无人机遥感系统在风暴潮灾害损失评估中的应用初探

无人机遥感系统由于具有响应迅速、起降方便、可低空作业、分辨率高等优点,在自然灾害调查及应急救援中有广泛的应用。文章在台风"苏力"登陆后,利用无人机遥感系统及时获取台风登陆点附近25km~2范围的高分辨遥感影像,通过对遥感影像进行分析处理,提取研究区域典型风暴潮承灾体的灾害损失信息并对其进行统计分析,为风暴潮灾害损失评估提供数据支持;对无人机低空遥感系统在风暴潮灾害调查及灾害损失评估中的应用作初步探索。结果表明,无人机低空遥感系统在风暴潮灾害调查中的应用具有一定的可行性且取得一定成果,但受制约的方面也较多,今后还需结合风暴潮灾害特点作进一步的应用探索。     

基于共生理论的中国沿海省市海洋经济生态协调模式研究

建立海洋生态与海洋经济的共生演化Logistic模型,通过压力-状态-影响-响应（PSIR）模型对Logistic模型中的基本指数进行求解,进一步计算海洋生态与海洋经济之间的共生系数,结果表明：天津和上海两市发展模式已摆脱资源索取模式,其海洋经济生态共生模式的探讨意义较小;其余沿海九省中,河北、江苏、广西和海南4省处于反向共生水平,辽宁和山东两省呈现并生模式,浙江和广东呈现出生态受益的偏利共生模式,福建则呈现出经济受害的偏利共生模式。根据沿海各省市海洋经济生态共生模式,提出相关的政策建议,以期对沿海省市今后的经济和生态发展模式提供理论依据。     

GeoCube： 面向大规模分析的多源对地观测时空立方体

随着对地立体观测体系的建立,遥感大数据不断累积。传统基于文件、景/幅式的影像组织方式,时空基准不够统一,集中式存储不利于大规模并行分析。对地观测大数据分析仍缺乏一套统一的数据模型与基础设施理论。近年来,数据立方体的研究为对地观测领域大数据分析基础设施提供了前景。基于统一的分析就绪型多维数据模型和集成对地观测数据分析功能,可构建一个基于数据立方的对地观测大数据分析基础设施。因此,本文提出了一个面向大规模分析的多源对地观测时空立方体,相较于现有的数据立方体方法,强调多源数据的统一组织、基于云计算的立方体处理模式以及基于人工智能优化的立方体计算。研究有助于构建时空大数据分析的新框架,同时建立与商业智能领域的数据立方体关联,为时空大数据建立统一的时空组织模型,支持大范围、长时序的快速大规模对地观测数据分析。本文在性能上与开源数据立方做了对比,结果证明提出的多源对地观测时空立方体在处理性能上具有明显优势。     

西南印度洋中脊表层沉积物非碳酸盐组分的粒度特征及其地质意义

The carbonate-free fraction of 20 surface sediments collected from the ultraslow-spreading Southwest Indian Ridge(SWIR) was studied by grain size analysis and mineralogical analysis with X-ray powder diffraction(XRD),stereo microscopy and scanning electron microscopy(SEM). The characteristics of the carbonate-free fraction of the sediments were obtained, and related influential factors were discussed. The results show that the mean grain size of this fraction is in 1.96Φ–8.19Φ, with poorly sorting and unimodal, bimodal or irregular bimodal distribution patterns. Four grain size end members of the fraction are derived with the End Member Model method. The finest end member EM1 shows a significant contribution of terrigenous materials of the aeolian input and sediment carried by the bottom current. End member EM2 with medium size mainly reflects sediment of a siliceous bioclast origin. EM3 and EM4 are interpreted as representing the coarser volcanic materials related to bedrock weathering or volcanic activities. Multi-provenance is the dominant factor controlling the grain size pattern of the carbonate-free fraction of the sediments in that area. In addition, sediment transport processes such as the bottom current and wind are the minor factors that influence the grain size distribution of the carbonate-free fraction sediments.     

