Use of LiDAR-derived DEM and a stream length-gradient index approach to investigation of landslides in Zagros Mountains,Iran

This paper presents an approach to stream length-gradient index analysis to identify tectonic signatures. The graded profile of the Dez River in Zagros Mountains, Iran, indicates that the area has been tectonically disturbed, and it triggers landslide hazards. The high-gradient index shows that a steeper gradient could be potentially a signature for landslides identification. The digital surface models acquired by airborne LiDAR were used in this study to generate the HRDEM. Our result shows a great potential for improving landslide investigations by implementing stream length-gradient index derived from the HRDEM in conjunction with the landslide inventories data-set in the GIS environment. We also identified a correlation between the stream length-gradient index and the graded topographic profile with slopes and landslides. This empirical approach was verified by geodata analytics and landslide inventories data-set in conjunction with field observations. This study has identified the locations of high-gradient indices with susceptible to landslides.     

Examining human heat stress with remote sensing technology

Heat stress as an environmental hazard which can seriously affect productivity, health, or even survival of individuals has long been studied. Despite the endeavors that have been made to address the issue quantitatively with various heat stress indices, they are often measured at scatter sites. This research devotes to revealing human heat stress within continuous space with remote sensing technology. The study began with the retrieval of dry-bulb temperature from land surface temperature (LST) with empirical models. As wet-bulb temperature was calculated from dry-bulb temperature and relative humidity, discomfort index (DI) as an indicator of heat stress was revealed for the study area at 1 km spatial resolution for three summer days. Results indicated that DI can be derived within continuous space with remotely sensed data, and its spatial distribution can be dramatically affected by relative humidity. Further comparison between DI and LST indicated that LST as a widely utilized indicator of surface thermal condition fails to address human heat stress as environmental factors such as relative humidity are not taken into account.     

太行山中段城南庄一带隐伏岩体及找矿前景分析

麻棚和赤瓦屋岩体都位于太行山中段热液金属矿成矿区内,在其周围已发现石湖石英脉大型金矿等60余处热液型矿床(点),其深部和外围可能存在找矿前景。本文通过探讨太行山中段城南庄一带遥感环形构造和重力负场特征与金属矿床和岩体的耦合关系,从城南庄卫星式-多层蘑菇群式遥感环形构造群、重力负场、中酸性岩脉侵入和温泉五种证据,推测城南庄深部存在比麻棚和赤瓦屋岩体大近六倍、面积约700 km~2的中酸性隐伏岩体—城南庄隐伏岩体。城南庄隐伏岩体边界基本与布格重力负异常边界吻合,呈长轴北东向宽缓带状展布,向南西方向倾伏,北侧埋深较浅、南侧埋深较深。城南庄隐伏岩体边部(特别是产状缓外倾,具有良好成矿空间的区域)和顶部与围岩的接触带位置、环形构造形成的晚期"小岩体"内部及附近位置和中酸性岩脉附近位置是寻找热液型矿床的有利部位。     

成层软土地基预固结处理后桩基水平承载力估算方法

目前通过对软土地基预加固处理来提高桩基水平承载力已被工程界认可,但如何在工程前期设计过程中估算软土地基预处理后桩基水平承载力提高值仍是技术难点。基于此,参考Bowles[1]的地基土水平抗力计算式,同时考虑成层软土地基预排水固结处理影响,通过数学推导,推求出根据原状软土室内土工试验抗剪强度指标及预加固处理时间,估算软土地基预处理后桩基水平承载力提高值的实用计算方法。考虑桩侧土弹塑性屈服影响,推导出成层软土中水平受荷桩弹塑性解析解及塑性区深度的计算式,给出了桩顶水平位移、桩身最大弯矩的无量纲计算式及相关计算源代码。依托于浙江省某水闸桩基工程案例,根据提出的计算方法对桩基水平承载力、桩顶水平位移及桩身最大弯矩等性状进行预估计算,并与地基预处理前、后现场试桩检测值进行验证对比,认为桩基水平承载力、桩顶水平位移及桩身最大弯矩等预估计算成果与工程现场试桩的检测值较接近,对类似工程设计具有较好的参考价值。     

