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1.
Inland water bodies are globally threatened by environmental degradation and climate change. On the other hand, new water bodies can be designed during landscape restoration (e.g. after coal mining). Effective management of new water resources requires continuous monitoring; in situ surveys are, however, extremely time-demanding. Remote sensing has been widely used for identifying water bodies. However, the use of optical imagery is constrained by accuracy problems related to the difficulty in distinguishing water features from other surfaces with low albedo, such as tree shadows. This is especially true when mapping water bodies of different sizes. To address these problems, we evaluated the potential of integrating hyperspectral data with LiDAR (hereinafter “integrative approach”). The study area consisted of several spoil heaps containing heterogeneous water bodies with a high variability of shape and size. We utilized object-based classification (Support Vector Machine) based on: (i) hyperspectral data; (ii) LiDAR variables; (iii) integration of both datasets. Besides, we classified hyperspectral data using pixel-based approaches (K-mean, spectral angle mapper). Individual approaches (hyperspectral data, LiDAR data and integrative approach) resulted in 2–22.4 % underestimation of the water surface area (i.e, omission error) and 0.4–1.5 % overestimation (i.e., commission error).The integrative approach yielded an improved discrimination of open water surface compared to other approaches (omission error of 2 % and commission error of 0.4 %). We also evaluated the success of detecting individual ponds; the integrative approach was the only one capable of detecting the water bodies with both omission and commission errors below 10 %. Finally, the assessment of misclassification reasons showed a successful elimination of shadows in the integrative approach. Our findings demonstrate that the integration of hyperspectral and LiDAR data can greatly improve the identification of small water bodies and can be applied in practice to support mapping of restoration process.  相似文献   
2.
当强震台站场地资料不完整时,所收集到的强震数据因缺乏准确的场地类别信息而难以有效利用。为解决这一问题,本文提出一种基于离散Fréchet距离的强震台站场地分类方法。将获取到的664个KiK-net台站场地按照《建筑抗震设计规范(GB 50011—2010)》进行分类,并构建2个数据集。利用数据集1得到Ⅰ、Ⅱ、Ⅲ类场地标准谱比曲线,并结合离散Fréchet距离对数据集2中的台站进行场地分类,统计分类成功率与误判率。统计结果表明,本文方法能较准确地对场地进行分类,且误判率在可接受范围内。将本文方法分类统计结果与斯皮尔曼秩相关系数法分类的成功率与误判率进行对比,结合本文方法分类后得到的平均谱比曲线,均可表明应用本文方法进行强震台站场地分类具有合理性。  相似文献   
3.
北京平原地区VS30估算模型适用性研究   总被引:1,自引:1,他引:0  
本文使用基于钻孔测井数据的3类模型,即常速度外推模型、速度梯度模型、双深度参数外推模型,通过对北京地区460个深度超过30m的钻孔剪切波速资料进行分析,详细探究了VS30估算模型在本研究区的适用性。研究结果表明双深度参数外推模型在估算VS30上准确度很高,其不需要大量的数据进行回归分析,且不具有区域独立性,可以为全球包括北京地区场地类别划分提供依据,进而在震害快速评估中用于确定场地影响,是一种值得推广的估算模型。  相似文献   
4.
张建平  金小赤 《地质论评》2022,68(6):2022112008-2022112008
2022年10月25至28日,国际地质科学联合会在西班牙Zumaia召开的“庆祝国际地质科学联合会成立60周年大会”上,正式向全球公布了国际地质科学联合会国际地球遗产委员会承担的国际地学计划(IGCP)731项目的成果之一:首批100个国际地质科学联合会地质遗产地名录,并发布了“国际地质科学联合会Zumaia宣言”,呼吁国际社会重视和关注地质遗产地的科学研究和保护管理,引起国际地学界和公众极大的关注。基于全程参与该项工作,本文系统介绍国际地质科学联合会地质遗产地名录的由来、发展、遴选程序和过程、地质遗产地的定义和标准,指出建立地质遗产地名录对科学研究和可持续发展的意义,并对今后地质遗产地发展前景进行展望,供读者参考。  相似文献   
5.
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.  相似文献   
6.
