高山冰川遥感提取方法研究

遥感的应用使得对冰川大尺度全覆盖、多时相变化的监测成为可能,然而冰川信息遥感提取方法的误差大等难题成为影响冰川监测的障碍。本文综合分析比较了目前已有的多种冰川提取方法的有效性,得出提取冰川范围精度最高的是面向对象的目视判读方法,其次是最大似然法监督分类、面向对象的自动分类、比值阈值法、雪盖指数法等。各自动方法提取冰川面积均有较大误差,且误差主要出现在冰舌末端、阴影区、薄冰区和云层遮盖范围等区域。本文将面向对象的目视判读法应用于冰川提取中,在保证信息提取精度的同时提高了传统解译的效率。     

Mass Balance Estimation of Dokriani Glacier in Central Indian Himalaya Using Remote Sensing Data

Dokriani Glacier is regarded as one of the important glaciers of Bhagirathi River basin, which fed river Ganges. The length of the glacier is about 4.6 km, and snout elevation is about 4028 m m.s.l. The mass balance of this glacier was calculated using field-based measurements for few years during 1994 to 2000. However, due to remote and poor accessibility, the field-based measurements could not continue; thus, remote sensing-based methods become useful tool to estimate the long-term mass balance of the glacier. In this study, glacier mass balance has been determined using accumulation area ratio (AAR) method. Remote sensing data sets, e.g. Landsat TM, ETM?+?and OLI, have been used to estimate AAR for different years from 1994 to 2014. An attempt has also been made to develop a mathematical relationship between remote sensing-derived AAR and field-observed mass balance data of the glacier. Further, this relationship has been used to estimate mass balance of the glacier for different years using remote sensing-derived AAR. Estimated mass balance was validated from ground-observed mass balance for few years. The field-observed and remote sensing-derived mass balance data are compared and showed high correlation. It has been observed that AAR for the Dokriani Glacier varies from 0.64 to 0.71. Mass balance of the glacier was observed between ??15.54 cm and ??50.95 cm during the study period. The study highlights the application of remote sensing in mass balance study of the glaciers and impact of climate change in glaciers of Central Indian Himalaya.     

基于GF-2数据的中梁山岩溶塌陷遥感调查

随着重庆经济增长和交通建设的日益发展,隧道工程建设引起的地面塌陷灾害已经成为中梁山地区最严重的地质环境问题之一,给该地区的经济发展和人民生命财产安全造成了严重影响。以2017年高分二号卫星高空间分辨率影像数据为主要信息提取源,在建立塌陷灾害遥感解译标志的基础上,对中梁山地区的塌陷灾害进行遥感调查和野外验证,共解译岩溶塌陷点120处。研究表明,中梁山岩溶塌陷主要分布在隧道两侧的三叠系下统嘉陵江组、大冶组地层,人为因素(修建隧道)是塌陷灾害的主要诱发因素。     

遥感数据的遗传-超平面分割算法

在传统的采用超平面作为判别边界的分割方法中，使用统计学的方法确定类判别界面，当区域间的统计值大于区域内的统计值时，就会出现类判决界面难于确定的问题。遗传算法的特点是进行全局优化搜索，利用这种算法优势可以解决传统算法难以解决的超平面空间定位问题，从而解决类判决界面的确定问题。通过EOS／MODIS图像数据的分割对该方法作了详细的介绍，其分类精度明显高于统计学分类方法。     

遥感图像数据复合方法

遥感图像数据复合是将多种遥感图像数据融合成一种新的图像数据的技术 ,是目前遥感应用分析的前沿 ,它主要包括几何配准和彩色变换两个方面的内容。几何配准采用相对配准和绝对配准两种方法 ;彩色变换采用 RGB彩色系统和 IHS彩色系统之间的变换。对SPOT和 TM图像数据进行复合实验 ,获得了一种新的复合图像。     

基于元数据的遥感数据自动入库系统设计与实现

随着遥感技术的发展和应用水平的提升,遥感数据的管理需求日益强烈,传统遥感数据入库方法自动化程度低。本文从遥感数据特点和遥感数据加工部门实际需求出发,对传统遥感数据入库流程进行了改进,提出了一套基于元数据的遥感数据自动入库解决方案,并自主开发了系统。该研究成果在北京、天津、广州等地项目中实际应用,大大提高了数据加工部门工作效率。     

