基于不同小波变换与同态滤波结合的CBERS-02B卫星CCD图像的薄云去除

卫星CCD图像的去云处理对遥感信息的增强与提取有重要的意义,尤其是在云覆盖严重的低纬度地区。为去除CBERS-02B卫星CCD图像中薄云的影响,分别使用Mallat和à trous 2种小波变换对图像进行分解;利用同态滤波对2种小波分解图像的低频系数进行处理,衰减其低频信息;将处理后的小波低频系数与分解的高频系数进行小波重构,从而达到去云的目的。定量分析基于Mallat和à trous小波变换结合同态滤波法的去云结果表明,经à trous小波变换结合同态滤波法的去云影像所包含信息量大,细节信息丰富,去云效果较好。     

云相态的卫星遥感研究进展

云相态不仅是气象学和气候学研究的重要参量,也是卫星云参数反演的关键要素,其识别的准确性直接关系到光学厚度、有效粒子半径等光学和微物理参数的反演精度.卫星遥感技术的发展为云相态的识别提供了前所未有的技术手段.对能够提取云相态信息的主要星载遥感源进行了介绍,重点总结了近30年来国内外利用星载被动光学遥感资料、偏振辐射资料以及主动雷达资料进行云相态反演的基本原理、方法以及技术特点,最后针对目前云相态反演工作中存在的一些问题和发展趋势进行了探讨.     

Analysis of Cloud Scale Error of Low Resolution Satellite Based on GF-4 and Its Influence on Downward Radiation Calculation

In order to study the scale error of low resolution meteorological satellite cloud detection and its impact on the calculation of downlink radiation, cloud detection using high resolution stationary satellite GF-4 data and error analysis were carried out. Firstly, the cloud detection of GF-4 data is carried out by using visible channel threshold method and time series method, and the error of cloud detection results of Himawari-8 and FY-2 (FY-2G, FY-2E) is analyzed based on the results of GF-4 cloud detection.In the study area, FY-2G, FY-2E and Himawari-8 cloud images could distinguish the clouds and clear sky. The main reason for the error was the scale effect produced by different spatial resolution satellites(the differences caused by cloud detection algorithms are not discussed here).Most of the errors occurred in the areas of thin clouds and broken clouds.High resolution data could detect broken clouds, while low resolution data lead to false and missed detection. On this basis, the error of remote sensing calculation of short wave radiation was analyzed,and it was found that the error of the actual cloud amount in the pixel would bring significant error to the estimation of the downward radiation.The relative error of the instantaneous downward radiation in the selected test area was -173.52%, and the maximum relative error of shortwave radiation was -20.20%.The results show that the high resolution stationary satellite data can significantly improve the estimation accuracy of the downlink shortwave radiation in the regions with more broken clouds.     

北疆牧区积雪图像分类与雪深反演模型的研究

利用NOAA/AVHRR晴空气象条件下的资料, 建立积雪监测反演模型, 动态监测雪灾期间大范围的积雪空间分布状况, 对牧区雪灾综合评价及防灾救灾具有重要的意义. 使用北疆地区1996-97年2次雪灾期间的4个时相的晴空NOAA卫星数据及20个地面气象台站观测资料, 研究了云与雪的判识及图像去云处理方法, 提出了云层覆盖下图像缺值插补处理的一种新算法; 采用线性混合光谱分解方法, 研究了基于像元的积雪覆盖率及积雪空间分类算法, 模拟出北疆地区积雪深度遥感地学反演模型. 研究结果可为牧区雪情动态监测、分析与综合评价系统的建设提供科学依据.     

Retrieval of cloud classification parameters using two-dimensional fast Fourier transform

A method is presented for the retrieval of classification parameters of clouds observed by satellite-borne imaging systems. It is based on a two-dimensional fast Fourier transform of cloud images and an analysis of their power spectra. The parameters retrieved provide quantitative information on mean brightness, size, shape and directional properties of clouds. The efficacy of the subdivision of the original cloud image into smaller regions and the determination of individual parameters is demonstrated by applying this procedure to some NOAA and INSAT cloud images.     

