黄河口海岸线遥感动态监测

本文以1976年至2002年间18景多时相遥感影像为主要数据源,在遥感与GIS技术的支持下,对影像进行几何校正与配准,并运用近红外波段的水体反射辐射率明显单一并低于其他地物的特性提取了逐年河口海岸的平均高潮线,另外经GIS叠加分析计算等获取了海岸线时空变化的数据,进一步分析了海岸线的演变过程,并根据河口来水来沙等条件提出了防止海岸蚀退的对策。     

遥感影像超分辨率处理方法与研究进展

随着人们对影像高分辨率需求的不断增加,图像超分辨率技术已成为相关研究领域的热点之一。针对在遥感领域并非所有的超分辨率方法都可用的现状,该文按照遥感影像超分辨率处理的流程,将超分辨率问题分为退化模型、配准、重建和精度评定4大模块。对于其中每一模块的理论、常用方法与研究进展进行了较全面的综述及比较分析。最后对这一领域的未来发展进行思考和展望。     

影像超分辨率重建技术在遥感中的应用

影像超分辨率重建是通过对多幅具有互补信息的低分辨率影像的处理,重建一幅高分辨率影像的技术,其在视频监控、医学诊断、遥感监测等领域具有很大的应用价值。以SPOT5和ADS40为例阐述了超分辨率重建技术在遥感观测系统中的应用现状,并给出了一种应用于多时相遥感影像处理的超分辨率重建方法。     

超像元尺度下的多光谱图像超分辨率洪水淹没制图

超分辨率制图SRM(Super-resolution Mapping)技术可以有效地处理遥感图像中的混合像元,获得准确的地物类别分布信息.目前,SRM技术已经成功地应用于多光谱图像洪水淹没定位中,称为超分辨率洪水淹没制图SRFIM(Super-resolution Flood Inundation Mapping).然...     

基于GIS和地统计学的地理国情监测成果制图应用研究

在全国范围开展的地理国情监测是对国家基础地理信息的动态更新,对监测数据的科学分析及成果展示有利于提升数据的使用价值。本文论述了利用GIS空间分析功能和地统计学原理,对国情监测数据的变化信息进行综合制图,为地理国情监测专项成果的可视化表达提供了新的方法。     

模糊类别制图的空间统计学方法

类别地图是地理信息系统（ＧＩＳ）应用中所利用的重要数据类别。这类数据可以从摄影测量和遥感技术得到。用摄影测量方法（影像判读）制作的类别地图常以点、线和多边形的离散目标形式描述,而遥感图像分类方法输出的类别地图以连通光栅块形式表达。不论哪一种情况,在每一个多边形或者光栅块（即制图单元）中仅允许单一类别,边界内部非均匀性和模糊形已经被“过滤”了。这样的类别地图沿用了古曲脆集合论,因为每个制图单元只允许     

ALOS-PRISM遥感影像超分辨率重建

介绍了日本ALOS卫星PRISM三线阵传感器的成像原理和方法,提出了利用PRISM三线阵影像进行超分辨率重建来提高PRISM影像的空间分辨率.提出了新的光流配准算法,该算法将标准互相关配准算法引入到Lueas-Kanade光流配准算法中,大大的减少了误配率,能够有效的消除PRISM Level 1级别的影像之间由于地形起伏所引起的变形.同时,改进了影像的高斯退化模型,在超分辨率算法中,引入了可变退化函数,通过交替最小化(AM)算法对可变退化函数进行盲估计,实验结果表明,超分辨率重建影像与插值影像相比,细节清晰很多,有效的提高了影像的分辨率.实验结果说明了本文配准算法可以达到超分辨率重建的亚像素的精度要求,可以应用于航空遥感影像的高精度匹配,同时也说明了将航空遥感影像的退化函数算子分为高斯退化算子和可变退化算子的思想是正确的,符合实际情况.     

浅谈多源多分辨率遥感数据整合

本文以ArcGlobe为平台,表现江西省的多源多分辨率遥感数据对江西省现有遥感数据的整理分析,提取出所需区域的最新遥感影像资料,补充制作缺失的遥感数据,将各传感器源的影像模拟为近自然真彩色影像,解决影像间的几何差异和色彩差异问题,对影像数据进行整合,建设2.5m-15m分辨率的省级影像库和0.2m-1m分辨率的设区市影像库,同时对影像数据的查询方法和管理方法进行探讨和研究。     

遥感影像超分辨率重建的字典学习类算法

近年来基于字典学习的超分辨率重建技术已成为图像处理领域的研究热点,相比基于重建的超分辨率方法,基于学习的方法充分利用了先验知识,在放大倍数较高时,仍可取得较好的效果,因此被公认为一种非常有前途的方法。本文对国内外已有的基于字典学习的超分辨率重建方法进行了系统研究,梳理了3种基于字典学习超分重建算法的基本原理及优缺点。此外,本文根据遥感影像的特点,使用同一数据源进行字典学习,利用不同字典学习算法分别生成高、低联合字典对,采用不同尺寸大小及缩放倍数的测试图像,进行超分辨率重建,对各种算法的重建性能、鲁棒性和复杂度进行综合分析,进一步研究了各种算法对遥感影像不同应用需求的适用性。     