基于海色遥感应用的MODIS数据预处理

较系统地介绍了从MODIS原始分发数据到海洋水色遥感反射率、离水辐射率等数据产品的产出过程;分析了各步骤原理,尤其针对标准大气校正算法无法计算出近岸二类水体离水辐射率问题提出邻近清洁水体外推混浊水体的思路;探索并改进了大气校正算法,计算出大部分近岸水体的离水辐射率数据。     

遥感数据的分形测量

用分形几何学方法对遥感数据进行了分析,从而定量解释遥感影像。共编制了３种分数维测量方法,它们是分线方法（或等值线方法）,方差方法和三角棱柱方法。用分线方法计算了腾冲地区陆地卫星ＴＭ数据的分数维。图像数据的等值线长度分别按行,按列和按行－列方法处理记取以便能发现图像的模式变化。当图像有明显的走向模式时,按行方法所测量的Ｄ值与按列方法测得的Ｄ值是不同的。按行－列方法测量的Ｄ值几乎不受定向模式的影响。当Ｒ（相关系数）＞０．９时,按３种方式记取等值线所得到的Ｄ值的变化趋势是一致的,都能给出图像数据中的空间相互关系。通过分维测量,不但能描述图像数据的整体特征而且能描述图像数据中的每个值的特征,揭示遥感数据表观的无序性和内在的规律性,更重要的是可把这些Ｄ值与地面物体之间建立联系来探讨各种自然现象中的有用信息。     

基于遥感和GIS的洪水坝河流域冰川变化研究

以洪水坝河流域为例,利用1956年的地形图和2003年的ASTER遥感影像及数字高程模型,在GIS的支持下对两期数据进行统计分析,结果表明:近47年来,洪水坝河流域冰川面积减少了14.04%,长度退缩了17.28%,储量减少了2.26%。研究认为,气温显著升高是洪水坝河流域冰川快速萎缩的主要原因。在和祁连山地区、西藏以及天山地区的冰川进行对比后,发现研究区冰川消融的速率介于三地之间,初步推测是由研究区所在区域的气候和自身属性共同作用的结果。     

基于IHS的多源遥感数据融合

首先简要叙述了IHS法在遥感图像融合中的应用,然后对实验结果进行了分析,并用融合后的图像建立了土地利用类型的解译标志,以期为HIS法用于遥感图像融合提供参考。     

多源遥感影像融合

遥感影像融合能富集同一地区不同数据源的信息大跨度波谱特性影像数据的融合,提供了有关各单个传感器的互补信息,使分类更精确;大跨度空间分辨力影 融合,有利于改善２多光谱影像的度,增强特征提取和目视判读能力,能有效地用于变化监测。     

Contrasting Signals of Glacier Changes in Zanskar Valley,Jammu & Kashmir,India Using Remote Sensing and GIS

The study of advancement and recession of the glaciers in the Himalayas is essential due to their contrasting response towards climatic change. In the present study, Survey of India (SOI) topographical maps of 1962, IRS: LISS-III image of 2001 and LANDSAT-5: TM (Thematic Mapper) image of 2009 were used to analyze the glacier fluctuations in a part of Zanskar valley. The analysis carried out on 212 glaciers indicated decrease of 57 km² (8 %) of glacier area over many glacier which was partly compensated with area increase by 42 km² (6 %) in other glaciers, resulting an overall glacier area decrease by only 15 km² (2 %) from 1962–2001. Due to glacier fragmentation the number of glaciers increased from 212 in 1962 to 238 by 2001. Although majority of glaciers (88 %) exhibited retreat (up to 13 my^?1), minor advancement (<15 my^?1) also took place in few glaciers during this period. Advancement took place mainly in larger glaciers (2–5 km² and >5 km²) located over wider altitudinal range (700 m–1,000 m) whereas smaller glaciers (<2 km²) with narrow altitudinal range (100 m–500 m) exhibited retreat. The supraglacial debris analysis indicated that percentage of debris cover over glaciers ranges from 1.43 % to 18.15 %. Smaller glaciers (<2 km²) were debris free in comparison to the larger glaciers (>5 km²). During 2001–2009 majority of the glaciers were apparently stable in terms of their area and snout position indicating less impact of climate forcing in parts of Zanskar valley as compared to other parts of the Himalaya.     

