城市泥石流易损性评价

本文探讨了城市泥石流易损性评价的系统方法,该方法包括:易损体类型划分,易损体数量调查统计,评价模型构建和核算易损体价值等主要内容.目前对地观测技术可以更精确地用于城市泥石流易损性分析,并对城市居民房屋、基础设施和农业用地等进行易损性评价.本研究以美国高分辨率的"快鸟"卫星影象为数据源,完成了研究区的土地覆盖类型遥感解译,应用地理信息系统提供的统计和分析工具,完成了研究区不同土地覆盖类型的城市泥石流易损性计算和评价.     

Improvements in Air Quality Modelling by Using Surface Boundary Layer Parameters derived from Satellite Land Cover Data

Many atmospheric dispersion models include only simpletreatment of surface features to estimate the wind profilesand stability parameters. Detailed characterisation of theland cover, particularly in large and complex urbanconurbations, is especially important, as the surfacefeatures can vary significantly over the area. This paperdiscusses the use of satellite land cover data to derivespatially resolved surface boundary layer (SBL) parameters.These parameters have been used in an air quality model,PEARL (Prediction Air Quality in Urban and RegionalLocations) for estimating monthly and annual COconcentrations. Land cover data, derived from LANDSATThematic Mapper Imagery, has been used to estimate SBLparameters (surface roughness length, albeedo, Bowen ratioand anthropogenic heat flux) for a study area of 10000km² encompassing Greater London and the surroundingcounties. The SBL parameters have been assigned according tomajor land cover types for the whole area at a spatialresolution of 1 × 1 km. Predictions from two versions of the PEARL model (one with land cover data and one without)have been compared with each other and with measured data forannual and monthly CO concentrations from seven London airquality monitoring sites. This comparison shows thatdifferences between predicted and observed values can bereduced by up to a factor of three. The use of SBLparameters derived from land cover data also yields moredetailed predicted annual CO spatial patterns especially inand around suburban areas. The performance of both versionsof the model for monthly CO concentrations has been comparedwith a range of statistical measures. This comparisonconfirms that improved agreement is observed betweenmodelled and measured monthly CO concentrations when use ismade of spatially resolved SBL parameters.     

基于卫星测高数据的2002～2018年太湖水位变化监测

针对传统水位监测方法的弊端以及太湖水位变化监测的现实需求,基于Envisat和Cryosat-2测高数据,采用Morlet小波分析、Mann-Kendall检验法研究2002年6月～2018年12月近20a的水位以及周期变化,并应用实测数据进行精度验证,从气象因素和人为影响两方面分析其不同时间尺度的变化趋势以及原因.结...     

智能巡检机器人在自然环境试验中的应用探讨

目的 探索建立自然环境试验智能巡检系统,使用机器人替代部分人工巡检工作。方法 通过分析巡检作业环境和巡检任务,确定智能巡检机器人的功能要求和技术参数,进而开展机器人本体结构设计,融合控制后台、远程数据库等设备,实现智能巡检系统构建。结果 开展了智能巡检数据采集的使用验证,巡检机器人采集的样品图像对焦清晰、分辨率高,样品在图像中的位置大小合理,腐蚀特征展示清楚。巡检系统可对样品图像进行自动分割和智能识别,对蚀点、流痕等损伤特征识别准确,精度可达0.1%。结论 智能巡检系统可以满足自然环境试验的巡检要求,替代人工完成部分巡检工作,智能巡检数据便于入库和使用挖掘,对于自然环境试验的数字化转型有积极的推动作用。     

东北冷涡下两次雷电过程特性对比分析

利用卫星、闪电和电场等资料对2009年6月江苏的两次受东北冷涡影响所致的雷电过程进行对比分析,探讨了发生雷电过程的天气形势和卫星产品等对强对流天气的指示作用,初步得出了同一环流背景下的两次雷电过程的特征:两次雷电过程都具备了较好的不稳定条件,但由于能量分布的差异,过程影响范围有所不同;5日雷电过程伴随冰雹,其正闪比明显高于只有闪电发生的21日;相当黑体亮度温度高低预示着对流活动活跃程度,大部分闪电分布在云顶温度低值区,或者温度梯度较大的对流旺盛区域;两次过程电场快变抖动都提前于地闪发生。     

