部分参数有非负约束平差模型的一种新算法

研究了部分参数带有非负约束的平差模型,提出了一种新的处理部分参数附有非负约束的平差方法。该方法是先将非负约束的最小二乘问题转换成凸二次规划问题,然后求其最优解。通过模拟实例说明,此算法可以很好地应用于实际测量中的平差计算。     

基于系统模型的CCD图像MTF补偿及误差分析

航天线阵推扫CCD图像在获取、传输过程中存在图像模糊的现象,而MTF是评价CCD图像质量的最可靠指标。为了改善图像质量,通过分析影响MTF的主要因素,提出基于系统模型的MTF补偿方法:首先建立系统模型,提出模型参数的估计方法,然后结合约束最小二乘算法复原图像。在仿真实验中,模拟图像的模糊和加噪过程,利用MTF模型复原图像,并评价MTF补偿图像质量,定量分析模型参数估计误差对图像复原结果的影响。实验结果表明:基于系统模型的MTF补偿方法能够有效而简便地复原图像,提高图像质量。     

A new method for specular and diffuse pseudorange multipath error extraction using wavelet analysis

Multipath remains one of the major challenges in Global Navigation Satellite System (GNSS) positioning because it is considered the dominant source of ranging errors, which can be classified into specular and diffuse types. We present a new method using wavelets to extract the pseudorange multipath in the time domain and breaking it down into the two components. The main idea is an analysis-reconstruction approach based on application of both continuous wavelet transform (CWT) and discrete wavelet transform (DWT). The proposed procedure involves the use of L1 code-minus-carrier (CMC) observable where higher-frequency terms are isolated as residuals. CMC residuals are analyzed by applying the CWT, and we propose the scalogram as a technique for discerning time–frequency variations of the multipath signal. Unlike Fourier transform, the potential of the CWT scalogram for examining the non-stationary and multifrequency nature of the multipath is confirmed as it simultaneously allows fine detection and time localization of the most representative frequencies of the signal. This interpretation of the CWT scalogram is relevant when choosing the levels of reconstruction with DWT, allowing accurate time domain extraction of both the specular and diffuse multipath. The performance and robustness of the method and its boundary applicability are assessed. The experiment was carried out using a receiver of Campania GNSS Network. The results are given in which specular multipath error is achieved using DWT level 7 approximation component and diffuse multipath error is achieved using DWT level 6 denoised detail component.     

A spatial error model with continuous random effects and an application to growth convergence

We propose a spatial error model with continuous random effects based on Matérn covariance functions and apply this model for the analysis of income convergence processes (\(\beta \)-convergence). The use of a model with continuous random effects permits a clearer visualization and interpretation of the spatial dependency patterns, avoids the problems of defining neighborhoods in spatial econometrics models, and allows projecting the spatial effects for every possible location in the continuous space, circumventing the existing aggregations in discrete lattice representations. We apply this model approach to analyze the economic growth of Brazilian municipalities between 1991 and 2010 using unconditional and conditional formulations and a spatiotemporal model of convergence. The results indicate that the estimated spatial random effects are consistent with the existence of income convergence clubs for Brazilian municipalities in this period.     

基于等高线重构误差的LOD建模及精度分析

本文运用等高线重构误差模型对细节层次模型(LOD模型)不同层次之间的精度进行研究。选取5种典型地貌区域进行试验,得到了不同地貌区域的重构误差拟合公式。根据得到的公式,可内插得到各种分辨率比率的重构误差。同时,利用逆公式,又能由重构误差确定相应的分辨率比率,为评价LOD模型精度提供了一种新的方法和思路。     

A general framework for error analysis in measurement-based GIS Part 1: The basic measurement-error model and related concepts

This is the first of a four-part series of papers which proposes a general framework for error analysis in measurement-based geographical information systems (MBGIS). The purpose of the series is to investigate the fundamental issues involved in measurement error (ME) analysis in MBGIS, and to provide a unified and effective treatment of errors and their propagation in various interrelated GIS and spatial operations. Part 1 deals with the formulation of the basic ME model together with the law of error propagation. Part 2 investigates the classic point-in-polygon problem under ME. Continuing to Part 3 is the analysis of ME in intersections and polygon overlays. In Part 4, error analyses in length and area measurements are made. In this present part, a simple but general model for ME in MBGIS is introduced. An approximate law of error propagation is then formulated. A simple, unified, and effective treatment of error bands for a line segment is made under the name of covariance-based error band. A new concept, called maximal allowable limit, which guarantees invariance in topology or geometric-property of a polygon under ME is also advanced. To handle errors in indirect measurements, a geodetic model for MBGIS is proposed and its error propagation problem is studied on the basis of the basic ME model as well as the approximate law of error propagation. Simulation experiments all substantiate the effectiveness of the proposed theoretical construct.This project was supported by the earmarked grant CUHK 4362/00H of the Hong Kong Research grants Council.     

