用中较传统方法更具普适性与简易性。该方法的测试结果表明,ISTB值由NH码调制不同引起,不同频点的ISTB值具有不一致性;此外,有无改正ISTB的北斗RTK性能对比反映了ISTB会严重降低整周模糊度固定与RTK定位性能。由此可知,本文方法能够保障现阶段北斗接收机更新换代过程中北斗RTK的高精度与高可靠性能。     

球面小波模型在GPS高程拟合中的应用

本文利用某地共99个GPS水准点的大地高和正常高求取高程异常,使用DOG球面小波模型和多面函数,分别对高程异常进行拟合。拟合时剔除模型残差大于2倍中误差的点,并在剔除粗差后重新进行拟合。通过比较外部检核点的已知高程异常值和球面小波模型值、多面函数拟合值之间的均方差评价模型的精度。数据结果表明,以外部检核均方差最小为准则,球面小波模型拟合精度较优,其拟合精度为1.65 cm,多面函数拟合精度为2.35 cm。     

基于高分遥感影像的建筑物侧面信息提取及其高度计算

本文选取成都市某一区域建筑物A、B为研究对象,采用分辨率为0.61 m的Quick bird影像,运用图像分割法和LVQ神经网络算法,提取建筑物侧面信息,根据假设法原理,构建高度计算物理模型,求取建筑物高度。对比实测数据,结合可能影响实验结果的实地因素、遥感影像因素进行精度分析与评价,探讨基于高分遥感影像的建筑物侧面信息提取和高度计算的方法。结果表明,LVQ神经网络算法在建筑物侧面提取和高度计算中有更好的应用价值,精度高达94%。     

基于多分辨率分析的GF-5和GF-1遥感影像空—谱融合

针对空间分辨率比率较大尺度差异下的高分五号(GF-5)与高分一号(GF-1)卫星影像的空—谱融合问题,提出多传感器影像融合策略:一方面,通过现有空—谱融合方法的分步融合得到融合影像;另一方面,在分步融合理论基础上,推导得出一体化融合基础框架,并进一步提出基于多分辨率分析的多传感器一体化融合方法,缓解现有方法因空间分辨率比率过大导致影像空、谱互补信息难以有效集成的问题。其中,提出的一体化融合方法基于调制传递函数MTF (Modulation Transfer Function)滤波对多传感器影像空间(高频)和光谱(低频)分量进行分解提取,并充分考虑多传感器高空间分辨率影像与高光谱分辨率影像之间的关系,以及高光谱分辨率影像波段间关系,设计合理的融合权重,最终可得到具有最高空间分辨率和最高光谱分辨率的融合影像。通过GF-1全色影像、GF-1多光谱影像、GF-5高光谱影像数据对提出方法进行实验验证,结果表明:本文方法可有效集成多传感器影像间的空、谱互补信息,得到较优融合结果。