Evaluation of effectiveness of three fuzzy systems and three texture extraction methods for building damage detection from post-event LiDAR data

Building damage maps after disasters can help us to better manage the rescue operations. Researchers have used Light Detection and Ranging (LiDAR) data for extracting the building damage maps. For producing building damage maps from LiDAR data in a rapid manner, it is necessary to understand the effectiveness of features and classifiers. However, there is no comprehensive study on the performance of features and classifiers in identifying damaged areas. In this study, the effectiveness of three texture extraction methods and three fuzzy systems for producing the building damage maps was investigated. In the proposed method, at first, a pre-processing stage was utilized to apply essential processes on post-event LiDAR data. Second, textural features were extracted from the pre-processed LiDAR data. Third, fuzzy inference systems were generated to make a relation between the extracted textural features of buildings and their damage extents. The proposed method was tested across three areas over the 2010 Haiti earthquake. Three building damage maps with overall accuracies of 75.0%, 78.1% and 61.4% were achieved. Based on outcomes, the fuzzy inference systems were stronger than random forest, bagging, boosting and support vector machine classifiers for detecting damaged buildings.     

Soil salinity and vegetation cover change detection from multi-temporal remotely sensed imagery in Al Hassa Oasis in Saudi Arabia

Detecting soil salinity changes and its impact on vegetation cover are necessary to understand the relationships between these changes in vegetation cover. This study aims to determine the changes in soil salinity and vegetation cover in Al Hassa Oasis over the past 28 years and investigates whether the salinity change causing the change in vegetation cover. Landsat time series data of years 1985, 2000 and 2013 were used to generate Normalized Difference Vegetation Index (NDVI) and Soil Salinity Index (SI) images, which were then used in image differencing to identify vegetation and salinity change/no-change for two periods. Soil salinity during 2000–2013 exhibits much higher increase compared to 1985–2000, while the vegetation cover declined to 6.31% for the same period. Additionally, highly significant (p < 0.0001) negative relationships found between the NDVI and SI differencing images, confirmed the potential long-term linkage between the changes in soil salinity and vegetation cover.     

微动技术在堤坝渗漏探测中的应用

堤坝是重要的水利工程,其安全性至关重要。坝体渗漏是常见的安全隐患之一,对坝体渗漏位置、程度以及坝体结构变化的探测一直是重要的物探课题。微动勘探作为一种新兴的物探手段,应用范围正逐步拓展,通过某水库大坝渗漏检测实例,展示频率-波数法微动线性点阵剖面测量进行大坝渗漏检测的效果,该技术通过提取频散曲线及视S波速度成像,刻画地层速度结构并圈定异常,可实现对大坝渗漏快速精确的无损探测,具有一定的方法优势和广泛的应用前景。     

人工智能在冰雹识别及临近预报中的初步应用

基于广东10部S波段多普勒天气雷达的三维拼图资料,利用机器学习技术开发了一种冰雹识别和临近预报的人工智能算法。算法设计时以雷达回波反射率的垂直和水平扫描数据为基础训练集,将冰雹云的雷达反射率扫描数据作为正样本,将其他雷达反射率扫描数据作为负样本,通过贝叶斯分类法对正、负样本数据集进行机器学习,训练人工智能识别冰雹云内在规律的能力。训练时以广东省2008-2013和2015-2016年的数据作为训练集,使用了2014年广东省12次冰雹过程的数据做检验。对比检验的结果表明,人工智能法比传统的概念模型法击中率高9个百分点。研究结果表明了人工智能对冰雹这类非线性强天气过程具有较强的识别能力。      

Single epoch GPS deformation signals extraction and gross error detection technique based on wavelet transform

IntroductionGPS technique is widely used for deformationmonitoring thanks for the high precision. Usual-ly , there are three working modes associatedwith GPS deformation observation: periodicalGPS deformation monitoring net , GPS monito-ring array and rea…     

A new approach for vegetation change detection in urban areas

IntroductionVegetation distribution and change is regardedas ani mportant sign of urban environment . Withcity expanding and population increasing, herecomes a series of problems on environment ,andmoreover ,greening ratio is regarded as a stand-ard of ci…     

特深地下管线的电磁场特征分析及探测研究

研究了管线的一系列电磁场特征,介绍了特深管线探测应用状况,通过实例分析了从1 m到21 m了不同埋深直线电流及强电流3~21 m情况下的电磁场Hx、Hz、ΔHx 〖WTBZ〗的归一化异常的分布特征 , 提出了对特深管线探测的对策,即频率、电流、远端接地等提高信噪比的技术对策,提出了确定地下金属管线平面位置、埋深的方法,利用水平磁场分量70%法确定管线深度的适用条件,分析了特深管线探测的干扰因素,广州市3个特深管线的探测成功实例,说明了方法的良好效果.     

综合物探方法在堤防质量检测中的应用

在堤防质量检测中,地球物理方法能够实现快速、无损的探测,但采用单一物探方法对堤防隐患的判别易形成多解,也很难对堤防质量做出准确分类.本文中应用探地雷达、高密度电法、地震勘探等综合物探方法对大源渡堤防质量进行检测,并以龙荫港以例,通过综合三种物探方法互相参照、相互验证,互为补充,查明了堤防隐患的分布位置与埋深,为堤防质量检测提供一种新的工作方法.     

探测未爆炸弹的地球物理技术综述

采用综合地球物理勘查技术探测未爆炸弹(UXO)具有快速、定位准确和成本低廉的优势.综述了国内外广泛应用的地面高精度磁测法、电磁法以及地质雷达和微重力法在探测UXO中的特点和效果,介绍了国外航空磁测法及航空电磁法探测UXO的进展,并根据某些探测实例阐述了在具体实施过程中应注意的技术问题;提出了适合中国UXO探测的一些措施和建议.     

基于ArcEngine的数字高程模型更新方法研究

采用COM技术,以ARCENGINE所提供的类库和凸包算法,实现了数字高程模型(DEM)数据更新的边界检测和利用矢量地形数据采集更新数字高程模型数据的方法。保证了数字高程模型数据的精度,可以满足数字高程模型的现势性需求。