利用城市骨架线网的道路和居民地联动匹配方法

同名道路或者居民地数据间由于数据一致性程度不高,往往存在较大的几何位置偏差,当对道路或者居民地单独进行匹配时,不利于提高匹配正确率和效率。针对这一问题,本文提出了一种利用城市骨架线网的道路和居民地联动匹配方法。联动匹配即模仿人在读图时通过特征地物和空间关联寻找目标地物的思维过程,将匹配看作是一种特征目标寻找、信息关联传递的推理过程。首先,利用约束Delaunay三角网对地图构建城市骨架线网。然后,通过道路、骨架线、骨架线网眼和居民地之间的拓扑关系建立道路和居民地之间的匹配传递模型。最后,根据该传递模型实现通过道路匹配带动居民地匹配或者通过居民地匹配带动道路匹配的联动匹配。该方法优势在于只要有一种要素的数据一致性比较好,就能带动另一种要素取得很好的匹配效果,同时符合人类进行匹配时的认知过程。     

基于灰度和方向一致性的遥感影像道路网提取

从遥感影像中提取道路网是一个经典课题,根据遥感影像中的道路具有灰度和方向一致性的特征,提出一种从遥感影像中提取道路网的新方法。首先根据遥感影像的灰度信息和方向方差信息建立灰度和方向一致性准则分割模型,由此可从遥感影像中提取基本的道路网轮廓,然后再针对道路区域存在非道路点:空洞和裂缝等情况,采用膨胀、腐蚀等操作去除杂乱物块,最后通过数学形态学操作提取出道路网。实验结果表明,该方法能够适用道路、建筑物、植被等多种复杂地物的城市遥感影像中提取道路网,且能获得较好地提取效果。     

常用稳健估计方法在测边网解算中的应用

针对最小二乘估计中稳健估计方法的效果尚未被分析证明的问题,该文以不同观测值数量、不同粗差数量和等权或不等权观测值的三个测边网为例,通过仿真实验的方法,对12种常用稳健估计方法的稳健性进行了比较,确定了对测边网解算相对更为有效的稳健估计方法。结果表明,L1法、Danish法、German-McClure法和IGGIII方案是12种方法中更为有效的稳健估计方法,能相对更有效地消除或减弱粗差对参数估计结果的影响。     

An assessment of gully erosion along major armoured roads in south-eastern region of South Africa: a remote sensing and GIS approach

An assessment of gully erosion along road drainage-release sites is critical for understanding the contribution of roads to soil loss and for informed land management practices. Considering that road-related gully erosion has traditionally been measured using field methods that are expensive, tedious and limited spatially as well as temporally, it is important to identify affordable, timely and robust methods that can be used to effectively map and estimate the volume of gullies along the road networks. In this study, gullies along major roads were identified from remotely sensed data sets and their volumes were estimated in a Geographic Information Systems environment. Also, the biophysical and climatic factors such as vegetation cover, the road contributing surface area, the gradient of the discharge hillslope and rainfall were derived from remotely sensed data sets using Geographic Information Systems techniques to find out whether they could explain the morphology of gullies that existed in this area. The results of this study indicate that hillslope gradient (R²?=?0.69, α = 0.00) and road contributing surface area (R²?=?0.63, α = 0.00) have a strong influence on the volume of gullies along the major roads in the south-eastern region of South Africa, as might have been expected. However, other factors such as vegetation cover (R² = 0.52, α = 0.00) and rainfall (R² = 0.41 and α = 0.58) have a moderately weaker influence on the overall volume of gullies. Overall, the findings of this study highlight the importance of using remote sensing and Geographic Information Systems technologies in investigating gully erosion occurrence along major roads where detailed field work remains a challenge.     

基于蚁群算法在实际动态路网中搜索最佳路径的应用

最佳路径是实际动态路网中备受关注的话题之一,为了提高出行的效率、缓解交通拥堵的状况,本文对动态路网进行分析研究。通过分析实际动态路网的可通行性及影响因素,针对在理论研究中未结合实际路网中的影响因素而得出的最佳路线不符实际路线中的最优情况,在蚁群算法的基础上,结合实际路况,笔者对其进行改进,该算法可实现计算出一条从起始点到终点的最佳路径,并在Visual Studio 2010中用C#语言设计并验证了该算法,证明了它的正确性和有效性。     

