Nonlinearly Constrained Optimization Theory to Interpret Magnetic Anomalies Due to Vertical Faults and Thin Dikes

A new and simple method based on a nonlinearly mathematical optimization concept has been proposed in this research to interpret magnetic anomalies due to vertical faults and thin dikes. This proposed interpretative method consists of three main steps. The first step is to formulate nonlinearly constrained optimization problems to describe the geophysical problems related to the studied structures. The second step is to suggest an interior penalty function in order to convert these nonlinearly constrained optimization problems into nonlinearly unconstrained optimization ones. The third step is to solve the converted nonlinearly unconstrained optimization problems by using the famous Hooke and Jeevess algorithm in order to estimate the geophysical parameters of the studied structures such as: depth, amplitude coefficient, and index parameter. The Hooke and Jeevess algorithm is purposely chosen for being robust and also its application to magnetic data converges rapidly towards the optimal estimation of parameters. This method was first tested on theoretical models with different random noise, where a very close agreement was obtained between the assumed and evaluated parameters. The validity of this new method was also tested on practical field examples taken from Australia, India, United States, and Brazil, where available magnetic data existed and was previously analyzed by different interpretative methods. The agreement between the results obtained by our developed method and those obtained by the other geophysical methods is good. The advantages of this newly proposed method, compared with the other published interpretative methods, also have been discussed and demonstrated.     

Nouvelles données sur le téphra de Sarliève et le téphra CF7, marqueurs chrono-stratigraphiques de Grande Limagne (Massif central,France)

A trachytic tephra, discovered in the ancient lake of Sarliève, ‘Grande Limagne’, has been dated using the thermoluminescence technique. The obtained age, 16±4 ka ($\text{2}\text{σ}$), is older than that of the trachytic volcanoes of the Cha??ne des Puys, the ashes of which have already been locally recognised in the region. Its analysis confirms its originality. In the course of the comparisons made to search for its spring, it appears that the wide-dispersion tephra CF7, beforehand correlated by hypothesis to the Puy de Clierzou, probably originates from the Kilian crater or the Puy de Vasset. To cite this article: D. Miallier et al., C. R. Geoscience 336 (2004).     

苏州下垫面格局演变及其局地热环境效应

以苏州为研究区域,选择1986年Landsat TM、2006年Landsat ETM+遥感图像为主要数据源,分别提取下垫面类型和地表温度,研究景观格局指数的粒度效应,并在适宜粒度下分析景观格局的演变特征,进而研究其与热环境变化之间的关系。结果表明,研究区20多年来景观破碎化程度、斑块形状复杂程度与景观多样性变大,而聚集程度变低,热场变异指数增大区域的景观格局指数变化更为明显,这说明下垫面格局演变对热环境变化具有一定的影响作用。     

武汉市10个主要极端天气气候指数变化趋势分析

根据武汉市1951—2007年逐日气温、降水量计算分析了10个极端天气气候指数的变化特征。结果表明:1)4个气温指数中,年及四季高、低温阈值均为上升趋势,并造成最长热浪天数的延长和霜冻日数的减少;低温阈值升速明显快于高温阈值,高温阈值仅在春季变化显著,最长热浪天数仅在冬季变化显著;低温阈值则为极显著上升趋势,尤其是年和冬季,造成"热春"、"暖冬"频繁;暖夜、闷热、傍晚至夜间的强对流等显著增多,暖日、高温热浪增加,霜冻日大幅减少。2)6个极端降水指数以增趋势为主,其中强降水阈值、比例、日数以及最大5日降水量在冬季增趋势最明显,仅夏季强降水阈值、比例略有减小,冬季日降水强度的增大趋势、夏季持续干期的缩短趋势显著性水平分别可达0.1、0.01。3)一些气温指数在1980—1990年代发生突变,而降水指数未现突变。     

北京城市高温遥感指标初探与时空格局分析

利用北京高温天气下的NOAA18/AVHRR卫星资料与气象台站资料,分析了日最高气温与遥感反演的城市地表温度的关系,初步确定了地表高温阈值并建立了高温遥感指标,并利用1989~2008年(缺2002年)6~9月NOAA/AVHRR资料开展了北京地区高温时空格局分析研究。指标初步研究表明:北京气温高温值为35、37、40°C对应的遥感地表高温值分别为44、47、52°C,可以较好地适用于北京平原地区;利用该阈值建立的地表高温强度指标(LSHI)对北京平原高温的监测与气象台站高温监测基本一致,而高温比例指数指标(LSHP)能有效反映出城市高温空间强弱和时间差异。北京遥感地表高温空间格局分析显示:夏季(6~8月)旬平均遥感地表温度≥44°C年出现概率不超过50%,广泛分布于城区和平原区;旬平均遥感地表温度≥47°C年出现概率不超过40%,集中于北京五环内;旬平均遥感地表温度≥52°C年出现概率不超过15%,集中于城区;6~9月高温出现的概率高值区一般都集中于五环内,其中旬平均遥感地表温度≥44°C、≥47°C、≥52°C的出现概率分别为80%~100%、60%~80%、10%~40%。     

基于地震数据专家的子午链台站地磁自动化产品系统设计与实现

基于对子午链台站地震地磁前兆异常以及地球空间环境变化等研究方向的需求分析,利用网络、大数据、云计算等新技术,结合地震数据专家（DatistEQ）软件,设计子午链台站地磁指数报告自动产出系统。该系统通过低代码、敏捷式开发工作流程,连接不同功能节点,可以实现用户定制化、数据标准化、功能智能化的系统报告产出。通过本地或者云端一键流程化工作,将不同类型的数据发送到科研工作者或其他需求者,简化工作流程,优化数据处理,实现高效率产品产出。     

Sentinel-2数据的冬小麦地上干生物量估算及评价

作物生物量快速精确的监测对于农业资源的合理利用与农田的精准管理具有重要意义。近年来,遥感技术因其独特的优势已被广泛用于作物生物量的估算中。本文主要针对不同宽波段植被指数在冬小麦生物量(文中的生物量均是指地上干生物量)估算方面的表现进行探索。首先利用欧洲空间局最新的Sentinel-2A卫星数据提取出17种常见的植被指数,之后分别构建其与相应时期内采集的冬小麦地上生物量间的最优估算模型,通过分析两者间的相关性与敏感性,获取适宜进行生物量估算的指数。最后,绘制了研究区的生物量空间分布图。结果表明,所选的植被指数均与生物量显著相关。其中,红边叶绿素指数(CI_(re))与生物量的估算精度最高(决定性系数R~2为0.83;均方根误差RMSE为180.29 g·m~(–2))。虽然相关性较高,但部分指数,如归一化差值植被指数(NDVI)等在生物量较高时会出现饱和现象,从而导致生物量的低估。而加入红边波段的指数不仅能够延缓指数的饱和趋势,而且能够提高反演精度。此外,通过敏感性分析发现,归一化差值指数和比值指数分别在作物生长的早期和中后期对生物量的变化保持较高的敏感性。由于红边比值指数(SR_(re))和MERIS叶绿素敏感指数(MTCI)在冬小麦全生长季内一直对生物量的变化保持高灵敏性,二者是生物量估算中最为稳定的指数。