基于Quickbird影像的小堡崩塌群调查研究

遥感技术为地质灾害调查研究提供了新的途径和手段,已成为地质灾害调查研究的一种重要技术手段,特别是高分辨率的Quickbird卫星影像在地质灾害的调查研究中有着广泛的应用。笔者在研究汉源县小堡崩塌群时,采用Quickbird卫星影像,通过遥感数字图像处理,获得高精度的遥感影像图作为地质灾害遥感研究的数据源,并进行遥感解译,总结小堡崩塌群的遥感影像特征。根据遥感影像特征来判定其规模、稳定性、危害程度和发展趋势,并分析其形成条件和影响因素。     

甘肃华亭地区铀矿化信息遥感提取方法

从分析ETM各波段图像的信息特征入手,在黄土覆盖等环境因素干扰严重的地区,利用遥感技术对其铀矿化的信息进行了提取.在ERDAS软件的支持下,应用图像融合、波段比值、主成分分析、光谱指数等技术方法,对ETM遥感影像数据进行增强处理.其中,图像融合与传统的图像融合略有不同,是在进行图像融合前将原始图像（ETM1～5,7）进行低通滤波处理,使得融合后的图像既保留高分辨率数据的空间信息,又保留低分辨率数据的光谱信息.在对研究区的遥感数据进行增强处理后,选取有利波段组合,圈定了有利铀成矿的远景区.     

毫米波测云雷达的特点及其研究现状与展望

云在大气的能量分配、辐射传输,尤其是水循环系统中有不可忽视的作用。云探测对云物理、人工影响天气、气候变化和航空航天等领域有重要意义,是大气科学研究的热点之一。尽管目前已经发展了很多种遥感设备对云进行观测(如激光雷达、卫星、云幂仪等),但这些设备无法得到高时空分辨率的云水平和垂直结构,而毫米波雷达是云三维精细结构探测的重要工具。由于毫米波雷达具有更接近小粒子尺度的短波长,因此更适合用来探测弱云,同时毫米波雷达也存在衰减严重的缺点。介绍了毫米波雷达的特点以及其探测小粒子的优势;对比分析了其与新一代多普勒天气雷达、晴空风廓线雷达的差异,得出：毫米波雷达具有高时空分辨率,能够更精确地反映云的垂直和水平结构,比普通天气雷达更适合监测云的变化。概括了国内外毫米波测云雷达的发展现状以及在云物理研究方面的情况,并展望了国内毫米波雷达未来研究的方向。     

Satellite detection of hazardous volcanic clouds and the risk to global air traffic

Remote sensing instruments have been used to identify, track and in some cases quantify atmospheric constituents from space-borne platforms for nearly 30 years. These data have proven to be extremely useful for detecting hazardous ash and gas (principally SO₂) clouds emitted by volcanoes and which have the potential to intersect global air routes. The remoteness of volcanoes, the sporadic timings of eruptions and the ability of the upper atmosphere winds to quickly spread ash and gas, make satellite remote sensing a key tool for developing hazard warning systems. It is easily recognized how powerful these tools are for hazard detection and yet there has not been a single instrument designed specifically for this use. Instead, researchers have had to make use of instruments and data designed for other purposes. In this article the satellite instruments, algorithms and techniques used for ash and gas detection are described from a historical perspective with a view to elucidating their value and shortcomings. Volcanic clouds residing in the mid- to upper-troposphere (heights above 5 km) have the greatest potential of intersecting air routes and can be dispersed over many 1,000s of kilometres by the prevailing winds. Global air traffic vulnerability to the threat posed by volcanic clouds is then considered from the perspectives of satellite remote sensing, the upper troposphere mean wind circulation, and current and forecast air traffic density based on an up-to-date aircraft emissions inventory. It is concluded that aviation in the Asia Pacific region will be increasingly vulnerable to volcanic cloud encounters because of the large number of active volcanoes in the region and the increasing growth rate of air traffic in that region. It is also noted that should high-speed civil transport (HSCT) aircraft become operational, there will be an increased risk to volcanic debris that is far from its source location. This vulnerability is highlighted using air traffic density maps based on NOx emissions and satellite SO₂ observations of the spread of volcanic clouds.     

