Exploring spatial-temporal change and gravity center movement of construction land in the Chang-Zhu-Tan urban agglomeration

Urban agglomeration is caused by the continuous acceleration of the urbanization process in China. Studying the expansion of construction land can not only know the changes and development of urban agglomeration in time, but also obtain the great significance of the future management. In this study, taking Changsha-Zhuzhou-Xiangtan (Chang-Zhu-Tan) urban agglomeration in Hunan province as a study area, Landsat images from 1995 to 2014 and Autologistic-CLUE-S model simulation data were used. Moreover, several factors including gravity center, direction, distance and landscape index were considered in the analysis of the expansion. The results revealed that the construction area increased by 132.18%, from 372.28 km² in 1995 to 864.37 km² in 2014. And it might even reach 1327.23 km² in 2023. Before 2014, three cities had their own respective and discrete development directions. However, because of the integration policy implementation in 2008, the Chang-Zhu-Tan began to gather, the gravity center moved southward after 2014, and the distance between cities decreased, which was in line with the development plan of urban expansion. The research methods and results were relatively reliable, and these results could provide some reference for the future land use planning and spatial allocation in the urbanization process of Chang-Zhu-Tan urban agglomeration.

     

A density-based approach for detecting network-constrained clusters in spatial point events

Existing spatial clustering methods primarily focus on points distributed in planar space. However, occurrence locations and background processes of most human mobility events within cities are constrained by the road network space. Here we describe a density-based clustering approach for objectively detecting clusters in network-constrained point events. First, the network-constrained Delaunay triangulation is constructed to facilitate the measurement of network distances between points. Then, a combination of network kernel density estimation and potential entropy is executed to determine the optimal neighbourhood size. Furthermore, all network-constrained events are tested under a null hypothesis to statistically identify core points with significantly high densities. Finally, spatial clusters can be formed by expanding from the identified core points. Experimental comparisons performed on the origin and destination points of taxis in Beijing demonstrate that the proposed method can ascertain network-constrained clusters precisely and significantly. The resulting time-dependent patterns of clusters will be informative for taxi route selections in the future.     

Two-stage permutation tests for determining homogeneity within a spatial cluster

The discovery of spatial clusters formed by proximal spatial units with similar non-spatial attribute values plays an important role in spatial data analysis. Although several spatial contiguity-constrained clustering methods are currently available, almost all of them discover clusters in a geographical dataset, even though the dataset has no natural clustering structure. Statistically evaluating the significance of the degree of homogeneity within a single spatial cluster is difficult. To overcome this limitation, this study develops a permutation test approach Specifically, the homogeneity of a spatial cluster is measured based on the local variance and cluster member permutation, and two-stage permutation tests are developed to determine the significance of the degree of homogeneity within each spatial cluster. The proposed permutation tests can be integrated into the existing spatial clustering algorithms to detect homogeneous spatial clusters. The proposed tests are compared with four existing tests (i.e., Park’s test, the contiguity-constrained nonparametric analysis of variance (COCOPAN) method, spatial scan statistic, and q-statistic) using two simulated and two meteorological datasets. The comparison shows that the proposed two-stage permutation tests are more effective to identify homogeneous spatial clusters and to determine homogeneous clustering structures in practical applications.     

Study on Nonlinear Characteristics of Freak-Wave Forces with Different Wave Steepness

The nonlinear wave forces on vertical cylinders induced by freak wave trains were experimentally investigated. A series of freak wave trains with different wave steepness were modeled in a wave flume. The corresponding wave forces on vertical cylinders of different diameters were measured. The experimental wave forces were also compared with the predicted results based on Morison formula. Particular attentions were paid to the effects of wave steepness on the dimensionless peak forces, asymmetry characteristics of the impact forces and high-frequency force components. Wavelet-based analysis methods were employed in revealing the local energy structures and quadratic phase coupling in the freak wave forces.     

马里亚纳海沟挑战者深渊初期多金属氧化物的 矿物学、地球化学特征及其成因环境研究

对大洋27航次在西太平洋马里亚纳海沟挑战者深渊获取的3个多金属氧化物样品进行了X射线矿物衍射分析、穆斯堡尔谱分析及地球化学元素分析,研究其矿物、地球化学特征差异。结果表明,所取样品处于多金属氧化物发育的初始阶段,具有独特的矿物地球化学特征:(1)相较于太平洋CC区及中太平洋海盆获取的多金属结核样品,本研究样品的矿物组成中含有异常高的石英、斜长石以及黏土矿物,而水羟锰矿和钙锰矿含量较低。(2)样品中铁相矿物主要为正方针铁矿(91.6%),另含少量纤铁矿(8.4%),推测是纤铁矿向更加稳定的正方针铁矿衍变的结果。(3)由于样品中深海黏土组分以及氧化物核心物质的混入,加上吸附金属氧化物时间较短,导致SiO₂和Al₂O₃含量均高于正常结核,而Fe、Mn、Cu、Co、Ni等其余金属元素含量较低。(4)由于形成时间较短,样品中稀土元素含量相对较低,ΣREE仅约为0.4×10^-3(一般太平洋CC区及中太平洋结核中稀土含量均大于1.0×10^-3);加之海水氧化还原作用的降低以及研究区海底热液活动的影响,Ce元素未表现出多金属结核中常见的正异常。     

