A surface network based method for studying urban hierarchies by night time light remote sensing data

Urban hierarchies are closely related to economic growth, urban planning and sustainable urban development. Due to the limited availability of reliable statistical data at fine scales, most existing studies on urban hierarchy characterization failed to capture the detailed urban spatial structure information. Previous studies have demonstrated that night time light data are correlated with many urban socio-economic indicators and hence can be used to characterize urban hierarchies. This paper presents a novel method for studying urban hierarchies from night time light data. Night time light data were first conceptualized as continuous mathematical surfaces, termed night time light surfaces. From the morphology of these surfaces the corresponding surface networks were derived. Hereafter, a night time light intensity (NTLI) graph was defined to describe the morphology of the surface network. Then, structural similarity between the night time light surfaces of any two different cities was calculated via a threshold-based maximum common induced graph searching algorithm. Finally, urban hierarchies were defined on the basis of the structural similarities between different cities. Using the 2015 annual NPP-VIIRS night time light data, the urban hierarchies of 32 major cities in China were successfully examined. The results are highly consistent with the reference urban hierarchies.     

Ekman模型时间变化风应力系数的伴随参数估计

本文基于时间分布参数设置,利用伴随同化方法,反演了Ekman模型中随时间变化的风应力拖曳系数,并在孪生实验和实际实验中对该方法进行了验证。在孪生实验中,研究了参数反演结果对不同影响因素的响应,包括:风速分布、风应力系数分布、风应力系数初始猜测值、风应力系数独立变量个数、观测数据误差和观测的深度。孪生实验结果验证了伴随同化方法反演Ekman模型中时变风应力系数的有效性,具体包括如下五个方面结论:1)不同风速分布下均能成功反演出不同风应力拖曳系数分布; 2)反演结果对初始猜测值较为敏感,风应力系数初始猜测值越接近给定值,反演结果越好;3)风应力系数独立点个数的选取会显著影响反演结果,合理的选择有利于提高反演效率及减小观测数据误差;4)观测误差能够影响反演结果,观测数据误差在20%以下时能取得合理的反演结果; 5)反演结果对观测数据的表层和次表层流速更为敏感,这是由Ekman流的物理性质决定的。实际实验,利用百慕大锚系试验平台的风速和流速数据,去除周期性潮流和地转流成分后得到Ekman流成分,并作为观测输入到该同化模型,反演出了适用于该区域和该时段的随时间变化的风应力系数。通过比较模拟流速和观测流速,证明利用伴随同化方法能从实测数据中反演出合理的时变风应力系数,对于海洋模型风应力系数的确定是一项有益的尝试。     

Experimental study on a sampling technique based on a freeze-sediments valve for deep-sea microorganism

Deep-sea microorganism research has become a hot topic in life science, owing to its special value in high pressure and low temperature environment. If not kept the in-situ low temperature and high pressure, it will cause the microorganism to lose its activity and lead to a waste of resources. A freeze-sediments valve presents a promising solution to maintain the low temperature and high pressure in situ, improve the success rate of sampling and shorten the sampling time. A series of experiments were conducted to characterize the freeze-sediments valve, including the sampling time without leakage, adaptation to different sediments and the effect of the length, etc. Most important of all, temperature change of sediments is observed in all experiments. Experimental results indicated that the freeze-sediments valve was formed in 5 min without leakage and the freeze-sediments valve could be applied to different sediments without limitations on sediments type and mineral content. Considering the pressure retaining capacity and formation time of freeze-sediments valve, it was found that the freeze-sediments valve with a length of 60–80 mm has good pressure retaining capacity whose value was 41.3–48.4 Mpa and short formation time which was 5 min. Precooling the sampler could be used to shorten the sampling time in the actual environment application. This sampling technique can play a vital role in maintaining in-situ low temperature at −2 to −4 ° Celsius in all the experiments. According to the tests, the sampling technique based on the freeze-sediments valve had the potential to solve the problem of keeping in-situ temperature, low sampling success rate and long sampling time in the future.     

Stochastic bivariate time series models of waves in the North Sea and their application in simulation-based design

In this paper, we present and evaluate three long-term wave models for application in simulation-based design of ships and marine structures. Designers and researchers often rely on historical weather data as a source for ocean area characteristics based on hindcast datasets or in-situ measurements. The limited access and size of historical datasets reduces repeatability of simulations and analyses, making it difficult to assess the sampling variability of performance and loads on marine vessels and structures. Markov, VAR and VARMA wave models, producing independent long-term time series of significant wave height (H_s) and spectral peak period (T_p), is presented as possible solutions to this problem. The models are tested and compared by addressing how the models affect interpretation of design concepts and the ability to replicate statistical and physical characteristics of the wave process. Our results show that the VAR and VARMA models perform sufficiently in describing design performance, but does not capture the physical process fully. The Markov model is found to perform worst of the tested models in the applied tests, especially for measures covering several consecutive sea states.     

Large-time response of ice cover to a load moving along a frozen channel

Unsteady response of an ice cover in a channel with vertical walls is studied for large times. The ice deflection is caused by a load moving along the frozen channel at a constant speed. The ice cover is modelled as a thin elastic plate clamped to the walls of the channel. The time-dependent problem is solved by using the Fourier transform along the channel and the method of separating variables. In the system moving along the channel together with the load, the large-time deflection of the ice cover consists of steady deflection and standing waves in front and behind the load. The number of waves, their frequencies and wavenumbers depend on the speed of the load and the values of the critical speeds for the channel. The number of the waves and their amplitudes are calculated for a given load and its speed. The maximum stress in the ice as a function of the load speed is estimated.     