Monitoring Forest Fire Danger with Remote Sensing

Our paper presents a review of the use of remote sensing technologies for forest wildfire danger monitoring, with a particular emphasis on its applicability to fuel moisture monitoring. Remote sensing of fuel moisture was first done with NOAA-AVHRR NDVI images, but NDVI is more related to vegetation greenness rather than water stress. NOAA-AVHRR surface temperature images were also used, alone or in association with NDVI images. Both kinds of images have a limited image availability due to cloud cover. This is not the case for radar images, but their use in fuel moisture monitoring is still experimental, because of the noisy effects of several factors. Finally, the paper discusses the operational potentials and limitations of the use of each kind of satellite data for fire danger monitoring.     

基于被动微波的寒旱区地表温度反演

以各频段水平极化和垂直极化发射率问的相关关系为条件,利用被动微波数据反演地表温度.算法既解决了地表温度反演过程中发射率难以确定的问题,又克服了热红外遥感受大气影响较大的缺点,其物理意义清晰,计算简便.算法以MODIS温度产品为评价标准,对36.5GHz和89 GHz反演结果进行分析.结果表明:89 GHz亮温数据反演精度高于36.5 GHz;与耕地和草场反演精度相比,裸土和山地反演精度较高.其原因在于高频数据穿透能力较低,能更好地表达地表温度.同时,低频数据相对高频更容易受到地表土壤水分变化的影响,发射率相对不够稳定,对反演结果有一定影响.     

卫星遥感影像与航空遥感影像的对比分析

本文对卫星遥感和航空遥感进行对比,并选取同一区域同时期同一比例尺的卫星遥感影像和航空遥感影像的DOM,进行土地利用地类的判译识别,通过对比分析,探讨了利用高精度卫星遥感影像进行土地利用更新的可行性。     

SAR遥感数据用于岩性识别与分类的研究

利用新疆北部山区雷达遥感数据,通过遥感数字图像处理与增强,生成雷达遥感假彩色合成影像应用于岩性判释。对不同岩性岩石,利用极化雷达提供的地表岩石的多种散射信息作为输入进行计算机神经网络分类,岩性识别分类的总精度为62.6%。与常规雷达数据分类对比,分类精度与岩石识别正确率均有显著提高。     

国外遥感卫星发展简介（1）

从美国发射其第一颗遥感卫星一陆地卫星－1算起的30余年里，世界范围内商业遥感卫星技术已经有了巨大的进步，越来越多的国家和国际团体拥有自己的遥感卫星。除了更多各类的遥感器得以使用外，卫星的图像分辨率和覆盖能力也有了很大的改进。未来的发展更加令人振奋。国外遥感卫星（包括已经发射和计划要发射的卫星）简介是根据从国内外出版物中获得的信息整编而成，旨在给遥感应用提供一个现在和未来图像信息源的总的概念。     

Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models

This paper presents landslide hazard analysis at Cameron area, Malaysia, using a geographic information system (GIS) and remote sensing data. Landslide locations were identified from interpretation of aerial photographs and field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence are topographic slope, topographic aspect, topographic curvature, and distance to rivers, all from the topographic database; lithology and distance to faults were taken from the geologic database; land cover from TM satellite image; the vegetation index value was taken from Landsat images; and precipitation distribution from meteorological data. Landslide hazard area was analyzed and mapped using the landslide occurrence factors by frequency ratio and bivariate logistic regression models. The results of the analysis were verified using the landslide location data and compared with the probabilistic models. The validation results showed that the frequency ratio model (accuracy is 89.25%) is better in prediction of landslide than bivariate logistic regression (accuracy is 85.73%) model.     