Spatial interpolation using conditional generative adversarial neural networks

ABSTRACT

Spatial interpolation is a traditional geostatistical operation that aims at predicting the attribute values of unobserved locations given a sample of data defined on point supports. However, the continuity and heterogeneity underlying spatial data are too complex to be approximated by classic statistical models. Deep learning models, especially the idea of conditional generative adversarial networks (CGANs), provide us with a perspective for formalizing spatial interpolation as a conditional generative task. In this article, we design a novel deep learning architecture named conditional encoder-decoder generative adversarial neural networks (CEDGANs) for spatial interpolation, therein combining the encoder-decoder structure with adversarial learning to capture deep representations of sampled spatial data and their interactions with local structural patterns. A case study on elevations in China demonstrates the ability of our model to achieve outstanding interpolation results compared to benchmark methods. Further experiments uncover the learned spatial knowledge in the model’s hidden layers and test the potential to generalize our adversarial interpolation idea across domains. This work is an endeavor to investigate deep spatial knowledge using artificial intelligence. The proposed model can benefit practical scenarios and enlighten future research in various geographical applications related to spatial prediction.     

P wave amplitude measurements at the Kaapvaal network: do they help in resolving deep earth structure?

Measurements of the amplitudes of seismic body waves at teleseismic distances have rarely resolved significant features mainly because of the large scatter of the data. However, amplitudes are easy to measure and may provide additional constraints on structure to supplement times and waveforms. A new approach to analysing body wave amplitudes at a regional network of similar instruments seeks to minimize scatter by first deriving amplitude station corrections analogous to station corrections for times. After correction for station effects, amplitudes from several events can be combined to give regional amplitude–distance curves without using information on event magnitudes. However, the earthquakes providing the observations must lie in a restricted range of azimuths from the stations of the network and provide considerable overlap in the range of distances between adjacent events, with no gaps in distance coverage. The advantages of the method are explored using P wave amplitudes from two sets of earthquakes in the Indonesian and South American regions recorded by the Kaapvaal network deployed across southern Africa. In the first example, high amplitudes near 88° distance suggest the presence of a small discontinuity at the top of D″ that causes constructive interference between the closely separated arrivals of a small triplication in the travel times. The second example, supplemented by calculations using synthetic data, shows how long-wavelength regional variations in amplitudes can be resolved to assist the interpretation of times and waveforms. However, the limited range of distances in the observations and lateral heterogeneities at any depths can result in bias or tilt of the amplitude–distance relationships. Constraining the depths of the structure causing the long-wavelength variations is a subject for future research.     

Estimation of the Amount of Suspended Sediment in the Tigris River using Artificial Neural Networks

The amount of sediment should be taken into consideration in the planning of water structures for efficient use of limited water resources. It is important to estimate the amount of sediment for the successful operation of these structures in their future performances. Such estimations can be achieved by Artificial Neural Network (ANNs) with low error percentages as seen in many other disciplines. These networks also enable the modeling of nonlinear relationships between the parameters affecting the event. The purpose of this research is to establish models for sediment amounts in the Tigris River at the Diyarbakir measurement station in Turkey. Rainfall, temperature and discharge are taken as independent variables in the models, whereas sediment is taken as the dependent variable. Fourteen different models are generated using ANNs and Regression Analysis (RA). The results are compared with each other and with the observed data. The relative error and determination coefficient are used as comparison criteria. It is concluded that due to their nonlinear modeling capability, ANNs give better results than RA.     

土工格栅在加固高速公路路堤中的应用研究

土工格栅应用到高速公路路基中,对土性参数c,? 值有不同程度的改善作用,在一定程度上解决了特殊土的施工问题。土工格栅蠕变试验表明,在相同荷载作用下,强度大的格栅应变较小;并且荷载变化及温度大小对格栅流变性有显著影响。有限元分析是研究加筋作用效果的一种有效方法,它可定性比较多种加筋方案的优劣。利用PLAXIS有限元模拟不同工况下的沉降量,表明土工格栅在限制水平方向位移比限制垂直方向位移更有效。现场荷载试验表明,土工格栅加筋能使路基承载力成倍提高,改善土体应力环境,有效地均衡差异沉降和减少总沉降量。土工格栅对路堤加固有显著作用,值得在实际工程中广泛应用。     

基于特征面向对象的地理网络模型研究

地理网络建模强调的是对逻辑网络中的节点和联线的网络拓扑和语义操作过程。而传统GIS矢量数据表达所采用的平面图原子级弧段-节点数据模型强调的是几何信息的表达。对此,作者讨论了如何将基于特征的GIS概念建模方法引入地理网络表达中,克服平面图数据模型的不足之处,发展基于特征的地理网络数据模型,并着重阐述了逻辑网络模型的特点和应用特征。在地理网络的表达方法中,作者分析了面向对象方法和数据库技术相结合的途径,比较了传统关系模型和面向对象模型在地理网络表达中的差异,以及面向对象方法在地理网络路径系统表达和动态分段及其网络连通性规则表达中的优势所在。