一种新的时间序列变点算法在变形数据分析中的应用

本文在传统的变点分析理论的基础上,针对传统变点处理的方法,提出利用自适应神经网络,在原时间序列的基础上,适当选择滚动窗口的长度d和窗口每次移动的间隔为n0,形成新的序列作为自适应神经网络的输入,对新序列进行分类,得到变点个数和位置,在此基础判断变点的类型。本文用模拟数据和实测滑坡三维变形数据和坝体变形数据对算法的有效性进行了检验。     

膨胀卷积与金字塔表达的深度学习模型用于农村建筑物提取

由于农村建筑物结构多样、空间分布复杂等特征,自动提取面临较多困难。针对该问题,本文提出采用膨胀卷积和金字塔池化表达的神经网络模型用于遥感影像中农村建筑物自动提取。在膨胀卷积神经网络模块中,通过改变孔尺寸的大小,获取不同感受野的特征信息;在金字塔表达方面,每个模块输入不同尺度的信息,且同时下采样的倍率也不同,获取多维的金字塔尺度特征;最终将提取的浅层及深层尺度特征信息进行融合,构建一个改进的适用于农村建筑物目标自动提取的深度学习模型。试验结果表明,与FCN-8s和DeepLab模型提取的结果相比,本文方法在农村建筑物提取中表现较好的性能,提取精度明显提高,且更好保留了目标边界细节信息,减少了噪声。     

利用分裂窗算法提取晴空导风示踪物的数值模拟与应用

气象卫星热红外通道能够探测到晴空区域内由大气水汽、沙尘气溶胶等物质含量分布不均所导致的微弱的纹理信息,通过追踪水汽和沙尘气溶胶纹理的移动可以反演出风场。然而这些信号很容易受地表温度变化的影响,需使用合适的算法来减弱地表温度干扰、提取微弱的示踪物信号。本文结合分裂窗差值理论,对使用分裂窗差值算法提取晴空区微弱示踪物信号进行数值模拟分析,并应用于晴空区风场的实例反演。数值模拟图像的结果显示,分裂窗差值算法可以削弱地表对示踪物信号的影响,突出水汽和沙尘气溶胶的分布特征,验证了分裂窗差值法的可行性与优越性。实例分析也表明,使用分裂窗差值图能够反演出单通道云图难以得到的晴空区低层风场,且反演结果与NCEP风场资料比较一致。     

Assessment of leaf carotenoids content with a new carotenoid index: Development and validation on experimental and model data

Leaf carotenoids content (LCar) is an important indicator of plant physiological status. Accurate estimation of LCar provides valuable insight into early detection of stress in vegetation. With spectroscopy techniques, a semi-empirical approach based on spectral indices was extensively used for carotenoids content estimation. However, established spectral indices for carotenoids that generally rely on limited measured data, might lack predictive accuracy for carotenoids estimation in various species and at different growth stages. In this study, we propose a new carotenoid index (CARI) for LCar assessment based on a large synthetic dataset simulated from the leaf radiative transfer model PROSPECT-5, and evaluate its capability with both simulated data from PROSPECT-5 and 4SAIL and extensive experimental datasets: the ANGERS dataset and experimental data acquired in field experiments in China in 2004. Results show that CARI was the index most linearly correlated with carotenoids content at the leaf level using a synthetic dataset (R² = 0.943, RMSE = 1.196 μg/cm²), compared with published spectral indices. Cross-validation results with CARI using ANGERS data achieved quite an accurate estimation (R² = 0.545, RMSE = 3.413 μg/cm²), though the RBRI performed as the best index (R² = 0.727, RMSE = 2.640 μg/cm²). CARI also showed good accuracy (R² = 0.639, RMSE = 1.520 μg/cm²) for LCar assessment with leaf level field survey data, though PRI performed better (R² = 0.710, RMSE = 1.369 μg/cm²). Whereas RBRI, PRI and other assessed spectral indices showed a good performance for a given dataset, overall their estimation accuracy was not consistent across all datasets used in this study. Conversely CARI was more robust showing good results in all datasets. Further assessment of LCar with simulated and measured canopy reflectance data indicated that CARI might not be very sensitive to LCar changes at low leaf area index (LAI) value, and in these conditions soil moisture influenced the LCar retrieval accuracy.     

倾斜实景模型和LiDAR点云数据相融合的不动产测量新方法

不动产地籍测量是一项基础性的测绘工作,地籍测量技术与方法的良性发展不仅能够最大限度地提升我国土地利用率,还能为获取高精度的空间数据提供高效便捷的手段.针对传统全站仪与GPS RTK组合地籍测量作业效率低、人力财力耗费大的缺点,本文依托陕南某地的地籍和不动产权籍调查项目,提出了一种地面三维激光扫描技术和倾斜摄影测量技术相...