基于多源遥感影像的长春市城市建成区提取

夜光遥感影像记录的城市灯光与人类活动密切相关,已广泛应用于城市信息提取。珞珈一号作为新一代夜光遥感数据源,比以往的夜光数据具有更高的空间分辨率和光谱分辨率,可以更清晰地表达城市建成区范围和内部结构。本文利用珞珈一号夜光遥感影像,通过人类居住指数（human settlement index, HSI）、植被覆盖和建筑共同校正的城市夜光指数（vegetation and build adjusted nighttime light urban index, VBANUI）及支持向量机（support vector machine, SVM）监督分类3种方法对长春市城市建成区进行提取,并与利用NPP/VIIRS（suomi national polar-orbiting partnership/visible infrared imaging radiometer suite）夜光遥感影像、采用同样方法得到的结果对比。结果显示：本文提出的VBANUI提高了传统植被覆盖校正的城市夜光指数（vegetation adjusted nighttime light urban index, VANUI）的提取精度,使用珞珈一号夜光遥感影像通过VBANUI提取的城市建成区结果最优,其Kappa系数为0.80,总体分类精度为90.74%;使用珞珈一号和NPP/VIIRS夜光遥感影像通过HSI按最佳阈值提取城市建成区的Kappa系数分别为0.75和0.72,总体分类精度分别为88.27%和86.54%;复合数据的SVM监督分类法中Landsat-NDBI、Landsat-NDBI-VIIRS、Landsat-NDBI-LJ和Landsat-NDBI-LJlog的Kappa系数分别为0.602、0.627、0.643和0.681,总体分类精度分别为81.11%、81.52%、82.25%和84.48%。研究结果表明：3种提取方法下,均为使用珞珈一号夜光遥感影像的结果优于使用NPP/VIIRS夜光遥感影像的结果,证明相比于NPP/VIIRS夜光遥感影像,珞珈一号夜光遥感影像更适用于城市尺度的建成区范围提取。     

滑坡对降雨响应的多指标监测及综合预警探析:以赣南罗坳滑坡为例

降雨量和位移是当前降雨型滑坡监测预警最常用的指标。然而,降雨量和位移监测结果只能反映降雨作用下滑坡的变形情况,不能揭示滑坡内在物理力学性状对降雨的响应。因此,除降雨量和位移监测之外,建立包括体积含水率、基质吸力等反映滑坡动态演化过程的关键指标监测体系必将成为今后更真实地把握滑坡内在演化趋势、更准确地建立滑坡综合预警判据的最有效手段。笔者对赣南地区典型降雨型滑坡进行了多指标监测及综合预警示范研究。结果表明:(1)在降雨条件下滑坡土体内部体积含水率、基质吸力和温度等多指标均产生有规律的动态响应;(2)随着降雨的持续,滑体体积含水率与基质吸力的变化均具有显著的滞后现象;(3)体积含水率和基质吸力变化速率与滑体位移具有显著的正相关性;(4)滑体温度分布变化规律受大气温度和体积含水率的共同影响。以实测数据的滑坡稳定性分析为基准,在考虑实际降雨入渗深度与滑坡稳定性的关联度上,建立了包括日降雨量、体积含水率增加速率、基质吸力减小速率以及位移速度多元指标预警方法体系,提出了基于关键指标综合预警体系及确定方法,旨在为降雨滑坡准确预警提供新模式。     

Brittleness index predictions from Lower Barnett Shale well-log data applying an optimized data matching algorithm at various sampling densities

