反射率因子和径向速度共同约束反演多普勒雷达风场

多普勒雷达可以提供降水回波区的风场信息。为了充分运用雷达资料分析中小尺度天气过程,本文假设反射率因子在短时间内的运动满足拉格朗日守恒,提出了采用连续两次的反射率因子回波和径向速度数据共同约束的方法来反演风场,在反演过程中避免了对径向速度的分布进行假设。针对连续两个时次之间反射率回波运动中产生的不同程度的误差做了模拟风场试验,结果表明,当回波运动随机误差不超过40%时,反演结果较为可靠。另外,本文还利用此风场反演方法进行两次中尺度天气过程的实例分析。结果表明,该方法反演的风场与实际风场结构相符,具有一定的应用价值。     

“数字重庆”地理空间信息定位基准体系的建设

介绍了"数字重庆"地理空间信息定位基准建设的基本情况,着重阐述了CQGNSS、高精度GPS控制网、精密水准网和区域似大地水准面精化等方面的数据处理情况,展示了山城地区的基准体系建设特点。     

利用稀疏分解的高分辨率遥感图像线状特征检测

目的 线状特征检测是利用遥感数据开展地物目标自动识别的重要步骤。利用高分辨率遥感图像的高度细节化特点,针对现有线状特征检测方法存在的问题,提出了一种基于稀疏分解的高分辨率遥感图像线状特征检测方法。采用 K-SVD字典学习算法获取线状特征表达所需的过完备字典,基于稀疏分解模型,从高分辨率遥感图像中分离出高频成分,实现遥感图像线状特征的初步检测;用曲波分层自适应阈值法对分离后的高频成分作降噪处理,以提高线状特征检测的效果。利用 QuickBird图像进行实验的结果显示,该方法在线段连续性、低对比度线段检测与椒盐噪声消除方面均有一定优势。     

联合机载LiDAR数据和潮汐数据自动提取潮位线

首先,联合机载激光雷达(LiDAR)数据提取的海岸带数字表面模型(DSM)与验潮站数据提取的高、低潮面进行相交运算,生成"水陆二值图像",然后对其以提取边缘的方式提取高、低潮潮位线;针对LiDAR光束无法穿透水体导致低潮线附近DSM为无效值的缺陷,采取移动趋势面拟合法外推概略低潮线附近DSM,在此基础上重新提取更精确的低潮潮位线。实验表明,该方法能在较少人工干预的情况下有效提取高、低潮潮位线。     

基于分水岭和多尺度分割方法的耕地信息提取

在探讨了分水岭和多尺度相结合的影像分割方法的基础上,研究了高分辨率影像耕地的信息分类以及分类精度评定;重点对影像分类精度进行了分析,在影像分类的过程中,分别采用基于像素的分类方法和基于对象的分类方法,实验结果表明基于对象的耕地分类方法精度远高于传统的分类方法。     

Near real-time high-resolution airborne camera,AEROCam, for precision agriculture

Precision agriculture often relies on high-resolution imagery to delineate the variability within a field. Airborne Environmental Research Observational Camera (AEROCam) was designed to meet the needs of agriculture producers, ranchers, and researchers, who require high-resolution imagery in a near real-time environment for rapid decision support. AEROCam was developed and operated through a unique collaboration between several departments at the University of North Dakota, including the Upper Midwest Aerospace Consortium (UMAC), the School of Engineering and Mines, and flight operations at the John D. Odegard School of Aerospace Sciences. AEROCam consists of a Redlake MS4100 area-scan multi-spectral digital camera that features a 1920 × 1080 CCD array (7.4-μm detector) with 8-bit quantization. When operated at ～2 km above ground level, multispectral images with four bands in the visible and near infrared have a ground sample distance of 1 m with a horizontal extent of just over 1.6 km. Depending on the applications, flying at different altitudes can adjust the spatial resolution from 0.25 to 2 m. Rigorous spectral and radiometric calibrations allow AEROCam to be used in a variety of applications, qualitative and quantitative. Equipped with an inertial measurement unit (IMU) system, the images acquired can be geo-referenced automatically and delivered to end users near real time through our Digital Northern Great Plains system (DNGP). The images are also available to zone mapping application for precision farming (ZoneMAP), an online decision support tool for creating management zones from remote sensing imagery and data from other sources. Operational since 2004, AEROCam has flown over 250 sorties and delivered over 150,000 images to the users in the Northern Great Plains region, resulting in numerous applications in precision agriculture and resource management.     