One important step in binary modeling of environmental problems is the generation of absence-datasets that are traditionally generated by random sampling and can undermine the quality of outputs.To solve this problem,this study develops the Absence Point Generation(APG)toolbox which is a Python-based ArcGIS toolbox for automated construction of absence-datasets for geospatial studies.The APG employs a frequency ratio analysis of four commonly used and important driving factors such as altitude,slope degree,topographic wetness index,and distance from rivers,and considers the presence locations buffer and density layers to define the low potential or susceptibility zones where absence-datasets are gener-ated.To test the APG toolbox,we applied two benchmark algorithms of random forest(RF)and boosted regression trees(BRT)in a case study to investigate groundwater potential using three absence datasets i.e.,the APG,random,and selection of absence samples(SAS)toolbox.The BRT-APG and RF-APG had the area under receiver operating curve(AUC)values of 0.947 and 0.942,while BRT and RF had weaker per-formances with the SAS and Random datasets.This effect resulted in AUC improvements for BRT and RF by 7.2,and 9.7%from the Random dataset,and AUC improvements for BRT and RF by 6.1,and 5.4%from the SAS dataset,respectively.The APG also impacted the importance of the input factors and the pattern of the groundwater potential maps,which proves the importance of absence points in environmental bin-ary issues.The proposed APG toolbox could be easily applied in other environmental hazards such as landslides,floods,and gully erosion,and land subsidence.  相似文献   
7.
The Western Yunnan Earthquake Predication Test Site set up jointly by the China Earthquake Administration, the National Science Foundation Commission of America, and United States Geological Survey has played an important role in development of early earthquake research work in China. Due to various objective reasons, most of the predicted targets in the earthquake prediction test site have not been achieved, and the development has been hindered. In recent years, the experiment site has been reconsidered, and renamed the “Earthquake Science Experimental Site”. Combined with the current development of seismology and the practical needs of disaster prevention and mitigation, we propose adding the “Underground Cloud Map” as the new direction of the experimental site. Using highly repeatable, environmentally friendly and safe airgun sources, we could send constant seismic signals, which realizes continuous monitoring of subsurface velocity changes. Utilizing the high-resolution 3-D crustal structure from ambient noise tomography, we could obtain 4-D (3-D space + 1-D time) images of subsurface structures, which we termed the “Underground Cloud Map”. The “Underground Cloud Map” can reflect underground velocity and stress changes, providing new means for the earthquake monitoring forecast nationwide, which promotes the conversion of experience-based earthquake prediction to physics-based prediction.  相似文献   
8.
吴效勇  王晓青  袁小祥  窦爱霞  丁香 《地震》2019,39(4):147-157
场地条件对地震动具有较大影响, 研究不同场地条件下的地震动特征对地震动的校正具有重要意义。 本文以九寨沟地震为例, 收集了66个台站的198条三分量强震观测记录和SRTM(Shuttle Radar Topography Mission)公里格网的DEM(Digital Elevation Model)数据, 从多个角度对场地特征进行分析。 首先根据坡度法使用DEM数据对九寨沟特征进行了场地分类, 然后讨论了不同场地类型下的加速度时程、 加速度反应谱、 地震动衰减等地震动特征。 研究表明, 缺少实测资料的情况下, 地形坡度可以作为Vs30(地表以下30 m范围的平均剪切波速度)的一种替代指标, 利用坡度法可以较快速地对场地进行分类; 利用强震观测记录能够从多角度对台站的场地特征进行分析, 不同场地类型对地震动影响不同, 其中, 土层对地震动具有明显的放大效应。 该结论可以为地震动结果的校正提供依据。  相似文献   
9.
Using the records of 3,069 regional earthquake events from the Fujian Digital Seismic Network from October 2008 to December 2015,in which the magnitude of each of the events was measured by at least six stations,statistics are taken on the deviation between the magnitude of a single station and the average magnitude of the network. It is found that the magnitudes average deviation of each station is-0. 31-0. 68. Statistics are also taken for the period corresponding to the maximum amplitude of the record measured in each station for calculating the magnitude,and the dominant period gained is 0. 06s-0. 38s; site response of each seismic station is inverted using the Moya method,and it is found that the site response of 98 stations is in the bands of 1-20 Hz,suggesting that the site has an amplifying or suppressing effect on the signals in certain frequency bands;Considering the site response corresponding to the inherent 0. 8s period of the WoodAnderson pendulum seismograph,and comparing the magnitude deviation caused by the site response corresponding to the dominant period time of each station with the average magnitude deviation, we obtain that there is a good linear relationship between the magnitude deviation from the dominant period site response and the average deviation of the magnitude of each station,indicating that the magnitude deviation of a single station has a close relationship with the site response of the period corresponding to the maximum amplitude measured for calculating the magnitude.  相似文献   
10.
为了研究湖北地区地震震源参数特征,本文基于湖北数字地震台网记录到的S波观测振幅谱,通过遗传算法获得湖北地区的介质品质因子和台站场地响应,并在此基础上计算了湖北地区地震震源参数。结果显示,湖北地区介质品质因子Q值随频率f变化的关系式为Q(f)=501.8·f~(0.309);对于大部分台站获得了与其岩石基底相符的场地响应,没有出现明显放大效应;地震震级与地震矩对数间呈线性关系,即lg M_0=10.06+1.093M_L;震源半径与应力降间呈双对数线性关系,即lgΔσ=10.52-2.01lgr;地震矩与拐角频率间整体上呈反相关;地震矩与应力降间关系不显著。  相似文献   
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