高光谱大气红外探测仪(AIRS)反演大气不稳定度指数在强对流天气个例中的应用试验

使用探空、NCEP-FNL,数据和高光谱分辨率大气垂直探测仪(AIRS)标准反演数据计算大气不稳定度指数,对2011年6月23日北京强对流天气发生前的本地及上游大气中不稳定能量进行分析研究。分析发现:利用08、14和20时探空数据计算的北京站不稳定度指数显示了在"6·23暴雨"过程发生前后北京上空不稳定能量变化,上游关键区无探空数据;利用NCEP和AIRS数据计算的不稳定度指数显示,强对流天气发生前,在北京的上游关键区大气处于极端不稳定状态(K指数大于40,SI指数小于一5),有利于强对流天气发生。文章的研究结果表明,探空数据时空分辨率较低,不利于监测强对流天气的发生;质量控制后AIRS数据计算的不稳定度指数可以监测对流天气的发生;空间分辨率较低的NCEP数据监测小范围大气不稳定层结能力较低。综上所述,AIRS反演产品具有弥补探空资料时空分辨率不足的优势,利用AIRS L2反演产品计算晴空大气不稳定度指数产品可以监测到"6·23暴雨"天气发生前上游关键区大气层结稳定度状态,为预报员决策提供有效的辅助信息。     

An improved dark object method to retrieve 500 m-resolution AOT (Aerosol Optical Thickness) image from MODIS data: A case study in the Pearl River Delta area,China

This paper presents an improved Dark Dense Vegetation (DDV) method for retrieving 500 m-resolution aerosol optical depth (AOT) based on MOD04-C005 arithmetic with the Moderate Resolution Imaging Spectroradiometer (MODIS) from the National Aeronautics and Space Administration (NASA). The improvements include change of the movement pattern of retrieval window, selection of a more suitable aerosol type, and storage of the look-up table. The method is then applied to obtain the AOT over the Pearl River Delta region (PRD). By comparing the results with the co-temporal ground sunphotometer observations in 2010, the correlation coefficient is found to be 0.794 with RMSE 0.139 and their variations remain consistent. Contrasts between model values in 2008 and MODIS AOT products in the same date also reveal a high accuracy of the improved DDV method. We also performed sensitivity tests to analyze the impacts of several parameters on apparent reflectance at different bands, and the results show that apparent reflectance is much more sensitive to surface reflectance and AOT than to elevation.     

对地勘单位设备管理的思考

设备管理是对设备寿命周期全过程的管理.地勘单位的设备管理,是保证地勘生产的物质基础,是进行现代地勘科研的物质技术手段,它对于地勘单位提高工作效率,确保工作质量,降低工作成本,获取最大经济利益等具有重大意义.     

Retrieval of wheat leaf area index from AWiFS multispectral data using canopy radiative transfer simulation

Accurate representation of leaf area index (LAI) from high resolution satellite observations is obligatory for various modelling exercises and predicting the precise farm productivity. Present study compared the two retrieval approach based on canopy radiative transfer (CRT) method and empirical method using four vegetation indices (VI) (e.g. NDVI, NDWI, RVI and GNDVI) to estimate the wheat LAI. Reflectance observations available at very high (56 m) spatial resolution from Advanced Wide-Field Sensor (AWiFS) sensor onboard Indian Remote Sensing (IRS) P6, Resourcesat-1 satellite was used in this study. This study was performed over two different wheat growing regions, situated in different agro-climatic settings/environments: Trans-Gangetic Plain Region (TGPR) and Central Plateau and Hill Region (CPHR). Forward simulation of canopy reflectances in four AWiFS bands viz. green (0.52–0.59 μm), red (0.62–0.68 μm), NIR (0.77–0.86 μm) and SWIR (1.55–1.70 μm) were carried out to generate the look up table (LUT) using CRT model PROSAIL from all combinations of canopy intrinsic variables. An inversion technique based on minimization of cost function was used to retrieve LAI from LUT and observed AWiFS surface reflectances. Two consecutive wheat growing seasons (November 2005–March 2006 and November 2006–March 2007) datasets were used in this study. The empirical models were developed from first season data and second growing season data used for validation. Among all the models, LAI-NDVI empirical model showed the least RMSE (root mean square error) of 0.54 and 0.51 in both agro-climatic regions respectively. The comparison of PROSAIL retrieved LAI with in situ measurements of 2006–2007 over the two agro-climatic regions produced substantially less RMSE of 0.34 and 0.41 having more R² of 0.91 and 0.95 for TGPR and CPHR respectively in comparison to empirical models. Moreover, CRT retrieved LAI had less value of errors in all the LAI classes contrary to empirical estimates. The PROSAIL based retrieval has potential for operational implementation to determine the regional crop LAI and can be extendible to other regions after rigorous validation exercise.     

