青海高原近43年夏季水汽分布及演变特征

通过对青海高原近43年夏季空中水汽分布及演变的研究,结果表明:(1)夏季来自孟加拉湾的暖湿水汽在东亚夏季风的驱动下向东北方向输送,与沿中纬度的西风环流输送的水汽在青海高原会合,但受高原大地形阻挡,到达该区的水汽含量较源区大大减小;(2)青海高原水汽通量场自西界向东界增加,水汽通量高值区基本分布在青海东部的边坡地带;(3)近43年青海高原净水汽通量收支有正有负,但整体上却呈增加趋势;(4)旱年青海高原水汽通量比平均状况偏少10~40 kg.m-1.s-1;涝年偏多10~20 kg.m-1.s-1;无论旱涝年,青海高原空中净水汽通量均呈正值,但旱年比平均状况偏少21.88%,涝年偏多53.99%。     

德令哈地应力强震短期异常特征研究

德令哈地应力自1997年投入观测以来,在青海及其邻近地区发生了4次Ms≥5.9级地震,在这4次地震前德令哈地应力观测资料显示出明显的短临异常。本文使用形态分析和斜率法对这几次异常进行了分析,对其短临异常特征结合地震的破裂类型进行了初步总结。     

与澜沧大震可能相关的震磁效应——小波分析一例

用小波法分析了与1988年澜沧大震相关的通海台地磁Z分量资料。小波分析结果显示地震前“日变幅差”ΔTg(24)存在可能的异常变化;异常为正异常,异常幅度很大,异常结束后立即发生了地震。     

ARIMA-LSTM组合模型在基于SPI干旱预测中的应用——以青海省为例

开展干旱预测是有效应对干旱风险的前提基础。利用1958—2017年青海省38个气象站点逐日降水量数据计算多尺度标准化降水指数（SPI）,并建立了SPI序列自回归移动平均模型（ARIMA）、长短时记忆神经网络模型（LSTM）和基于二者优点提出的ARIMA-LSTM组合模型;对模型参数进行率定和验证后,利用所建立的模型,以西宁站点为例,对多尺度SPI值进行预测,借助均方根误差（RMSE）、平均绝对百分比误差（MAPE）和决定系数R²对所有预测模型的有效性进行判定。结果表明：ARIMA-LSTM组合模型在SPI1和SPI12的RMSE值分别为0.159 7和0.181 0,均低于ARIMA模型的1.265 4和0.293 3,说明ARIMA模型与ARIMA-LSTM组合模型对SPI的预测精度都与时间尺度有关,ARIMA模型的预测精度随着时间尺度的增加而逐渐提高;结合GIS并利用实测数据与模型的预测数据相比较说明ARIMA-LSTM组合模型相比于单一ARIMA模型的预测精度更高,且能够很好拟合不同时间尺度的SPI值。     

“一带一路”建设背景下重庆与东盟国家贸易格局演变和影响因素分析

“贸易畅通”是“一带一路”建设的重要内容,重庆作为中国西部地区内陆开放高地,贸易发展优势明显。运用贸易强度指数和HM指数,分析2001—2017年重庆与东盟国家贸易格局和贸易依赖程度,并分析影响重庆与东盟国家贸易格局的影响因素。结果表明：①重庆与东盟国家贸易联系紧密,增长速度快,贸易总额在“一带一路”沿线六大区域中始终保持领先地位;②马来西亚和泰国成为重庆与东盟国家中最重要的贸易伙伴,越南、新加坡、菲律宾和印度尼西亚紧随其后,而与缅甸、柬埔寨、老挝和文莱的贸易总额较少;③在进口方面,形成以马来西亚、泰国和越南为首的多元进口格局,泰国和越南进口伙伴地位上升。在出口方面,形成以马来西亚为首的多元出口新格局,越南出口地位下降;④在市场相互依赖程度方面,重庆出口对东盟国家特别是马来西亚和新加坡贸易市场的重要性程度上升,而对东盟国家市场依赖程度较小;⑤产业结构、贸易通道、文化交流和政策等是影响重庆与东盟国家贸易格局的重要影响因素。     

Tree species identification within an extensive forest area with diverse management regimes using airborne hyperspectral data