The capability of accurately predicting mineralogical brittleness index(BI)from basic suites of well logs is desir-able as it provides a useful indicator of the fracability of tight formations.Measuring mineralogical components in rocks is expensive and time consuming.However,the basic well log curves are not well correlated with BI so correlation-based,machine-learning methods are not able to derive highly accurate BI predictions using such data.A correlation-free,optimized data-matching algorithm is configured to predict BI on a supervised basis from well log and core data available from two published wells in the Lower Barnett Shale Formation(Texas).This transparent open box(TOB)algorithm matches data records by calculating the sum of squared errors be-tween their variables and selecting the best matches as those with the minimum squared errors.It then applies optimizers to adjust weights applied to individual variable errors to minimize the root mean square error(RMSE)between calculated and predicted(BI).The prediction accuracy achieved by TOB using just five well logs(Gr,pb,Ns,Rs,Dt)to predict BI is dependent on the density of data records sampled.At a sampling density of about one sample per 0.5 ft BI is predicted with RMSE～0.056 and R2～0.790.At a sampling density of about one sample per 0.1 ft BI is predicted with RMSE～0.008 and R2～0.995.Adding a stratigraphic height index as an additional(sixth)input variable method improves BI prediction accuracy to RMSE～0.003 and R2～0.999 for the two wells with only 1 record in 10,000 yielding a BI prediction error of＞±0.1.The model has the potential to be applied in an unsupervised basis to predict BI from basic well log data in surrounding wells lacking mineralogical measure-ments but with similar lithofacies and burial histories.The method could also be extended to predict elastic rock properties in and seismic attributes from wells and seismic data to improve the precision of brittleness index and fracability mapping spatially.     

2017年辽宁省春夏季精细化气象干旱监测评估

基于辽宁省1114个国家级和区域级地面台站1961年以来的逐日气温和降水观测资料,利用距离平方反比法差值生成了1717个乡镇的气象资料序列,采用气象干旱综合监测指数统计分析了辽宁省2017年4—8月精细化到乡镇的气象干旱特征。结果表明:2017年辽宁省春夏季异常高温,同时降水异常偏少,致使气象干旱不断发展;干旱在4月5日前从中部和北部开始,4月末扩展到西部,5—6月再向东南发展,波及88%的乡镇,7月以来气象干旱程度开始减轻;气象干旱持续时间长的乡镇主要集中在中部和北部,最长持续时间153d;受气温偏高和降水过程的影响,中度以上气象干旱面积呈阶段性变化,且极端干旱的发展伴随高温时段。由于气象干旱不同于农业干旱,在开展为农服务时要因地制宜采取应对措施。     

四川省旅游气候舒适度评价

为了更好地发展旅游事业,本文以四川省2006~2016年21个站点的气象数据为基础数据,运用奥利弗温湿指数和IDW空间插值法对四川省旅游气候舒适度进行评价。结果表明:(1)从总体上看,四川省旅游气候舒适度差异显著,呈现出西部较高、东部较低的特征;(2)从季节上看,四川省春、秋季舒适度较高,最适合人们旅游;夏、冬季舒适度较差,最不适合旅游;(3)从旅游地上看,除了甘孜州、阿坝州和凉山州的最舒适时期为7月,最不舒适时期为1月。四川省典型旅游地最舒适时期大都为4月和10月,最不舒适时期主要为1月和7月。因此,除甘孜州,阿坝州和凉山州外,4月和10月四川省适合旅游;相反,1月和7月四川省不适合旅游。     

高原季风特征及其与东亚夏季风关系的研究

利用ERA-Interim的位势高度场、温度场和风场再分析资料,计算了1988-2017年的传统高原季风指数(Trational Plateau Monsoon Index,TPMI)和动态高原季风指数(Dynamic Plateau Monsoon Index,DPMI),分析了高原季风的空间分布特征和时间演变规律,结合东亚夏季风指数(East Asian Summer Monsoon Index,EASMI),探讨了高原季风与东亚季风的关系。研究表明:(1)高原夏季风从4月开始形成,暖性低值系统在高原上生成;6月暖性低压系统中心形成并达到最强,此时高原夏季风强度也达到最大;10月暖性闭合低压系统向东北方向移动且强度也随之减弱并退出,高原夏季风结束。(2)DPMI和EASMI具有明显的年际变化特征,在关键年高原夏季风和东亚夏季风的强度表现一致。(3)中纬度受东亚季风所影响区域的位势高度场和青藏高原区域的位势高度场均处于同一正相关区域,而且超前两个月的DPMI同EASMI的相关系数最大,表明高原夏季风对东亚夏季风具有一定的指示意义。(4)东亚夏季风经圈环流受高原温度场变化的影响而移动,高原夏季风的低压系统与高原温度场关系密切。