一种基于高光谱遥感数据的植被LAI反演算法

针对高光谱遥感数据反演叶面积指数(LAI)的问题,提出了基于主成分变换(PCA)的综合反演算法。研究表明,利用变换后的高光谱数据建立的神经网络反演模型具有更好的泛化性,提高了实测数据的反演稳定性和精度,同时加快了反演速度。     

Multiple Classifier Systems for Hyperspectral Remote Sensing Data Classification

One of the most widely used outputs of remote sensing technology is Hyperspectral image. This large amount of information can increase classification accuracy. But at the same time, conventional classification techniques are facing the problem of statistical estimation in high-dimensional space. Recently in remote sensing, support vector machines (SVMs) have shown very suitable performance in classifying high dimensionality problem. Another strategy that has recently been used in remote sensing is multiple classifier system (MCS). It can also improve classification accuracy by combining different classifier methods or by a diversity of the same classifier. This paper aims to classify a Hyperspectral data using the most common methods of multiple classifier systems i.e. adaboost and bagging and a MCS based on SVM. The data used in the paper is an AVIRIS data with 224 spectral bands. The final results show the high capability of SVMs and MCSs in classifying high dimensionality data.     

小波变换在遥感图像数据融合中的应用

用小波变换实现了一种新的遥感图像数据融合方法 ,该方法采用梯度算法对不同尺度子带数据进行融合 ,用加权法对基带数据进行融合。给出了 SAR图像与 TM图像的融合结果的定性评价 ,并用熵及平均梯度进行了定量评价     

利用决策级融合进行遥感影像分类

提出了一种基于决策级融合的遥感影像分类方法。该方法对遥感影像特征以最大似然分类器进行预分类,应用Adaboost算法将分类的结果进行决策级融合,实现影像的分类。实验结果表明,该方法的分类精度较传统分类方法有明显的提高。     

多源遥感数据快速自动处理技术探讨

甘肃省地图院利用国内外先进的现代测绘技术,构建了集地理信息采集、处理、贮存、管理于一体的信息化测绘生产体系,完成了信息化测绘生产基地的构建[1]。多源遥感数据快速自动处理技术应用研究是信息化测绘生产技术应用研究的一方面,主要是利用以信息化测绘生产基地为依托的遥感影像集群数据处理系统完成。本文主要探讨如何快速自动处理多源遥感数据,并以ADS80数据为例,对集群系统构建前后的效率进行对比实验。     

基于小波变换的遥感图像压缩

遥感图像的压缩领域中,小波分析理论为其提供了新的压缩方法和压缩思路,比较好地解决了遥感图像的压缩和传输问题。而小波基的选择直接决定了图像压缩的压缩效果和压缩速度,着重对比了不同的小波基性质对图像压缩带来的效果,给出了小波基选择的原则,并通过对各种小波性质的总结,选择双正交小波基（D5/3）应用于遥感图像的压缩     

遥感数据尺度特征的研究进展

遥感传感器多样化发展引领了遥感数据空间分辨率和时间分辨率多样化,形成了完善的遥感数据层次体系,为地球表面现象的表达和应用提供了大量的数据源。在不同尺度数据的综合应用过程中,尺度特征凸显重要。本文根据国内外的研究现状对遥感影像尺度特征的研究进行了分析,并对当前研究中面临的问题进行了探索,最后对遥感影像尺度特征将来发展趋势与前景进行了分析和展望。     

Feature Extraction in Remote Sensing High-Dimensional Image Data

High-dimensional image data open new possibilities in remote sensing digital image classification, particularly when dealing with classes that are spectrally very similar. The main problem refers to the estimation of a large number of classifier's parameters. One possible solution to this problem consists in reducing the dimensionality of the original data without a significant loss of information. In this letter, a new approach to reduce data dimensionality is proposed. In the proposed methodology, each pixel's curve of spectral response is initially segmented, and the digital numbers (DNs) at each segment are replaced by a smaller number of statistics. In this letter, the proposed statistics are the mean and variance of the segment's DNs, which are supposed to carry information about the segment's position and shape, respectively. Tests were performed by using Airborne Visible/Infrared Imaging Spectrometer hyperspectral image data. The experiments have shown that this methodology is capable of providing very acceptable results, in addition of being computationally efficient