无人机与卫星影像的叶面积指数遥感反演研究

针对卫星遥感影像获取的叶面积指数精度较低的问题,该文结合无人机低空航拍影像和卫星影像,基于最小二乘法建立了一种叶面积指数遥感反演方法,并与卫星影像像元二分模型进行了比较。结果表明:从单一植被类型到整体植被叶面积指数的反演,新方法均优于卫星影像的像元二分法,两者整体相对误差分别为27%和35%。4种植被类型中,草本植物对模型的反演精度影响较大,两者相对误差分别为32%和56%。使用该方法准确计算了长汀县相关区域叶面积指数分布,与他人结果一致。该方法提高了卫星遥感影像获取叶面积指数的精度,为大面积高精度估算区域植被提供了一种方法。     

东亚多卫星集成降水业务系统

静止气象卫星与极轨气象卫星的集成应用,能够充分发挥静止气象卫星与极轨气象卫星的各自优势。东亚多卫星集成降水业务系统采用拉格朗日集成算法,利用静止气象卫星的红外观测信息计算的红外冷云移动矢量,为极轨气象卫星微波降水的发展提供约束条件,实现了静止气象卫星红外观测信息与极轨气象卫星微波降水的集成,综合了两类卫星观测的优势。同时业务系统的设计考虑了多数据分级管理、多业务单元的协同工作和插件式的系统整体框架,为业务系统合理、快速处理多种来源的红外观测数据、微波降水数据,以及未来的数据更迭和算法更新提供了必要保障。     

Abundances of Jupiter's trace hydrocarbons from Voyager and Cassini

The flybys of Jupiter by the Voyager spacecraft in 1979, and over two decades later by Cassini in 2000, have provided us with unique datasets from two different epochs, allowing the investigation of seasonal change in the atmosphere. In this paper we model zonal averages of thermal infrared spectra from the two instruments, Voyager 1 IRIS and Cassini CIRS, to retrieve the vertical and meridional profiles of temperature, and the abundances of the two minor hydrocarbons, acetylene (C₂H₂) and ethane (C₂H₆). The spatial variation of these gases is controlled by both chemistry and dynamics, and therefore their observed distribution gives us an insight into both processes. We find that the two gases paint quite different pictures of seasonal change. Whilst the 2-D cross-section of C₂H₆ abundance is slightly increased and more symmetric in 2000 (northern summer solstice) compared to 1979 (northern fall equinox), the major trend of equator to pole increase remains. For C₂H₂ on the other hand, the Voyager epoch exhibits almost no latitudinal variation, whilst the Cassini era shows a marked decrease polewards in both hemispheres. At the present time, these experimental findings are in advance of interpretation, as there are no published models of 2-D Jovian seasonal chemical variation available for comparison.     

“SZ-4”飞船高度计天线指向角反演方法

利用2003年2月7到8日“SZ-4”高度计的波形数据,经过波形数据预处理(波形为1 s的平均、去除热噪声和波形归一化)后,对海面回波波形后沿进行拟合,计算出了高度计天线的指向角,结果表明,“SZ-4”飞船高度计天线的指向角几乎全部在0.024°以内,天线指向在计算时间内比较稳定.     

青藏高原实测剖面数据管理与检索系统开发的方法与意义

青藏高原实测剖面检索数据管理与检索系统是利用ACCESS软件建立青藏高原实测剖面数据库,采用ArcGIS软件形成了青藏高原实测剖面分布图,利用WEBGIS技术实现网络发布。该系统主要为服务对象提供实测地层剖面数据的检索与查询服务,提供地图查询、浏览、打印服务,同时还提供青藏高原地质背景知识的服务。该系统提供的服务比传统的资料服务有着更多的优点:访问范围更加广泛,平台独立,操作简单,计算模式灵活高效。     

协同多时相波谱特征的不透水面信息级联提取

不透水面作为反应城市表征变化和区域城镇化的重要技术指标,其位置、图斑大小、空间分布等信息在地表水热循环和能量平衡等领域被广泛需求。传统方法大都基于单一时相信息提取不透水面,而忽略多时相所蕴含的丰富信息。因此,本文提出多时相信息融合的不透水面级联提取方法,利用Landsat-8 OLI遥感影像分析归一化植被指数（Normalized Difference Vegetation Index, NDVI）、改进的归一化水体指数（Modified Normalized Difference Water Index, MNDWI）和归一化建筑指数（Normalized Difference Building Index, NDBI）年内时序变化特点和典型地物间多时相波谱曲线的协同特征,并归纳不透水面多时相变化规律;再根据先验知识所获取的有效地表信息,进行多时相分级提取不透水面信息。此外,基于实地考察数据和同期2 m GF-1遥感影像屏幕数字化生成30 m不透水面图斑,进行精度验证、分析和对比单时相、四季相及多时相3种时序情况下的提取精度。结果表明：单时相提取不透水面总精度最低,四季相提取精度优于单时相,而多时相提取精度最高（精度可达93.66%,Kappa系数为0.81）。本方法在偏远城镇不透水面的有效识别中显露潜在优势,可为不透水面提取方法融合时序波谱特征提供新思路。     

