滇西北亚高山针叶林、硬叶栎类林的树种多样性

在滇西北香格里拉地区,以长苞冷杉(Abiesgeorgei)林、丽江云杉(Picealikiangensis)林作为亚高山针叶林的代表,以川滇高山栎(Quercusaquifolioides)林作为硬叶栎类林的代表,分别选择了6块样地,采用Shannon-Wiener多样性指数(H)、Simpson多样性指数的倒数(D')、Pielou均匀度指数(JH、JD)分别测定其树种多样性,并进行了比较研究。结果表明,三个森林类型的Shannon Wiener指数、Simpson指数的倒数、物种丰富度的顺序均为:长苞冷杉林>川滇高山栎林>丽江云杉林;而前两类森林的Pielou均匀度指数差异不大,但都高于丽江云杉林的均匀度指数值。滇西北的川滇高山栎具有很强的萌生能力。人工种植的亚高山针叶林的树种多样性较原始林低,需要较长时间的恢复过程。亚高山针叶林的存在极大地丰富了云南省的树种多样性,使云南植被的垂直地带性得到了充分体现。     

Approximate optimal tracking control for near-surface AUVs with wave disturbances

This paper considers the optimal trajectory tracking control problem for near-surface autonomous underwater vehicles (AUVs) in the presence of wave disturbances. An approximate optimal tracking control (AOTC) approach is proposed. Firstly, a six-degrees-of-freedom (six-DOF) AUV model with its body-fixed coordinate system is decoupled and simplified and then a nonlinear control model of AUVs in the vertical plane is given. Also, an exosystem model of wave disturbances is constructed based on Hirom approximation formula. Secondly, the time-parameterized desired trajectory which is tracked by the AUV’s system is represented by the exosystem. Then, the coupled two-point boundary value (TPBV) problem of optimal tracking control for AUVs is derived from the theory of quadratic optimal control. By using a recently developed successive approximation approach to construct sequences, the coupled TPBV problem is transformed into a problem of solving two decoupled linear differential sequences of state vectors and adjoint vectors. By iteratively solving the two equation sequences, the AOTC law is obtained, which consists of a nonlinear optimal feedback item, an expected output tracking item, a feedforward disturbances rejection item, and a nonlinear compensatory term. Furthermore, a wave disturbances observer model is designed in order to solve the physically realizable problem. Simulation is carried out by using the Remote Environmental Unit (REMUS) AUV model to demonstrate the effectiveness of the proposed algorithm.     

某电站坝区玄武岩承压水特征及其对建坝影响分析

某电站玄武岩坝区地质条件复杂,研究表明坝区玄武岩裂隙含水系统具有不均匀性、各向异性和多级次性特点。本文结合玄武岩裂隙特征和渗透系数确定方法,给出了评价岩体渗透性的尺度。勘探揭露河床右侧及右岸岸坡发育承压水,据埋藏条件和水化学成分可分为上部承压水和下部承压水,分别对其分布范围特征;承压水水位、流量及动态特征;承压水水化学特征;贮存环境特征;补给、径流、排泄特征等方面进行阐述,分析了承压水对建坝影响,根据分析成果采取针对性处理措施,取得了较好的效果。     

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.     

自然保护地社区居民感知冲突的空间响应及形成机制——以西昌邛海国家湿地公园为例

以西昌邛海国家湿地公园为例,采用半结构访谈与参与式制图相结合的方法对当地居民进行调查。通过质性+空间的混合分析方法探讨了居民感知冲突的类型、空间响应分布及其形成机制,旨在为自然保护地的冲突管理提供参考,实现人地关系协调发展。结果显示：① 社区居民感知有7种冲突类型,分别为生计保障不足、活动空间压缩、政策措施缺位、情感支持弱化、日常生活不便、环境质量降低和生产经营矛盾,前5种冲突总占比达76.4%,构成了当地的主要冲突;② 冲突的空间响应是居民对冲突关注度和不满意程度的共同反映,总体上呈现出高值区相对独立、低值区连片分布的空间格局,响应水平较高的区域,具有较高的冲突显示度和管理优先等级;③ 冲突的空间响应是多因素共同作用的复杂现象,其中旅游开发程度和生计策略的影响较大,交通出行管理、居住区类型、土地利用类型和房屋修建管理的影响也不容忽视,总体反映了邛海生态建设、旅游开发、政策与制度安排、社会经济等基本情况,分别为冲突响应提供了原始动力、外部推动力、结构性动力和社会性动力。     

利用风云3D微波成像仪数据估算北极海冰密集度的精度评价

卷积神经网络（convolutional neural network, CNN）已用于星载全球导航卫星系统反射测量（global navigation satellite system-reflectometry,GNSS-R）海冰检测,其具有数据预处理简单、最大限度保留反射面信息等优势,但已有GNSS-R CNN海冰检测方法研究的数据集时间跨度较小,代表性有限,且未考虑训练集内海水、海冰时延多普勒图（delay-Doppler map, DDM）的比例对方法泛化能力的影响。针对该问题,首先提出一种筛除畸形DDM方法,有效筛除错误数据;然后,设计合适的CNN结构及参数,通过小样本对比实验发现CNN模型在训练集内海水、海冰DDM的比例为1∶1时具有高准确率和最佳泛化能力,并优化数据集选取策略;最后使用2018年全年大样本数据集评估改进的方法在大数据量和大时间跨度时的有效性和可靠性。研究表明,改进的方法通过加强数据质量控制、优化数据集选取策略,提升了CNN海冰检测方法的泛化能力及可靠性,使其更适用于实际应用场景,为海冰消融等研究提供参考。

     

Why are halo coronal mass ejections faster?

Halo coronal mass ejections (CMEs) have been to be significantly faster than normal CMEs, which is a long-standing puzzle. In order to solve the puzzle, we first investigate the observed properties of 31 limb CMEs that clearly display loopshaped frontal loops. The observational results show a strong tendency that slower CMEs are weaker in white-light intensity. Then, we perform a Monte Carlo simulation of 20000 artificial limb CMEs that have an average velocity of ～523km s -1. The Thomson scattering of thes...     

梧桐坑梯级开发工程地质条件研究

桔桐坑小流域水电梯级开发 ,为三级开发方案 ,以沙铺砻水电站为枢纽 ,结合开发贵庄口水电站、金坑口水电站工程。本文从工程地质角度出发 ,利用三个水电站工程 ,对梧桐坑流域进行地质条件研究