上部基坑施工对软土地铁隧道变形监测与分析

新金桥广场基坑围护结构位于正在运营的地铁隧道顶部。通过有效的隧道结构变形监控指导施工使其对地铁隧道的影响控制在允许范围内,对这一成功经验进行总结,以供今后工作参考。     

改进的小波阈值函数对变形监测数据的去噪研究

基于小波分析中传统的阈值函数,结合其他学者提出的小波阈值函数,提出一种改进的小波阈值函数,并将其应用于变形监测数据的去噪处理。理论分析和算例表明,新的小波阈值去噪函数能够有效去除噪声。     

A novel dynamic stretching solution to eliminate saturation effect in NDVI and its application in drought monitoring

The normalized difference vegetation index(NDVI) is one of the key input variables for developing drought indices.However,the NDVI quickly saturates in high vegetation surfaces,and thus,the generalization of a drought index over different ecosystems becomes a challenge.This paper presents a novel,dynamic stretching algorithm to overcome the saturation effect in NDVI.A scaling transformation function to eliminate saturation effects when the vegetation fraction(VF) is large is proposed.Dynamic range adjustment is conducted using three coefficients,namely,the normalization factor(a),the stretching range controlling factor(m),and the stretching size controlling factor(e).The results show that the stretched NDVI(S-NDVI) is more sensitive to vegetation fraction than NDVI when the VF is large,ranging from 0.75 to 1.00.Moreover,the saturation effect in NDVI is effectively removed by using the S-NDVI.Further analysis suggests that there is a good linear correlation between the S-NDVI and the leaf area index(LAI).At the same time,the proposed S-NDVI significantly reduces or even eliminates the saturation effect over high biomass.A comparative analysis is performed between drought indices derived from NDVI and S-NDVI,respectively.In the experiment,reflectance data from the moderate resolution imaging spectroradiometer(MODIS) products and in-situ observation data from the meteorological sites at a regional scale are used.In this study,the coefficient of determination(R2) of the stretched drought index(S-DI) is above 0.5,indicating the reliability of the proposed algorithm with surface soil moisture content.Thus,the S-DI is suggested to be used as a drought index in extended regions,thus regional heterogeneity should be taken into account when applying stretching method.     

青藏高原典型植被生长季遥感模型提取分析

物候变化是衡量全球气候变化最直接、敏感的指示器,针对青藏高原这个独特地域单元上特殊的高寒植被进行关键物候期遥感提取模型及植被物候时空变化的研究具有重要的意义。本文首先以反距离加权空间插值算法与Savitzky-Golay滤波算法相结合的数据重建模型获得高质量2003-2012年青藏高原MODIS归一化植被指数(NDVI)数据。在此数据基础上,分别利用动态阈值法、最大变化斜率法、logistic曲线拟合法3种遥感植被生长季提取模型,对青藏高原地区两种典型植被的生长季(SOS生长季开始期,EOS生长季结束期,LOS生长季长度)进行提取。通过对3种模型提取结果的对比分析,并结合日均温模型对提取结果的验证发现,动态阈值法为青藏高原地区典型植被生长季的最优遥感提取模型。该模型对近10 a的高分辨率典型高寒植被物候参量的反演及时空变化特征分析表明,受青藏高原水热及海拔梯度的影响,青藏高原植被物候变化呈现出从东南向西北的空间分异规律,随春季温度的升高,近10 a来青藏高原高寒草地总体呈现生长季开始期(SOS)提前(0.248 d/a)的趋势。     

基于CEEMDAN的GNSS变形监测去噪方法

为了提高GNSS变形监测数据去噪的有效性和可靠性,提出一种自适应完备集合经验模态分解(complete ensemble empirical mode decomposition with adaptive noise, CEEMDAN)去噪方法。首先将GNSS变形序列经CEEMDAN分解为若干特征模态函数;其次引入排列熵理论确定高低频分界值K,利用小波分析对高频分量进行去噪,去噪后与低频分量重构得到去噪序列;最后通过仿真和实测边坡GNSS变形监测数据,利用信噪比、均方根误差、相关系数等指标对比分析CEEMDAN、EMD和小波去噪方法。结果表明,CEEMDAN方法的去噪效果和精度优于EMD和小波去噪方法,证明了本文所提方法的有效性和可靠性。     

山东省地面沉降监测与防治工作进展

近年来,山东省地面沉降监测与防治工作取得了重要进展,初步建立了以二等水准路线、全球定位系统(GPS)、基岩标分层标和地下水监测为基础的"四网合一"地面沉降监测体系,INSAR监测实现了山东全省覆盖。监测成果显示,山东省地面沉降主要位于东营市广饶县、滨州市博兴县、聊城市茌平县,沉降速率呈加快趋势,造成建筑物地基下沉、房屋开裂、地下管道破损等一系列地质环境问题。     

