基于GIS的盐城国家级自然保护区生态安全评价（英文）

本研究利用遥感和GIS技术,分析盐城自然保护区1983–2018年的景观格局变化,建立了基于区域自然-社会-经济复合生态系统安全格局的评价指标体系,分析了生态安全变化的空间特征和成因。结果表明,1983–2018年由于人类活动加剧,研究区内景观格局变化强烈,从以自然景观为主发展到自然景观与人工景观并存。在整体生态安全方面,目前保护区的生态安全状况不容乐观,从保护区丹顶鹤的生存状态看,保护区总体上还是适宜丹顶鹤栖息的,但由于人类活动的增加以及政策的调整,丹顶鹤的栖息地呈现破碎化并向核心区和缓冲区等局部区域聚集。我们应从管理、政策制定以及当地居民的环境保护意识上增加宣传和投入,并相应减少保护区内人类活动的强度。     

Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.     

ASTER数据的煤矿区水体信息提取

为实现多光谱数据对煤矿区水体信息提取,以萍乡市芦新岭及周边煤矿为试验区,在国内外学者对水体指数法提取水体信息和应用的启发下,对试验区不同地物的波谱特征进行分析。本文首先利用数学统计方法建立一种ASTER数据综合归一化差异水体指数模型SWI ASTER_xy,然后利用这一模型对试验区进行水体信息提取。试验表明,该模型能够有效地提取矿区各类水体,还可以运用在ASTER数据（或其他多光谱数据）对不同区域不同地物的提取,在遥感地物定量提取上具有很好的效果和潜力,具有一定的推广价值。     

基于无人机遥感和面向对象法的简单地物分类研究

近年来,全国各地进行了大范围的土地利用调查,随着无人机遥感技术越来越成熟,无人机影像分析技术已深入应用到土地利用调查中,其中最多的用途是地物分类。本文选择昭通市昭阳区某乡镇区域为研究区,对采集到的无人机影像进行预处理,生成对应的正射影像;基于多种可见光植被指数,计算每3种指数合并得到影像的OIF指数,确定最佳波段组合;采用基于规则和基于样本两种面向对象分类方法,提取房屋、道路、植被等简单地物及背景。分析结果:两种方法的提取精度均达到90%以上,基于规则的面向对象分类方法精度较高,但耗时较长;基于样本的面向对象方法耗时较短,精度相对较低。两种方法相结合的全自动分类提取是下一步研究的目标。     

Mapping 3D visibility in an urban street environment from mobile LiDAR point clouds

ABSTRACT

Visibility determination is a key requirement in a wide range of national and urban applications, such as national security, landscape management, and urban design. Mobile LiDAR point clouds can depict the urban built environment with a high level of details and accuracy. However, few three-dimensional visibility approaches have been developed for the street-level point-cloud data. Accordingly, an approach based on mobile LiDAR point clouds has been developed to map the three-dimensional visibility at the street level. The method consists of five steps: voxelization of point-cloud data, construction of lines-of-sight, construction of sectors of sight, construction of three-dimensional visible space, and calculation of volume index. The proposed approach is able to automatically measure the volume of visible space and openness at any viewpoint along a street. This approach has been applied to three study areas. The results indicated that the proposed approach enables accurate simulation of visible space as well as high-resolution (1 m × 1 m) mapping of the visible volume index. The proposed approach can make a contribution to the improvement of urban planning and design processes that aim at developing more sustainable built environments.     

西北太平洋低纬度区域海水中溶解氨基酸的分布及组成研究

本文对2018年秋季西北太平洋低纬度区域上层海洋(5~200 m)中溶解氨基酸(THAA)的分布和组成进行了研究。结果表明,该海域表层海水中THAA的浓度范围为0.40~0.97μmol/L,平均浓度为0.58±0.14μmol/L;5~200m垂直断面上THAA的平均浓度为0.59±0.16μmol/L,范围为0.30~1.05μmol/L。调查海域内THAA浓度明显低于中国近海,在5~200m内的垂直分布基本表现出随深度增加而增加的趋势。将表层和垂直水体中的THAA分别与DOC、Chla等环境因子进行相关性分析,结果显示均无显著相关性。西北太平洋低纬度区域海水中的优势氨基酸是天冬氨酸(Asp)、谷氨酸(Glu)、丝氨酸(Ser)、甘氨酸(Gly)、苏氨酸(Thr)和丙氨酸(Ala)。基于氨基酸的碳归一化产率(THAA-C%)、降解因子(DI)值,表明该海域表层海水中的有机质降解程度较高,且随深度的增加而降低。     

成飞飞行区域短时强降水时空分布特征及强降水指数分析

成飞飞行空域包含高原、盆地、山区等多种地形,局地气候显著,短时强降水频发。该文使用国家气象信息中心2017—2021年多资料融合逐小时降水数据、国家自动站探空观测数据。统计分析发现,盆地周围沿山地区为盆地短时强降水高发区;101～102°E,31～32°N区域为高原短时强降水高发区。利用百分位法得到高原地区强对流指数阈值：CAPE值≥1930.5 J·kg^-1,BCAPE值≥1974.7 J·kg^-1,抬升指数≥2.6℃,大气可降水量≥86.1 mm,K指数≥37.2℃,SI指数≤-0.9℃。盆地地区强对流指数阈值：CAPE值≥2230.6 J·kg^-1,BCAPE值≥2264.4 J·kg^-1,抬升指数≥1.8℃,大气可降水量≥93.0 mm,K指数≥40.8℃,SI指数≤-1.8℃。建立短时强降水不同下垫面强对流指数阈值,为今后短时强降雨客观预报提供新的思路和方向。     

简介加利福尼亚理工学院建筑结构健康状态的实时监测和性能评估系统

介绍了加利福尼亚理工学院建筑结构健康状态的实时监测和性能评估系统近年来的发展。该系统安装在帕斯迪纳市的加利福尼亚理工学院校园里的米利肯图书馆内。它通过互联网向全世界提供真实的实时数据。     

细菌细胞膜脂记录的西太平洋暖池约4Ma以来沉积物风尘陆源输入变化

西菲律宾海作为西太平洋暖池的一部分,重建其在地质历史时期的热力学变化、陆源输入变化,对于理解西太平洋暖池在全球地质时间尺度上的作用具有重要意义.利用古菌与细菌的细胞膜质甘油二烷基甘油四醚(glycerol dialkyl glycerol tetraethers,GDGTs)对西菲律宾海XT-47孔沉积物的陆源输入及其...     

广西农业干旱动态评估模型

以自然条件下大气-作物-土壤系统的水量平衡方程为基础,结合广西干旱灾害特点,建立广西农业干旱评估模型。与广西历史农业旱情实况对比分析表明,该模型能够较客观、定量地对农业干旱的发生、发展过程进行逐日动态监测和灾中、灾后评估。