突变理论在边坡工程应用的研究进展

突变理论是非线性科学领域中的一个重要分支,作为一种数学工具已经在众多领域得到广泛应用,在边坡工程中的应用尤为活跃。首先简述了突变理论的发展概况和基本原理,然后分别从3个方面详细论述了突变理论在边坡工程应用中的研究进展,即基于尖点突变法的边(斜)坡稳定性分析、基于突变级数法的边(斜)坡稳定性评价和基于灰色理论、模糊数学的尖点突变预测模型对滑坡时间预报,重点讨论了相应的理论模型、应用方法和实际效果,最后结合目前存在的问题探讨突变理论在边坡工程的发展趋势。     

GeoPW: Laying Blocks for the Geospatial Processing Web

Recent advances in Web‐related technologies have significantly promoted the wide sharing and integrated analysis of distributed geospatial data. Geospatial applications often involve diverse sources of data and complex geoprocessing functions. Existing Web‐based GIS focuses more on access to distributed geospatial data. In scientific problem solving, the ability to carry out geospatial analysis is essential to geoscientific discovery. This article presents the design and implementation of GeoPW, a set of services providing geoprocessing functions over the Web. The concept of the Geospatial Processing Web is discussed to address the geoprocessing demands in the emerging information infrastructure, and the role of GeoPW in establishing the Geospatial Processing Web is identified. The services in GeoPW are implemented by developing middleware that wraps legacy GIS analysis components to provide a large number of geoprocessing utilities over the Web. These services are open and accessible to the public, and they support integrated geoprocessing on the Web.     

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.     

基于层次分析法的黄河上游水源涵养区生态系统恢复力评价——以甘南州、临夏州为例北大核心CSCD

在全球气候变化背景下,人类活动对生态环境质量影响的定量评价是区域生态保护与高质量发展的关键问题。本文基于层次分析法(AHP)和GIS可视化空间分析技术,应用遥感反演的生态系统分类资料和社会经济统计资料等,构建了包含社会经济、土地压力、自然条件3个准则层的生态系统恢复力评价指标体系,结合指标时空尺度无量纲化与综合指数法,进行了甘肃省甘南州、临夏州2000—2020年的生态系统恢复力定量评估。结果表明:研究区域空间尺度生态恢复力范围分别为0.14—0.65(2000年)、0.12—0.72(2005年)、0.07—0.70(2010年)、0.12—0.70(2015年)、0.28—0.82(2020年);甘南生态系统恢复力较高,临夏生态系统恢复力较低,在空间分布上,生态系统恢复力呈现北低南高的总体特征,高生态恢复力的乡镇以草地、森林、灌木生态系统为主,低生态恢复力的乡镇以农田、城镇生态系统为主;在时序变化特征中,生态系统恢复力总体向好,呈现先上升、后下降、最后上升趋势,受人类活动与气候变化共同作用。     

西安市地震应急指挥技术系统设计与实现

本文从系统总体架构设计、系统功能设计与应用成果、系统特色4个方面简要介绍了西安市地震应急指挥技术系统设计与实现情况.本系统是首个应用于省会城市地震应急工作,并基于国产Server GIS软件平台研制开发出的地震应急指挥技术系统,可为大城市地震应急指挥技术系统的建设与发展提供可借鉴的经验.     

基于新型分层邻域阈值搜索法提高水下潜器重力匹配导航的匹配效率

本文开展了水下潜器重力匹配导航的匹配效率改善研究.第一,为克服传统TERCOM算法逐点遍历搜索效率较低的缺点,提出新型分层邻域阈值搜索法.其原理如下：首先,利用4格网间隔数进行粗搜索匹配;其次,为提高初始匹配点的选取标准设置4 mGal阈值（基准图上重力值与实测重力值之差）,对选取的若干粗搜索行最佳匹配点周围24邻域点进行取舍并匹配比较;最后,获得搜索范围内最佳匹配点.第二,综合考虑了重力场标准差、峰度系数、坡度标准差、粗糙度、信息熵等重力场主要特征参数,将其作为适配区优劣的分析依据.第三,在适配性良好的区域内,在保证水下导航精度的前提下,基于分层邻域阈值搜索法,以本文参数设置为例,水下潜器重力匹配导航的匹配效率提高约14.14倍.