Integration of hyperspectral and LiDAR data for mapping small water bodies     

《International Journal of Applied Earth Observation and Geoinformation》2020

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   

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management   总被引：1，自引：0，他引：1  

Zizheng Guo  Yu Shi  Faming Huang  Xuanmei Fan  Jinsong Huang 《地学前缘(英文版)》2021,12(6):243-261

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   

APG:A novel python-based ArcGIS toolbox to generate absence-datasets for geospatial studies     

Seyed Amir Naghibi  Hossein Hashemi  Biswajeet Pradhan 《地学前缘(英文版)》2021,12(6):90-104

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   

汶川大型地震滑坡的类型及启程剧动机理研究     

赵晓彦  胡厚田 《工程地质学报》2015,23(1):78-85

2008年汶川大地震诱发大型地震滑坡300余处,造成了巨大的生命财产损失,研究其发生机理有重要的理论意义和防灾减灾的实用价值.经收集分析已有地震滑坡的研究成果及多次深入现场调查,本文发现众多大型地震滑坡发生时都伴随有区别于汶川主震的地面震动,并将其称为滑坡地面震动,简称滑坡震动.本文在论述滑坡震动依据、成因及特征的基础上,根据滑坡震动力与主震力的组合情况及其对大型地震滑坡的影响不同,将汶川地震滑坡划分为3种类型:主震型地震滑坡,迟震型地震滑坡和同震型地震滑坡.认为主震型地震滑坡在主震结束前滑动,其主导失稳力学因素为主震力和重力,无滑坡震动或可忽略; 同震型地震滑坡亦在主震结束前滑动,但其主导失稳力学因素除主震力和重力外,滑坡震动力起重要作用; 迟震型地震滑坡在主震结束后滑动,主导失稳力学因素为滑坡震动力和重力.认为大型地震滑坡地面震动的发生与活断层导致地震类似,据此提出了滑坡震动加速度的估算方法,并以此为基础分析研究了各类型地震滑坡的启程剧动机理.  相似文献   

Salt diapirs without well defined boundaries – a feasibility study of semi‐automatic detection     

Anglique Berthelot  Anne H. S. Solberg  Erlend Morisbak  Leiv‐J Gelius 《Geophysical Prospecting》2011,59(4):682-696

Prestack depth imaging of seismic data in complex areas such as salt structures requires extensive velocity model updating. In many cases, salt boundaries can be difficult to identify due to lack of seismic reflectivity. Traditional amplitude based segmentation methods do not properly tackle this problem, resulting in extensive manual editing. This paper presents a selection of seismic attributes that can reveal texture differences between the salt diapirs and the surrounding geology as opposed to amplitude‐sensitive attributes that are used in case of well defined boundaries. The approach consists of first extracting selected texture attributes, then using these attributes to train a classifier to estimate the probability that each pixel in the data set belongs to one of the following classes: near‐horizontal layering, highly‐dipping areas and the inside of the salt that appears more like a low amplitude area with small variations in texture. To find the border between the inside of the salt and the highly‐dipping surroundings, the posterior probability of the class salt is input to a graph‐cut algorithm that produces a smooth, continuous border. An in‐line seismic section and a timeslice from a 3D North Sea data set were employed to test the proposed approach. Comparisons between the automatically segmented salt contours and the corresponding contours as provided by an experienced interpreter showed a high degree of similarity.  相似文献   

关于土地覆被遥感监测的几点思考   总被引：1，自引：0，他引：1  

张磊  吴炳方 《国土资源遥感》2011,22(1):15-20

针对国内外土地覆被遥感监测中存在的突出问题展开讨论,分析土地覆被分类系统的目标适应性; 总结现有分类算法的特点及存在问题,分析小尺度和大尺度监测技术的差异性和效果; 研究不同尺度土地覆被监测所解决的应用问题及尺度空间变化下的分类效果; 分析现有监测体系的分类精度及产生误差的原因和解决方法.  相似文献   