DOT2008A海面地形模型在我国邻近海域的精度评估

文中首先介绍了DOT2008A模型建立的原理和方法,利用我国48个长期验潮站19 a连续观测数据验证DOT2008A模型的精度,其均方差为0.118 m,残差的标准偏差为0.086 m;联合多源测高卫星建立的海面地形模型数据验证DOT2008A的精度,均方差为0.106 m,残差的标准偏差为0.099 5 m,且其残差分布图基本符合正态分布。从实验结果来看,DOT2008A模型在我国周边海域精度较高,其建立方法较为合理,转化应用价值较高;同时与多源测高卫星建立的海面地形比较结果来看,验证了自主建立的海面地形模型的正确性,对建立我国高精度海面地形模型具有重要的借鉴意义。     

An improved building detection approach using L-band POLSAR two-dimensional time-frequency decomposition over oriented built-up areas

The objective of this study is to efficiently extract detailed information about various man-made targets in oriented built-up areas using polarimetric synthetic aperture radar (POLSAR) images. This paper develops an improved approach for building detection by utilizing Two-Dimensional Time-Frequency (2-D TF) decomposition. This method performs outstandingly in distinguishing between man-made and natural targets based on the isotropic behaviors, frequency-sensitive responses, and scattering mechanisms of objects. The proposed method can preserve the spatial resolution and exploit the advantages of TF decomposition; specifically, the exact outlines of buildings can be effectively located, and more types of features (e.g., flat roofs, roads, and walls that are oblique to the radar illumination) can be distinguished from forests in complex built-up areas by 2-D TF decomposition. The coarser-resolution subaperture images that are produced in the azimuth direction, which correspond to different looking angles, are beneficial for detecting man-made structures with main scattering centers oriented at oblique angles with respect to the radar illumination. In the range direction, the obtained subaperture images, which correspond to various observation frequencies, can be helpful in distinguishing flat roofs and roads from forests. This method was successfully implemented to analyze both NASA/JPL L-band AIRSAR and L-band EMISAR data sets. The building detection results of the proposed method exhibit a significant improvement over those of other methods and reach an overall accuracy over 80%, with approximately 20% higher than the accuracies of K-means clustering and the entropy/alpha-Wishart classifier and approximately 10% higher than the accuracy of the support vector machine method. Moreover, building details can be precisely detected, obliquely oriented buildings can be identified, and the distinction between buildings and forests is significantly improved, as both visually and statistically indicated. This method is highly adaptable and has substantial application value.     

基于资源三号卫星立体像对的DEM提取实验及其应用——以拉萨市城关区为例

利用测绘卫星立体像对提取DEM效率高、精度高。本实验的主要目的是进行资源三号测绘卫星立体像对高海拔地区DEM提取实验,比较正视、前视及后视3种视角全色影像不同组合情况的立体像对所提取DEM的效果,以拉萨市城关区为实验区,并将实验结果与SRTMDEM进行比较。实验结果显示,正视与前、后视组成的立体像对提取的DEM效果相当,均好于前视、后视全色影像组成的立体像对提取得到的DEM,拉萨市城关区空间分辨率可达10 m,效果良好,可为城市地质灾害评价等提供基础数据。     

基于经验模式分解的太阳南北半球黑子面积的Rieger-type周期相位分析

采用经验模式分解技术研究了从第12到第24太阳活动周黑子面积数据中的Rieger-type周期,以及它们在南北半球上的相位关系。研究发现:(1)Rieger-type周期尺度以及时间尺度在两个半球上是不一样的,从而导致了半球分布的不对称性;(2)平均Rieger-type周期在北半球上的周期长度略大于南半球上的;(3)占主导地位半球的Rieger-type周期的相位不一定是超前的,半球Rieger-type周期尺度相近的也并不一定是相关性强的。     

运用人工鱼群算法的3D扫描碎片重建探究

针对传统三维碎片拼接匹配过程中依赖单一特征及存在误差累积的问题,提出了一种运用鱼群算法的全局最优匹配方法。该方法先对碎片点云数据进行多特征提取,结合纹理、专家经验信息对混合在一起的多种类型碎片进行粗糙集分类,之后采用鱼群算法的最优解求得最佳匹配方案。实例验证所提全局匹配方法具有能力强、与初始位置无关及较强的稳健性等特点,为三维碎片的全局匹配提供了一种有效的解决方案。