时间尺度重构EEMD-GRNN改进模型预测PM2.5的研究

合理构建PM_2.5浓度预测模型是科学、准确地预测PM_2.5浓度变化的关键。传统PM_2.5预测EEMD-GRNN模型具有较好的预测精度,但是存在过于关注研究数据本身而忽略其物理意义的不足。本研究基于南京市2014-2017年PM_2.5浓度时间序列数据,分析PM_2.5浓度多尺度变化特征及其对气象因子和大气污染因子的尺度响应,基于时间尺度重构进行EEMD-GRNN模型的改进与实证研究。南京市样本数据PM_2.5浓度变化表现为明显的天际尺度和月际尺度,从重构尺度（天际、月际）构建GRNN模型更具有现实意义;同时,PM_2.5对PM₁₀、NO₂、O₃、RH、MinT等因子存在多尺度响应效应,以其作为GRNN模型中的输入变量更具有时间序列上的解释意义。改进后的EEMD-GRNN模型具有更高的PM_2.5浓度预测精度,MAE、MAPE、RMSE和R²分别为6.17、18.41%、8.32和0.95,而传统EEMD-GRNN模型的模型有效性检验结果分别为8.37、27.56%、11.56、0.91。对于高浓度天（PM_2.5浓度大于100 μg/m³）的预测,改进模型更是全面优于传统EEMD-GRNN模型,MAPE为12.02%,相较于传统模型提高了9.03%。     

基于GPS和水准数据的微粒群算法联合反演祁连山北缘断裂三维滑动速率

将微粒群算法与位错理论模型相结合,采用中国地壳运动观测网络提供的青藏高原地区2001~2004年GPS测量数据和2000~2006年水准测量数据,通过常规定权和附有相对权比的方法对祁连山北缘断裂的三维滑动速率进行联合反演,并与蚁群算法反演结果进行对比。结果表明,微粒群算法收敛速度快、稳定性高,结合经典位错理论模型,是一种可以有效求解断层三维滑动速率反演问题的优化算法,在大地测量反演领域极具应用潜力。     

重力数据约束的二维地震层析成像在台湾海峡南部的应用

地震-重力联合反演可以降低多解性,针对大勘探范围内岩石波速-密度关系存在较大散布的问题,引入交叉梯度结构约束构建统一的目标函数是一种有效的解决方案。利用台湾海峡南部HX-13测线进行验证:由于火成岩侵入体的存在,部分区域难以拾取可靠的地震初至,常规的走时反演无法准确恢复基底面的形态。搜集研究区的船测重力资料,根据地震地质条件和数据特点设置合适的反演参数,实现基于物性和结构双重约束的重力-地震联合反演。由对反演结果的分析和解释可以看出,该方法可在很大程度上弥补地震数据不完备的缺陷,使反演过程稳定,并提高模型的可靠性。     

GNSS变形监测网短基线时间序列噪声特性分析

利用时间跨度为5 a的GNSS短基线时间序列对噪声特性进行分析,发现长周期噪声分量(随机游走噪声)。选取最优噪声模型,评估不同噪声模型对测站周期振幅和线性速度估值的影响。结果表明,短基线时间序列中有色噪声应顾及闪烁噪声和随机游走噪声,对于表现出随机游走噪声的分量,可能与测站的真实运动有关;假设只有白噪声时求得的速度估值与最优噪声模型下求得的速度估值存在0.4～0.6 mm/a的偏差,对周期振幅的影响可以忽略。     

基于位置大数据的国庆假期青藏高原人群分布时空变化模式挖掘

人类活动是引起青藏高原生态环境发生改变的重要因素。很多学者对青藏高原史前人类活动和近几十年的人口分布格局与人口流动开展了大量研究,但有关人群时空分布的精细尺度研究相对缺乏。海量的位置大数据为认识高原人群短期的动态变化提供了新途径。本文利用手机定位数据、人口迁徙数据等高时空分辨率的位置大数据,通过时间序列分解方法和基于统计检验的异常判别方法,分析了2017年国庆期间青海与西藏的人群分布时空变化特征,并探讨了假期旅游行为及人口迁徙与变化特征之间的关系。研究结果显示：① 在省级和城市整体尺度上,定位请求量的假期变化在时间上呈现先降后升的“潮汐”变化模式;② 在精细网格尺度上,西宁和拉萨城市及周边地区的人群分布变化在空间上呈现中心跌、周边涨的“离心化”变化模式。国庆假期人们向城市周边热门景点移动聚集的旅游行为和城市之间的人口迁徙都是导致西宁和拉萨周边地区定位请求量上涨的重要潜在原因,而两座高原城市中心定位请求的下跌不仅与人口迁徙有关,还与假期人类日常行为及定位请求频次的变化等因素有关。通过位置大数据挖掘节庆假期人群分布的时空变化,不仅加深了对高原人口分布格局与流动变化的认识,也为高原城镇化与生态保护的精细化管理与决策提供支撑。