遥感技术在城市建筑震害预测中的应用研究

长期以来,在城市的震害预测研究工作中,建筑物属性信息的主要获取方法是基于人工调查的传统方式。近年来,随着遥感技术的发展,尤其是高分辨率民用遥感卫星的成功发射,使得利用遥感技术进行城市震害预测成为可能。鉴于传统的信息获取方式存在的费时费力,数据获取周期长,数据信息时效性差等缺点,以郑州市中牟县的部分住宅区为例,对高分辨率遥感影像在城市震害预测中的应用做了相应研究。     

青藏高原东北侧突发性暴雨特征综合分析

对1970-2007年发生在青藏高原东北侧陕西的突发性暴雨研究发现,其夜间降水特点明显,对流层中层较强的偏南气流是突发性暴雨水汽输送贡献最大者和低层辐合的主要动力来源。偏南气流北伸的位置决定突发性暴雨落区偏南或偏北,300hPa一致的纬向12～20m·s-1强风速带为突发性暴雨提供高层抽吸作用。上述两点对突发性暴雨落区有一定的预报指示意义。云图分析显示,突发性暴雨多有中尺度云团配合,上升运动最大值的高度层与突发性暴雨落区地域位置有关。     

基于ai智能图像的工控火电现场爆炸风险评估

对工控火电现场爆炸风险进行评估时,若采用人工识别现场图片信息的方法,容易导致现场图片特征信息采集不准确,存在评估耗时长、评估效率低和评估结果不准确的问题。针对该问题,提出1种基于ai智能图像的工控火电现场爆炸风险评估方法;通过自适应融合方法提取工控火电现场ai智能图像中的特征信息,根据特征信息对工控火电现场ai智能图像进行识别;结合层次分析法和问卷调查法,选取工控火电现场爆炸风险评估指标;在图像识别结果的基础上,通过风险等级集合、评估指标权重,建立工控火电现场爆炸风险评估模型,并与另外2种工控火电现场爆炸风险评估方法进行了对比。研究结果表明:所建方法能够缩短评估时间,且评估效率较高、评估结果准确率较高。     

A Special Vegetation Index for the Weed Detection in Sensor Based Precision Agriculture

Many technologies in precision agriculture (PA) require image analysis and image- processing with weed and background differentiations. The detection of weeds on mulched cropland is one important image-processing task for sensor based precision herbicide applications. The article introduces a special vegetation index, the Difference Index with Red Threshold (DIRT), for the weed detection on mulched croplands. Experimental investigations in weed detection on mulched areas point out that the DIRT performs better than the Normalized Difference Vegetation Index (NDVI). The result of the evaluation with four different decision criteria indicate, that the new DIRT gives the highest reliability in weed/background differentiation on mulched areas. While using the same spectral bands (infrared and red) as the NDVI, the new DIRT is more suitable for weed detection than the other vegetation indices and requires only a small amount of additional calculation power. The new vegetation index DIRT was tested on mulched areas during automatic ratings with a special weed camera system. The test results compare the new DIRT and three other decision criteria: the difference between infrared and red intensity (Diff), the soil-adjusted quotient between infrared and red intensity (Quotient) and the NDVI. The decision criteria were compared with the definition of a worse case decision quality parameter Q, suitable for mulched croplands. Although this new index DIRT needs further testing, the index seems to be a good decision criterion for the weed detection on mulched areas and should also be useful for other image processing applications in precision agriculture. The weed detection hardware and the PC program for the weed image processing were developed with funds from the German Federal Ministry of Education and Research (BMBF).     

Retrieval And Monitoring of Atmospheric Trace Gas Concentrations in Nadir and Limb Geometry Using the Space-Borne Sciamachy Instrument

The Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) onboard the European Envisat spacecraft performs continuous spectral observations of reflected, scattered and transmitted sunlight in various observation geometries. A unique feature of SCIAMACHY is the capability of probing the atmosphere in three different observation geometries:The nadir, limb, and occultation measurement modes. In nadir mode, column densities of trace gases are retrieved with a spatial resolution of typically 30× 60 km using the Differential Optical Absorption Spectroscopy (DOAS) technique (Platt and Perner, 1983). Alternating with the nadir measurement, vertical profiles of absorber concentration in the stratosphere are derived in limb and occultation. In this paper we present an overview over some applications of SCIAMACHY data in space-based monitoring of atmospheric pollution. The DOAS algorithms for the retrieval of total column amounts from nadir spectra are briefly described and case studies of pollution events are presented. We also illustrate the technique used to derive stratospheric concentration profiles from limb observations and show comparisons with other remote sensing systems. Special emphasis will be given to techniques, which take advantage of SCIAMACHY's different viewing geometries. In particular, we will discuss the potential and limits of strategies to infer tropospheric abundances of O₃and NO₂.