臭氧卫星遥感六十年进展

臭氧已成为中国继PM_2.5之后多地的首要污染物,臭氧污染防治是中国“十四五”及未来大气污染防治的重点。本文回顾了近60年来国内外臭氧卫星观测方面的主要进展,包括卫星探测载荷和臭氧相关的反演应用技术等,分为3个阶段总结了卫星载荷天底、临边和掩星3种探测方式的发展历程。臭氧卫星遥感反演算法和监测应用也随着载荷的发展在不断更新,本文重点介绍了臭氧柱总量和垂直廓线卫星遥感反演算法、近地面臭氧及其前体物观测、平流层臭氧入侵观测和区域传输、臭氧卫星观测数据的精度验证等方面的重要进展。对比国际臭氧卫星遥感监测,中国臭氧监测卫星发展滞后,虽然国家民用空间基础设施规划中陆续发射的高光谱观测卫星、大气环境监测卫星具有初步的臭氧监测能力,但在卫星载荷在功能、性能等方面还有不小差距,比如空间分辨率、信噪比等方面。在算法反演和监测应用方面,目前臭氧柱总量反演精度较高,还存在对流层中低层和近地面臭氧浓度反演精度不够,臭氧污染评估及成因分析不足,如近地面臭氧污染迁移转化过程、平流层臭氧侵入识别分析等问题,是下一步要重点关注的方向。     

辽宁太阳紫外线辐射特征及强度预报

利用紫外线观测仪器对辽宁4个地区紫外线辐射强度进行观测,研究了辽宁地区紫外线辐射强度的变化特征;分析了影响到达地面紫外线辐射强度的因子,结合MM5数值模式建立了统计预测模型,建立了紫外线辐射强度分级标准和对人体健康影响的对应关系。结果表明:辽宁地区的紫外线辐射强度,总体上是西、北部较东、南部稍强,但相差不大;紫外线辐射强度具有明显的季节变化,夏季最大、冬季最小。每年5～9月紫外线强度维持在一个较高的水平,日最大值出现在每日的11～14时。夏季紫外线对人体的影响最大,冬季基本无影响。云量的变化对紫外线强度的影响较大。紫外线辐射强度预报模型的预测结果较为理想。     

Seasonal variation of airborne fungi of the Tiantishan Grottoes and Western Xia Museum,Wuwei, China

In this study, a systematic survey of cultural airborne fungi was carried out in the occurrence environments of wall paintings that are preserved in the Tiantishan Grottoes and the Western Xia Museum, China. A bio-aerosol sampler was used for sampling in four seasons in 2016. Culture-dependent and -independent methods were taken to acquire airborne fungal concentration and purified strains; by the extraction of genomic DNA, amplification of fungal ITS rRNA gene region, sequencing, and phylogenetic analysis, thereafter the fungal community composition and distribution characteristics of different study sites were clarified. We disclosure the main environmental factors which may be responsible for dynamic changes of airborne fungi at the sampling sites. The concentration of cultural airborne fungi was in a range from 13 to 1,576 CFU/m³, no significant difference between the two sites at the Tiantishan Grottoes, with obvious characteristics of seasonal variation, in winter and spring were higher than in summer and autumn. Also, there was a significant difference in fungal concentration between the inside and outside of the Western Xia Museum, the outside of the museum was far more than the inside of the museum in the four seasons, particularly in the winter. Eight fungal genera were detected, including Cladosporium, Penicillium, Alternaria, and Filobasidium as the dominant groups. The airborne fungal community structures of the Tiantishan Grottoes show a distinct characteristic of seasonal variation and spatial distribution. Relative humidity, temperature and seasonal rainfall influence airborne fungal distribution. Some of the isolated strains have the potential to cause biodeterioration of ancient wall paintings. This study provides supporting information for the pre-warning conservation of cultural relics that are preserved at local sites and inside museums.     

基于改进PSO-SVM的噪声稳健建筑物变形监测方法

对高层、超高层建筑物进行实时,高精度的变形监测对提前预防安全隐患,保证人民生命财产安全具有重要意义.建筑物变形作为一种典型的随机性和微弱性过程,噪声等误差的存在会影响从中提取有用的变形信息.针对该问题,提出一种改进粒子群(ParticleSwarmOptimization,PSO)算法优化支持向量机(SupportVe...