Generation of high spatial and temporal resolution NDVI and its application in crop biomass estimation

Abstract

While data like HJ-1 CCD images have advantageous spatial characteristics for describing crop properties, the temporal resolution of the data is rather low, which can be easily made worse by cloud contamination. In contrast, although Moderate Resolution Imaging Spectroradiometer (MODIS) can only achieve a spatial resolution of 250 m in its normalised difference vegetation index (NDVI) product, it has a high temporal resolution, covering the Earth up to multiple times per day. To combine the high spatial resolution and high temporal resolution of different data sources, a new method (Spatial and Temporal Adaptive Vegetation index Fusion Model [STAVFM]) for blending NDVI of different spatial and temporal resolutions to produce high spatial–temporal resolution NDVI datasets was developed based on Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). STAVFM defines a time window according to the temporal variation of crops, takes crop phenophase into consideration and improves the temporal weighting algorithm. The result showed that the new method can combine the temporal information of MODIS NDVI and spatial difference information of HJ-1 CCD NDVI to generate an NDVI dataset with both high spatial and high temporal resolution. An application of the generated NDVI dataset in crop biomass estimation was provided. An average absolute error of 17.2% was achieved. The estimated winter wheat biomass correlated well with observed biomass (R ² of 0.876). We conclude that the new dataset will improve the application of crop biomass estimation by describing the crop biomass accumulation in detail. There is potential to apply the approach in many other studies, including crop production estimation, crop growth monitoring and agricultural ecosystem carbon cycle research, which will contribute to the implementation of Digital Earth by describing land surface processes in detail.     

北斗Ⅱ载波相位差分定位法在高填方变形监测中的应用

通过对北斗Ⅱ载波相位差分定位技术在高填方变形监测中的应用研究,包括实时动态差分定位(RTK)和静态相对定位,构建了完整的北斗Ⅱ高填方变形监测软硬件系统。该系统采用基于贯序极限学习机的卫星信号周跳探测与修复方法进行数据预处理,并利用基于卫星历元数的分层置信滤波算法对静态相对定位结果进行修正,提高了定位结果的准确性和可靠性。通过自制的精度测试装置,以百分表和钢尺测量的位移变化量为相对真值,完成了上述变形监测系统的精度试验。试验结果表明:该系统的RTK高程测量精度优于2 cm,静态高程测量精度优于2 mm,静态水平位移测量精度优于1.5 mm,可有效抑制卫星信号周跳和卫星历元数量较少等因素的影响。     

高分辨率遥感影像主干道路提取的感知编组方法

针对高分辨率遥感影像的道路提取受"同物异谱、同谱异物"干扰的问题,该文提出一种基于感知编组的高分辨率遥感影像主干道路自动提取方法:首先,使用Line Segment Detector算法提取影像中直线段信息。然后,利用高分辨率遥感影像上的道路几何特征对直线段进行感知编组;最后,经过长度约束得到道路信息。使用两景影像进行了主干道路提取实验。实验结果表明,两个实验中主干道路提取的完整率、正确率和检测质量都在96%以上。     

风电场设计私有云GIS平台架构研究

云计算是目前信息产业最热门的技术之一,GIS厂商纷纷将GIS软件迁移至云计算环境。与国外云计算部署不同,国内更青睐私有云技术,企业、政府机构纷纷搭建私有云GIS平台。针对风电场设计的特点,本文基于目前云计算应用和研究,构建了私有云GIS平台的体系框架,并对平台所涉及的主要关键技术进行了深入探索,对私有云GIS模式下的资源进行了详细的分类,包括核心服务、服务管理、用户访问接口3个部分。其中,核心服务将硬件基础设施、软件运行环境、应用程序抽象成服务,可满足多样化的风电场设计应用需要。