引导滤波联合局部判别嵌入的高光谱影像分类

高光谱遥感影像分类是高光谱遥感影像处理和应用的重要组成部分。然而,高光谱遥感影像具有波段数量较多和空间分辨率较高等特点,给分类任务带来一定的挑战。为了提高分类精度,充分利用影像的空间信息和像素间的局部信息,提出一种引导滤波联合局部判别嵌入的高光谱影像分类方法。首先,对高光谱遥感影像进行归一化,利用主成分分析方法实现特征提取,将提取的第一主成分影像作为引导图像;其次,采用引导滤波分别提取各波段影像的空间特征;然后,将提取的空间影像特征进行叠加,通过局部Fisher判别分析完成低维嵌入;最后,将得到的低维嵌入特征输入支持向量机分类器得到分类结果。采用Indian Pines和Pavia University两幅高光谱影像进行实验的结果表明：在分别从各类地物中随机选取10%和100个样本作为训练样本的情况下,其总体分类精度分别提高到98.28%和99.45%;对比其他相关方法,该方法能够获取更高的分类精度。该方法在低维嵌入的同时,有效利用了影像的空间信息,改善了分类效果。     

矿山遥感编图中的高分辨率遥感数据选择与比例尺计算方法

通过对青海调查矿区多种高分辨率卫星数据处理后形成的图像进行解译和编图,掌握了合理选择遥感数据信息源、利用制图软件计算遥感影像图比例尺及编制野外调查和成果解译图的技术方法。得出在选择遥感数据时要考虑不同数据的技术参数、性价比及调查区面积;明确了当图像的出图分辨率确定后,其比例尺与图像的空间分辨率、像素大小、文档大小有直接关系,同时建立了计算遥感图像最佳比例尺和最佳出图比例尺的公式和方法;介绍了利用Photoshop和Mapgis软件,编制矿山野外调查用图和遥感解译成果图件的流程及方法。这些工作的完成对青海矿业开发地质环境效应调查起到了积极的指导作用,也充分体现了高分辨率遥感图像在工作条件艰苦地区的优势作用。     

多源遥感数据在西准噶尔哈拉阿拉特山地区1:5万地质填图中的对比研究

以ETM、SPOT5和Quickbird为主要信息源,在哈拉阿拉特山地区开展1:5万区域地质填图,对该地区的地层单元、中—小规模地质体(如岩脉、小岩体和火山口)和地质构造特征进行了详细地遥感解译分析,并开展了大量的遥感野外地质调查验证.结果表明,采用彩色空间HSV变换融合法将SPOT5高精度遥感图像数据与ETM图像数据...     

无人机影像在高陡边坡危岩体调查中的应用

在高陡边坡危岩体的调查中,复杂的地形条件经常限制工作的正常开展,如何快速准确地获取地质灾害信息一直是地质灾害调查研究中的难点之一。以往的研究中对无人机遥感技术在黄土、高原等地区应用有所报道,但对西南地区高陡边坡危岩体灾害调查的研究尚无报道。文章以锦屏二级水电站出线场边坡落石灾害所在区域为例,将无人机摄影测量技术应用于高陡边坡危岩体调查中,通过无人机倾斜摄影获取高分辨率遥感影像,开展遥感影像三维建模,进行地质灾害遥感解译,总结了无人机遥感系统在高陡边坡危岩体调查的技术流程。通过三维实景模型,精确地分析了落石灾害的空间分布、失稳模式及演化过程,查明了区域内危岩隐患点的分布特征;基于三维点云模型,提取出地质灾害体的属性信息,测得落石方量为11.7 m3,采用最小二乘法进行平面拟合,得到落石两组主控结构面产状为275.4°∠31.2°、103.5°∠63.3°。实践表明,无人机遥感技术在高陡边坡地区落石灾害调查中具有明显的可行性和优越性,可以较好地应用于高陡边坡危岩体调查中。     

二维平面非恒定流数学模型的遥感水位数据同化

为了在水流计算中定量化利用遥感水位数据,基于偏微分方程最优化控制理论建立了变分模型来融合二维平面非恒定流的数学模型和数据。根据遥感数据空间信息密集的特点,提出遥感水位数据同化的新算法。采用人工合成数据考察了面域遥感数据对于定常参数和时变两类参数的反演效果。试验结果表明,遥感数据提供的空间分布式信息有利于空间分布式参数的反演识别,而且通过引入考虑水面空间变化信息的附加项,可以改善观测信息的同化,更好地辨识时变参数(流量过程)。以Moselle河的RADARSAT卫星遥感水位数据检验了模型的实用性。