遥感自动提取海岸线方法

利用遥感技术确定海岸线位置的问题受到关注由来已久,就其在国内外的研究现状做了介绍,利用小波边缘检测算子提取出黄河三角洲河口区2004年Landsat TM图像的海岸线位置;在分析小波算子与传统边缘提取方法相比的优点的同时,并就其存在的不足提出了今后的研究重点。     

改进的P-SVM支持向量机与遥感数据分类

本文介绍了将P-SVM算法引入多光谱/高分辨率遥感数据的分类, 并且展示了卫星ASTER和航空ADS40数字影像分类的技术过程和结果验证。结果表明：P-SVM方法的分类精度不低于SVM, 并减少了时耗。     

Linking archival and remotely sensed data for long-term environmental monitoring

The broad objective of this paper is to illustrate how archival, historical and remotely sensed data can be used to complement each other for long-term environmental monitoring. One of the major constraints confronting scientific investigation in the area of long-term environmental monitoring is lack of data at the required temporal and spatial scales. While remotely sensed data have provided dependable change detection databases since 1972, long-term changes such as those associated with typical climate scenarios often require longer time series data. The lack of data in readily accessible and usable formats for periods predating commercial satellite products has for a long time restricted the scope of environmental studies to temporally brief, synoptic overviews covering short time scales, thereby compromising our understanding of complex environmental processes. One way to improve this understanding is by cross-linking different forms of data at different temporal scales. However, most remote sensing based change research has tended to marginalize the utility of archival and historical sources in environmental monitoring. While the accuracy of data from non-instrumental records is often source-specific and varies from place to place, carefully conducted searches can yield useful information that can be effectively used to extend the temporal coverage of projects dependant on time series data. This paper is based on an ongoing project on environmental monitoring in the world's largest Ramsar site, the Okavango Delta, located on the northeastern fringes of Southern Africa's Kalahari–Namib desert in northern Botswana. With a database covering over 150 years between 1849 and 2001, the primary objectives of this paper are to: (1) outline how modern remotely sensed data (i.e., CORONA and Landsat) can be complemented by historical in situ observations (i.e., travellers’ records and archival maps) to extend temporal coverage into the historical past, (2) illustrate that different forms of declassified Cold War intelligence data (i.e., CORONA) can be constructively exploited to further scientific understanding and (3) provide a conceptual framework for collating and disseminating data at regional and international levels through electronic media.     

遥感影像地图在线服务系统设计与实现

针对遥感影像地图服务中存在的问题,本文提出了基于网络的遥感影像地图服务,设计了基于ArcGIS Server的遥感影像地图服务系统的整体框架及相关功能模块,研究了实现系统所涉及的关键技术,最后在开源环境Eclipse下用Java编程实现了遥感影像地图服务系统,为遥感影像的网络应用提供了一个服务平台。     

An improved algorithm for supervised fuzzyC-means clustering of remotely sensed data

This paper describes an improved algorithm for fuzzyc-means clustering of remotely sensed data, by which the degree of fuzziness of the resultant classification is decreased as comparing with that by a conventional algorithm: that is, the classification accuracy is increased. This is achieved by incorporating covariance matrices at the level of individual classes rather than assuming a global one. Empirical results from a fuzzy classification of an Edinburgh suburban land cover confirmed the improved performance of the new algorithm for fuzzyc-means clustering, in particular when fuzziness is also accommodated in the assumed reference data.     

海岸线及其测绘技术探讨

海岸线是人类所使用的最古老的边界线之一,然而,由于其动态特征,加之当今社会对海岸带的需求越来越多,这条边界线的位置存在争议,因而,如何使用客观手段测绘海岸线尤为重要。文中针对海岸线定义及其位置确定不明确的现状,指出海岸线定义存在的问题,给出完善定义的意见;分析海岸线常规的测绘方法,探讨海岸线精确测绘的新方法和技术。     

