一种基于点云提取微地形对象的方法

在分析微地形特点以及现有网格DEM在表述微地形中存在的不足的基础上,提出了面向对象的数字高程模型,给出了该模型的形式化描述和以点云为数据源构建面向对象数字高程模型过程中采用的对象边界的识别、特征保持的点云疏化、基于属性近似的网格约化及对象识别等关键步骤的方法。并以实例证明了此过程的可行性。     

TRMM PR雷达与阜阳雷达降水资料的对比研究

选取了1998年与1999年HUBEX观测资料，将TRMM卫星上的星载降雨雷达PR与阜阳的713数字化天气雷达资料在以下3个方面做了比较：(1)强度场的分布；(2)平均反射率廓线；(3)灵敏度。分析、比较结果可知阜阳雷达在探测灵敏度和水平方向的分辨率要高于PR，但由于波束宽度、衰减和资料转化过程计算误差的原因，其远距离处的观测值与真实值有一定偏差。PR波长短，对衰减敏感，尤其是在垂直方向上经过强衰减后，订正值仍偏小。但由于探测方式的不同PR在水平方向上不存在衰减的问题，且其资料分布均匀，因此提出一种用PR资料来订正地基雷达资料的方法用以提高地基雷达探测的精确度。     

Cartographically Wordy but not Necessarily Worthy

Abstract

A novel method called multidirectional visibility index (MVI) has been developed and verified. The MVI improves standard cartographic analytical shading with a number of enhancements to topographic detail and prominent structures, i.e. the portrayal of flat areas in lighter tones, the accentuation of morphologic edges, and the multiscale visualisation of morphologic terrain features. The procedure requires a digital elevation model (DEM) and involves the following steps: visibility mask computation; the respective multidirectional altering of the azimuth and elevation angle; the generation of continuous grid MVIs that indicate upper/lower views, quasi-slope, and relative relief; and an appropriate visualisation of the relevant MVI as a standalone technique or in combination with standard hill-shaded relief. The modelling parameters are robust and therefore highly adaptive to different landforms.     

GIS的未来之我见

对当前地理信息系统的发展动态进行了分析,提出了未来GIS的发展呈现出的新特点、云计算GIS的发展趋势以及GIS和人们的生活密切相关.     

融合多尺度视网膜图像增强的动态云检测

云检测是气象卫星各类定量遥感产品的基础,无论是以云图为基础的天气分析还是以去云为前提的各类大气和地表参数反演、沙尘火情等灾害检测,都需要对遥感影像中的云进行准确识别,尤其是薄云和云边缘等细节识别。针对静止气象卫星(以Himawari-8为例)精细化云检测,本文提出了一种基于多尺度视网膜图像增强的动态云检测算法。该算法基于云层与背景信息辐射特征不同的原理,构建可见光和红外波段的晴空辐射背景场,通过多尺度图像增强和最大类间差方法对辐射差值进行云细节信息的增强和提取。利用2021-2022年的75景MODIS云检测产品作为验证数据进行算法精度验证,整体上算法精度达到91.13%,召回率为94.02%,精确率为86.71%,有较强的适用性和稳健性,且已经较好地支撑了近两年的定量遥感产品业务化应用。     

Improving the assessment of ICESat water altimetry accuracy accounting for autocorrelation

Given that water resources are scarce and are strained by competing demands, it has become crucial to develop and improve techniques to observe the temporal and spatial variations in the inland water volume. Due to the lack of data and the heterogeneity of water level stations, remote sensing, and especially altimetry from space, appear as complementary techniques for water level monitoring. In addition to spatial resolution and sampling rates in space or time, one of the most relevant criteria for satellite altimetry on inland water is the accuracy of the elevation data. Here, the accuracy of ICESat LIDAR altimetry product is assessed over the Great Lakes in North America. The accuracy assessment method used in this paper emphasizes on autocorrelation in high temporal frequency ICESat measurements. It also considers uncertainties resulting from both in situ lake level reference data. A probabilistic upscaling process was developed. This process is based on several successive ICESat shots averaged in a spatial transect accounting for autocorrelation between successive shots. The method also applies pre-processing of the ICESat data with saturation correction of ICESat waveforms, spatial filtering to avoid measurement disturbance from the land–water transition effects on waveform saturation and data selection to avoid trends in water elevations across space. Initially this paper analyzes 237 collected ICESat transects, consistent with the available hydrometric ground stations for four of the Great Lakes. By adapting a geostatistical framework, a high frequency autocorrelation between successive shot elevation values was observed and then modeled for 45% of the 237 transects. The modeled autocorrelation was therefore used to estimate water elevations at the transect scale and the resulting uncertainty for the 117 transects without trend. This uncertainty was 8 times greater than the usual computed uncertainty, when no temporal correlation is taken into account. This temporal correlation, corresponding to approximately 11 consecutive ICESat shots, could be linked to low transmitted ICESat GLAS energy and to poor weather conditions. Assuming Gaussian uncertainties for both reference data and ICESat data upscaled at the transect scale, we derived GLAS deviations statistics by averaging the results at station and lake scales. An overall bias of −4.6 cm (underestimation) and an overall standard deviation of 11.6 cm were computed for all lakes. Results demonstrated the relevance of taking autocorrelation into account in satellite data uncertainty assesment.     

一种基于直方图均衡化改进的图像增强算法

本文分析了传统的灰度图像直方图均衡化算法的不足,提出了一种基于概率的灰度图像直方图均衡化的改进算法。该方法给出了较合理的变换关系,使运算结果有较大改善,而且保留了传统算法的快速、自动化的特点。     

小波同态滤波用于南极遥感影像阴影信息增强

介绍了同态滤波方法的原理、实现过程和特点,给出适用的滤波器和表达式,引入基于小波变换的同态滤波方法,采用同态滤波器对小波分解系数进行处理,实现了在保持南极遥感影像总体面貌的基础上增强阴影信息的效果.     

遥感图像中云层遮挡影响消除方法研究述评

 综合评述了目前用于消除遥感图像云层遮挡影响方法的原理、应用现状及处理过程中存在的问题，并在同一实验区比较了同态滤波和Kriging插值等方法的处理效果，结果表明，Kriging插值处理具有一定的优越性。