Classifying knowledge on climate change impacts, adaptation, and vulnerability in Europe for informing adaptation research and decision-making: A conceptual meta-analysis   总被引：3，自引：0，他引：3  

Mareen E. Hofmann  Jochen HinkelMarkus Wrobel 《Global Environmental Change》2011,21(3):1106-1116

Knowledge on climate change impacts, adaptation, and vulnerability is fragmented, because it is found in disparate case studies which use inconsistent terminology and focus on distinct aspects relevant to adaptation. While large-scale syntheses such as the Assessment Reports of the Intergovernmental Panel on Climate Change provide a high level overview and are useful for international decision-making, there is a need for systematic and flexible access to this research-based knowledge in order to aid future adaptation research and decision-making. Against this background, we present a ‘conceptual’ meta-analysis, a novel approach to meta-analyse studies on climate change impacts, adaptation, and vulnerability in Europe. The meta-analysis results in a classification scheme for relating the diverse studies. This scheme consists of (i) a classification of studies according to the type of adaptation-relevant results they produce and (ii) a hierarchical classification of the regional and thematic context of studies. The implementation of this scheme, for example in the form of a database, overcomes some of the identified gaps of current adaptation knowledge representation. We furthermore present a quantitative analysis of the classified studies that exemplifies how the developed classification scheme can be applied to get a systematic and quantitative overview of the knowledge they contain. Thus, the conceptual meta-analysis and the classification scheme represent a first step towards a systematisation of knowledge on climate change impacts, adaptation, and vulnerability and may be seen as a useful complement to qualitative literature reviews.  相似文献   

矿物学文献中未定名矿物的编码系统:国际矿物学协会新矿物与命名和分类委员会“未定名矿物”小组报告     

傅小土  杨主明 《矿物学报》2015,35(2):276-278

国际矿物学协会新矿物与命名和分类委员会(IMA-CNMMN)的未定名矿物小组(SUM),开发了一个编码系统,对已经发表但尚未定名的矿物进行编码。在文献中存在两类未定名矿物。一是"有效"未定名矿物,是指未定名矿物没有对应的已知矿物种,但如果它们有其他产地或能够在其他样品中被发现,那么已发表的相关矿物描述允许得到认可。二是"无效"未定名矿物,是指未定名矿物已经有对应的已知矿物种;或者相关矿物描述不足以获得认可。未定名矿物的名单是由IMA保管。该编码系统提供了一个永久的UM号码。中国的矿物学文献的数量和重要性有必要用中文阐述未定名矿物的编码系统。  相似文献   

基于SVM测井数据的火山岩岩性识别——以辽河盆地东部坳陷为例   总被引：2，自引：1，他引：1       下载免费PDF全文

牟丹  王祝文  黄玉龙  许石  周大鹏 《地球物理学报》2015,58(5):1785-1793

辽河盆地东部坳陷储集层由火山多期喷发形成,岩相岩性复杂,岩性以中、基性火山岩为主.本文将火山岩的岩心及岩矿鉴定资料与测井数据进行整合,应用测井数据建立支持向量机(SVM)两分类和多分类岩性识别模式.首先,深入研究支持向量机二分类及"一对一"、"一对多"和有向无环图三种经典多分类算法的基本原理及结构;然后,总结研究区域火山岩岩石特征,分析测井数据的测井响应组合特征,选择40口井中岩心分析和薄片鉴定资料完整、常规五种测井曲线(RLLD,CNL,DEN,AC,GR)齐全的1200个测井数据作为训练样本,构造三种支持向量机岩性识别模式;最后,对4测试井中800个测井数据进行岩性识别,识别结果与取心段岩心描述和岩心/岩屑薄片鉴定资料对比,实验结果表明有向无环图更适合辽河盆地火山岩的识别,识别正确率达到82.3%.  相似文献   

Kinematic classification of non-interacting spiral galaxies     

《New Astronomy》2014

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