遥感估算地表蒸散发真实性检验研究进展

地表蒸散发是连接土壤—植被—大气连续体的纽带,结合遥感技术估算地表蒸散发已成为获取区域乃至全球尺度时空连续地表蒸散发量的有效手段。由于遥感估算地表蒸散发容易受到地表空间异质性和近地层气象条件复杂性的影响,在模型机理与变量参数化方案、输入数据和时间尺度扩展等方面存在不确定性,影响了其准确度的提高和应用范围的拓展,因此需要开展真实性检验。本文综述了当前遥感估算地表蒸散发(包括植被蒸腾和土壤蒸发)真实性检验研究的相关成果,重点归纳并总结了应用于遥感估算地表蒸散发真实性检验的直接检验法和间接检法的主要原理、适用性和优缺点,在此基础上阐述了当前遥感估算地表蒸散发真实性检验研究所面临的挑战。分析表明：由于地表空间异质性的普遍存在,遥感估算地表蒸散发真实性检验研究在理论和方法方面还受到诸多挑战,今后应打破地表蒸散发遥感产品真实性检验局限在均匀地表的传统思路,发展非均匀地表遥感估算地表蒸散发真实性检验的理论框架,包括地表水热状况空间异质性的度量、非均匀地表验证场的优化布设、非均匀下垫面地表蒸散发的多尺度观测试验、卫星像元/区域尺度地表蒸散发相对真值的获取、验证过程中的不确定性分析以及遥感估算地表蒸散发的实证研究等,并构建一个多源、多尺度、多方法、多层次的真实性检验技术流程,以期把遥感估算地表蒸散发真实性检验作为突破口,提升相应遥感产品的应用水平,推动定量遥感科学的发展。     

Exploring uncertainty in remotely sensed data with parallel coordinate plots

The existence of uncertainty in classified remotely sensed data necessitates the application of enhanced techniques for identifying and visualizing the various degrees of uncertainty. This paper, therefore, applies the multidimensional graphical data analysis technique of parallel coordinate plots (PCP) to visualize the uncertainty in Landsat Thematic Mapper (TM) data classified by the Maximum Likelihood Classifier (MLC) and Fuzzy C-Means (FCM). The Landsat TM data are from the Yellow River Delta, Shandong Province, China. Image classification with MLC and FCM provides the probability vector and fuzzy membership vector of each pixel. Based on these vectors, the Shannon's entropy (S.E.) of each pixel is calculated. PCPs are then produced for each classification output. The PCP axes denote the posterior probability vector and fuzzy membership vector and two additional axes represent S.E. and the associated degree of uncertainty. The PCPs highlight the distribution of probability values of different land cover types for each pixel, and also reflect the status of pixels with different degrees of uncertainty. Brushing functionality is then added to PCP visualization in order to highlight selected pixels of interest. This not only reduces the visualization uncertainty, but also provides invaluable information on the positional and spectral characteristics of targeted pixels.     

基于Contourlet变换的高空间分辨率遥感影像检索研究

本文在高空间分辨率遥感影像纹理特征提取研究中引入Contourlet变换,将不同尺度、不同方向子带系数矩阵的均值、方差和能量作为纹理特征,并为分类能力强的特征量赋予较大的权值,体现相应子带分类能力的差异性。以QuickBird影像为样本数据、采用五叉树分解策略的纹理检索实证研究表明,基于Contourlet变换提取高空间分辨率遥感影像纹理特征信息的效果优于Gabor小波变换。     

基于傅里叶描述子的高分辨率遥感图像 地物形状特征表达

本文在对傅里叶描述子进行归一化的基础上, 将该方法引入地物轮廓的形状特征描述中, 针对建筑物、 农田、道路和河道4 种典型地物, 分别从谱线特征、不同频段描述子对形状特征的贡献率、形状重构三个方面进行 分析, 结果表明, 在谱线图中, 直流分量对形状特征的贡献率在70%以上, 低频和高频成分共占7%—24%左右, 中 频成分的贡献率只有2%—4%左右, 仅低频成分(第1—5 项)便能够很好地进行地物形状重构。最后将第1—5 项描 述子应用到基于决策树的面向对象分类中, 得出实验区总体分类精度为98.48%     

Markov random field-based method for super-resolution mapping of forest encroachment from remotely sensed ASTER image

Forest encroachment (FE) is a problem in Andaman and Nicobar Islands (ANI) in India for environment and planning. Small gaps created in the forest slowly expand its periphery disturbing the biodiversity. Therefore, intrusion of poachers, slash and burn and other factors causing FE must be carefully detected and monitored. Remote sensing offers a great opportunity to accomplish this task because of its synoptic view. Conventional classification methods with remotely sensed images are problematic because of small size of FE and mixed landcover composition. This study presents an application of super-resolution mapping (SRM) based on Markov random field for detection of FE using ASTER (15 m) images. The SRM results were validated using multispectral IRS LISS-IV (5.8 m) image. Non-contiguous FE patches of various sizes and shapes are characterized using the spatial contextual information. The novelty of this approach lies in the identification and separability of small FE pockets which could not be achieved with pixel-based maximum likelihood classifier (MLC). The SRM parameters were optimized and found comparable to previous studies. Classification accuracy obtained with SRM at scale factor 3 is κ = 0.62 that is superior to accuracy of MLC (κ = 0.51). SRM is a promising tool for detection and monitoring of FE at Rutland Island in ANI, India.