基于物联网GIS的消防智能巡检系统设计与实现

消防设施的高效智能管理是衡量城市智慧化水平的重要指标。为了实现该目标,利用物联网技术以及网络地理信息服务技术,设计并实现了集移动巡检终端与网络后台信息管理系统于一体的消防设施智能巡检系统。该系统利用智能无线传感器、RFID以及蓝牙无线通讯等技术,实现消防设施非接触式自动巡检与巡检信息实时传输;通过基于GIS的消防管线与消防拴拓扑结构分层分级可视化,实现消防设施的统一高效管理。相比于现有巡检方式,基于物联网GIS的消防设施智能巡检系统提高了巡检效率与便捷性以及巡检信息的准确性与实时性,为城市中消防设施的实时动态智慧化管理提供了技术支撑和保障。     

中性大气掩星标准反演技术

结合JPL和GFZ的中性大气标准反演算法，发展了上海天文台中性大气掩星标准反演算法流程．对CHAMP观测资料进行中性大气反演，并将反演结果与ECMWF(the European Center for Medium Range Weather Forecasting)的预报大气数据进行比较．作为讨论，指出将来的发展方向．     

基于贝叶斯网络的Web访问模式挖掘模型系统

根据用户的访问记录,以及每次检索输入的关键词、用户的动作来动态更新用户的兴趣点.提出了一个能较好吻合这一思想的数据挖掘模型,以用户的停留时间、访问频率和用户输入的检索关键词为数据对象,进行用户兴趣分析,动态跟踪用户需求意向,简化检索过程,提高WEB资源的使用效率.     

5000 m新型能源勘探智能钻探装备与技术研究

结合我国地下新型能源勘探工作的重大需求,开展了“5000 m新型能源勘探智能钻探装备与技术”的研究,取得了5000 m多功能交流变频电动钻机、多参数孔底自动监测装置、高温环保泥浆及泥浆性能自动测量装置、取心和无心钻进不提钻互换钻具等系列成果,填补了国内空白,推动了新型能源深部钻探技术向智能化方向发展。     

复杂地层顶板大直径高位定向钻孔试验

针对煤矿地层条件复杂,常规钻进工作量大、单孔深度不足、难以成孔、瓦斯抽采浓度低等诸多问题,开展了煤矿复杂地层中施工顶板大直径高位定向钻孔试验。以东保卫煤矿施工为依据,根据煤层顶板地质实际情况,在36号煤层顶板施工6个?120 mm大孔径顶板高位定向钻孔,其中孔深>300 m钻孔成孔率达到83.3%,最大孔深510 m。利用顶板大直径高位定向钻孔进行瓦斯抽采,其抽采浓度比原有工作面常规瓦斯钻孔抽采浓度增加66.7%,取得显著瓦斯抽采效果。顶板大直径高位定向钻孔的成功应用,为东保卫煤矿以及相似条件矿区推广应用提供了技术支撑。     

基于星载激光雷达ICESat-2的雪深监测方法研究

目前,被动微波数据是积雪深度反演的主要数据源,受其较粗空间分辨率的影响,反演雪深存在较大的不确定性。激光雷达由于其较高的测高精度,在雪深监测方面具有一定的潜力,基于星载激光雷达ICESat-2数据对北疆地区2018年10月至2019年9月积雪季的雪深进行了提取。由于很难获取ICESat-2轨迹点的雪深观测资料,因此首先利用地面雪深观测数据对目前流行的被动微波雪深反演产品进行验证,获取精度可靠的雪深产品并与发展的ICESat-2监测雪深数据产品进行对比。结果表明：AMSR2雪深产品在北疆地区误差较大,整体存在高估现象,中国雪深长时间序列雪深产品精度相对可靠,以作为对比ICESat-2模拟雪深的参考数据;ICESat-2雪深与中国雪深长时间序列雪深产品在空间上以及变化趋势方面吻合度较高,但ICESat-2雪深变化更加连续,说明ICESat-2激光雷达数据不但可以提取区域积雪的深度,对积雪深度的空间变化也比被动微波数据更加敏感,可以获取更加详细的积雪深度空间变化细节,为精细化的积雪深度空间分布提供数据支撑。