Information on tree species composition is crucial in forest management and can be obtained using remote sensing. While the topic has been addressed frequently over the last years, the remote sensing-based identification of tree species across wide and complex forest areas is still sparse in the literature. Our study presents a tree species classification of a large fraction of the Białowieża Forest in Poland covering 62 000 ha and being subject to diverse management regimes. Key objectives were to obtain an accurate tree species map and to examine if the prevalent management strategy influences the classification results. Tree species classification was conducted based on airborne hyperspectral HySpex data. We applied an iterative Support Vector Machine classification and obtained a thematic map of 7 individual tree species (birch, oak, hornbeam, lime, alder, pine, spruce) and an additional class containing other broadleaves. Generally, the more heterogeneous the area was, the more errors we observed in the classification results. Managed forests were classified more accurately than reserves. Our findings indicate that mapping dominant tree species with airborne hyperspectral data can be accomplished also over large areas and that forest management and its effects on forest structure has an influence on classification accuracies and should be actively considered when progressing towards operational mapping of tree species composition.     

Lidar-aided analysis of boreal forest backscatter at Ku band

This paper analyzes the backscatter of the microwave signal in a boreal forest environment based on a Ku -band airborne Frequency-Modulated Continuous Waveform (FMCW) profiling radar—Tomoradar. We selected a half-managed boreal forest in the southern part of Finland for a field test. By decomposing the waveform collected by the Tomoradar, the vertical canopy structure was achieved. Based on the amplitude of the waveform, the Backscattered Energy Ratio of Canopy-to-Total (BERCT) was calculated. Meanwhile, the canopy fraction was derived from the corresponding point cloud recorded by a Velodyne VLP-16 LiDAR mounted on the same platform. Lidar-derived canopy fraction was obtained by counting the number of the first/ the strongest returns versus the total amount of returns. Qualitative and quantitative analysis of radar-derived BERCT on lidar-derived canopy fraction and canopy height are investigated. A fitted model is derived to describe the Ku-band microwave backscatter in the boreal forest to numerically analyze the proportion contributed by four factors: lidar-derived canopy fraction, radar-derived canopy height, the radar-derived distance between trees and radar sensor and other factors, from co-polarization Tomoradar measurements. The Root Mean Squared Error (RMSE) of the proposed model was 0.0958, and the coefficient of determination R2 was 0.912. The fitted model reveals that the correlation coefficient between radar-derived BERCT and lidar-derived canopy fraction is 0.84, which illustrates that lidar surface reflection explains the majority of the profiling /waveform radar response. Thus, vertical canopy structure derived from lidar can be used for the benefit of radar analysis.     

金沙江美姑河牛牛坝水电站库区泥石流对工程影响分析

金沙江美姑河牛牛坝水电站库区泥石流沟分布面积广、发生频率高;调查表明库区现有不同类型泥石流沟31条,其中属于高度危险的泥石流沟4条,中度危险的泥石流沟15条;这些泥石流不会造成严重的堵河问题。在施工期泥石流对水电站工程的影响突出,特别是靠近库首的泥石流对工程的安全构成威胁。水库蓄水后,库区泥石流对水电站工程影响有所降低,但位于大坝下游区的泥石流对水电站正常运行仍有较大的影响。     

青藏铁路冻土区路基工程安全可靠性监测技术研究

通过对冻土区路基工程和冻土之间相互作用过程的分析,提出冻土区路基工程的安全可靠性监测关键技术一是监测方法,二是监测手段,三是数据分析。冻土区路基工程的安全可靠性首先取决于工程周围和工程基底多年冻土的热稳定性,其次取决于发生变形的路基填土厚度及其基底融化层厚度。因此,路基顶面以下不同深度地温监测和年际冻融季节时段路基土层变形监测是冻土区工程长期可靠性监测的主要指标。青藏铁路自然条件的严酷性,要求监测手段具有可靠性和耐久性以及对复杂自然条件变化的适应性。文章提出一种自动观测多年冻土地温和路基变形,并能够实现数据无线传输的现场监测系统设计方案,通过现场试验,证明这种监测系统能够适应青藏高原恶劣的自然条件,减轻了人工监测的劳苦,具有可靠性和耐久性。作者还提出了能够简便判断冻土区工程安全可靠性的监测数据分析方法,对目前冻土区工程安全可靠性分析具有一定的理论指导作用。     

青海团宝山花岗岩年代学、地球化学特征及其地质意义

青海省团宝山花岗岩位于南祁连东段,侵位于古元古代化隆群中.为了解其侵位时代、岩体成因和产出构造环境,利用LA-ICP-MS锆石U-Pb定年和地球化学测试方法对团宝山花岗岩岩体样品进行分析.获得其锆石U-Pb年龄为(776±8)Ma;该岩体SiO2、Al2O3和K2O含量较高,而FeOT、MgO和CaO含量较低,K2O/...