利用HY-2微波辐射计数据反演北极区域海冰密集度方法研究

HY-2是中国自主研发的海洋卫星。 本文研究了利用HY-2卫星扫描微波辐射计亮温数据反演北极海冰密集度的方法。参考NASA TEAM方法,我们对典型海区光谱梯度率和极化梯度率进行了统计分析,确定了计算海冰密集度所需的亮温特征值;利用天气滤波器有效去除了开阔海域由于大气中水蒸气、云中液态水、降雨等现象引起的海冰密集度计算错误。本文计算了2012年全年的北极海冰密集度产品并对产品精度进行了初步验证,验证结果表明：三个海冰类型已知区域的海冰密集度结果与理想值比较接近,多年冰密集度的反演精度需要进一步提高;本文结果与美国冰雪数据中心和德国不来梅大学提供的两种业务化海冰密集度产品一致。本研究为利用HY-2卫星监测极区海冰密集度变化,发布实时产品奠定了基础。     

毫米波云雷达功率谱密度数据的检验和 在弱降水滴谱反演中的应用研究

本文首先利用数值模拟的方法,分析了利用毫米波云雷达功率谱密度反演雨滴谱时,降水粒子米散射效应、空气湍流、空气上升速度等对雨滴谱和液态水含量等参数反演的影响;建立了功率谱密度处理及其直接反演雨滴谱、液态水含量、降水强度和空气上升速度的方法;并利用2012年7月在云南腾冲观测的二次弱降水数据,采用毫米波雷达和Ku波段微降水雷达观测的回波强度、径向速度垂直廓线以及780 m高度上的功率谱密度对比的方法,以及毫米波云雷达观测的780 m高度上功率谱密度、回波强度与地面雨滴谱计算得到的这些量的对比方法,分析了毫米波雷达数据的可靠性;并将780 m高度上毫米波雷达反演的雨滴谱与地面雨滴谱数据进行了对比,分析了毫米波雷达反演的雨滴谱的准确性;分析了毫米波雷达回波强度偏弱的原因,讨论了该高度以下降水对毫米波雷达衰减的影响。结果表明:空气湍流对弱降水微物理参数反演影响不大,而空气上升速度和米散射效应均对反演结果有一定影响;毫米波雷达观测到的径向速度和功率谱密度与微降水雷达比较一致,回波强度的垂直廓线的形状与微降水雷达也比较一致,但毫米波雷达观测的回波强度偏弱;与雨滴谱计算值相比,毫米波雷达观测的低层的回波强度也偏弱,天线上的积水是造成毫米波雷达回波强度变弱的主要原因。毫米波雷达观测的低层的功率谱密度与地面雨滴谱观测的数据形状比较一致,但有一定的位移。毫米波雷达反演的雨滴谱与地面观测的谱型和粒子大小也比较一致。这些结果初步验证了毫米波雷达观测的功率谱密度及其反演方法的可靠性。     

A method for sea surface wind field retrieval from SAR image mode data

To retrieve wind field from SAR images, the development for surface wind field retrieval from SAR images based on the improvement of new inversion model is present. Geophysical Model Functions(GMFs) have been widely applied for wind field retrieval from SAR images. Among them CMOD4 has a good performance under low and moderate wind conditions. Although CMOD5 is developed recently with a more fundamental basis, it has ambiguity of wind speed and a shape gradient of normalized radar cross section under low wind speed condition. This study proposes a method of wind field retrieval from SAR image by combining CMOD5 and CMOD4 Five VV-polarisation RADARSAT2 SAR images are implemented for validation and the retrieval results by a combination method(CMOD5 and CMOD4) together with CMOD4 GMF are compared with QuikSCAT wind data. The root-mean-square error(RMSE) of wind speed is 0.75 m s-1 with correlation coefficient 0.84 using the combination method and the RMSE of wind speed is 1.01 m s-1 with correlation coefficient 0.72 using CMOD4 GMF alone for those cases. The proposed method can be applied to SAR image for avoiding the internal defect in CMOD5 under low wind speed condition.     

星载激光雷达卫星海面风场反演算法研究

The principal purpose of this paper is to extract entire sea surface wind＇s information from spaceborne lidar, and particularly to utilize a appropriate algorithm for removing the interference information due to white caps and subsurface water. Wind speeds are obtained through empirical relationship with sea surface mean square slopes. Wind directions are derived from relationship between wind speeds and wind directions im plied in CMOD5n geophysical models function （GMF）. Whitecaps backscattering signals were distinguished with the help of lidar depolarization ratio measurements and rectified by whitecaps coverage equation. Subsurface water backscattering signals were corrected by means of inverse distance weighted （IDW） from neighborhood non-singular data with optimal subsurface water backscattering calibration parameters. To verify the algorithm reliably, it selected NDBC＇s TAO buoy-laying area as survey region in camparison with buoys＇ wind field data and METOP satellite ASCAT of 25 km single orbit wind field data after temporal-spa tial matching. Validation results showed that the retrieval algorithm works well in terms of root mean square error （RMSE） less than 2m/s and wind direction＇s RMSE less than 21 degree.