机载中波红外影像分类性能分析

由于中波红外谱段复杂的辐射特性以及红外探测技术的限制,目前学界对中波红外的遥感分类应用探索较少。该文是在国内首幅可见光-中波红外高分辨率(中波红外0.6m分辨率)多光谱影像的基础上,探索地物的中波红外辐射特性,挖掘中波红外谱段的潜在价值,进而融合地物的中波红外与可见光的特征,分析中波红外影像的地物分类性能,提高遥感地物分类的精度。中波红外谱段的光谱辐射特性不同于可见光与热红外谱段,既包含地面反射辐射,也包含地面物体的发射辐射能量。研究中基于多尺度分割算法与随机森林分类器分别对可见光影像和中红外+可见光四波段融合影像进行面向对象分类。该方法融合了地物的可见光与中波红外特征,并且评估了光谱、形状、纹理等特征在分类中的重要程度,定量分析了融合中波红外波段后的特征空间。研究结果表明:针对中红外特征,最有效特征为中红外与可见光其中两波段组合HIS空间各分量特征,其次为灰度共生矩阵纹理信息;中波红外波段的引入可以稳定地提高地物分类的总精度;中波红外波段对于人工地物的分类效果优于非人工地物类型,其中建筑物的分类精度提升最为显著。     

微波遥感中的地物光谱特性研究

地物光谱特性研究是遥感中的一项重要的应用基础研究,对传感器波段的选择,遥感图象的解译和处理,数字图象的识别,大气传输过程中遥感信息的校正及新的遥感领域的开拓等均具有重要意义.它可分为四个波段,即反射光谱波段(0.3～2.5微米)、反射一发射光谱波段(3—5微米)、发射光谱波段(8～14微米)和微波波段(1mm—30cm).目前,可见光和红外波段的地物光谱特性研究比较充分,积累资料比较多,微波波段则比较薄弱,起步也较晚,正在大力研究发展之中.     

基于图像分割的无人机遥感影像目标提取技术

为全面增强遥感影像上地物波谱的反射特性能力,实现对无人机目标的无误提取,提出基于图像分割的无人机遥感影像目标提取技术;在类哈尔滤波器结构的支持下,按照区域环境中地物目标的颜色特征,完成低层影像特征的量化处理,实现基于图像分割技术的无人机遥感深度图获取;定义与无人机遥感影像相关的基本名词,通过原始特征选择的方式,判定地物波谱的平均反射特性水平,得到准确的特征元素相关性测度数值,完成无人机遥感影像的目标融合处理;在此基础上,分割多分辨率条件下的影像目标,在定义图像纹理与尺度条件的同时,得到最终的地物提取结果,实现基于图像分割无人机遥感影像目标提取技术的应用;对比实验结果表明,在初始采集相位条件及亚像素条件下,目标地物的波谱宽度均超过7.0μm,遥感影像的反射特性能力大幅提升,满足对无人机目标无误提取的实用需求。     

基于地物反射特性的多波段遥感图像无损压缩方法

要实现多波段遥感图像的无损压缩,去除空间和谱间的相关性是其中的重要环节。通过分类,分析不同地物在不同波段的反射特性,再根据不同地物的波段反射特性构造出针对不同地物的谱间预测器,用以去除谱间相关性。对于去除谱间相关的残差图像,采用Ｓ＋ Ｐ变换,以去除空间相关。实验取得了令人满意的效果,证明了这种方法的有效性。     

一种有效的多波段遥感图像无损压缩方法

首先利用分类的方法,得到同一地物在不同波段的光谱反射特性,在此基础上构造谱间预测器,去除谱间相关性,再对残差图像采用S＋P变换去除空间相关性,然后,利用改进的分级树的集合划分（SPIHT）方法,实现遥感图像的高效无损编码,实验表明本方法取得满意的结果,显示了本方法在多波段遥感图像压缩中的潜力。     

新疆北部地质矿产遥感探测

地处欧亚大陆腹地的新疆北部地区,呈近东西向,由北至南发育有阿尔泰、准噶尔及天山褶皱带,蕴藏着丰富的矿产资源。该地区内气候干燥、植被稀疏,基岩广泛裸露,遥感技术的应用,无疑可发挥其特有的作用。地质体的反射、辐射、散射特性,构成了电磁波的四个波段窗口对地质矿产的有效探测能力。波长范围0.4—1.1μm的可见光—近红外波段可识别铁的氧化物;1.1—2.5μm的短波红外对含羟基矿物敏感;8—14μm的中红外波段是识别硅酸盐矿物的理想波段;0.8—23.5cm的微波区在控矿构造研究中具有显著效果。相应于这些工作波段的机星载传感器     

一种飞机目标及典型地物红外辐射仿真方法

机场场景内的飞机目标及其所处的地物背景具有重要军事应用价值,为了实现对这类目标的检测、识别以及动态监测,需要一套能够在不同季节、不同气象条件、不同时段、不同探测波段等条件下机场场景内飞机/地物红外辐射仿真的软件来提供训练样本。在Visual Studio 2010环境下,利用OpenGL构建了典型机场场景下飞机及地物背景模型,结合传热学和红外辐射理论的分析,将一款用于热红外分析的RadThermIR软件内核嵌入算法中,提出一种计算飞机及其地物背景的红外辐射场模型和构建其红外图像仿真方法。以图像灰度相似度作为评价指标,该方法和真实红外图像相比,仿真精度高于80%,实验结果表明,该方法可为实现全天候机场场景下飞机目标自动检测识别提供丰富的红外特性分析数据和特性知识训练样本。     

Worldview 3全色与短波红外影像两步式融合框架

Worldview 3是目前最先进的高分辨率光学卫星之一。针对Worldview 3遥感卫星数据全色波段和短波红外波段（Short-Wave Infrared,SWIR）空间分辨率差异大、波谱范围不一致所导致的融合结果块状效应以及空间分辨率增强效果有限的问题,提出一种两步式影像融合框架。该框架降低全色波段空间分辨率,实现与SWIR波段的初步融合;将初步融合的结果与原始分辨率全色波段进行第二步融合。通过选择6种典型像素级融合方法两两组合,形成36种融合方案,验证框架的可用性。选取包含植被、建筑、水体等典型地物类型的Worldview 3数据集进行实验,并采用五个定量评价指标进行评价。实验结果表明：使用两步式融合框架进行融合,通过渐进式空间细节注入的方式,避免了直接融合产生的块状效应,实现了短波红外影像的空间分辨率增强;第一步融合采用高通滤波（HPF）融合法,第二步融合采用GS（Gram-Schmidt Transform）变换融合方法,引入的空间信息最多,获得的融合结果质量最好。提出的融合框架既能避免块状效应的产生,又能有效增强SWIR波段的空间分辨率,对于其他卫星的全色与短波红外波段的融合也具有一定借鉴意义。     

风云三号传感器红外通道海表比辐射率模拟

海表比辐射率（SSE）是从卫星被动遥感数据反演海表温度（SST）的关键参数之一,本文讲述了利用Wu andSmith（1997）发展的SSE模型,对搭载在风云三号（FY-3A）上的红外大气探空仪（IRAS）第8（12.47μm）、9（11.11μm）、19（3.98μm）和20（3.76μm）波段,中分辨率光谱成像仪（MERSI）第5波段（11.54μm）,可见光红外扫描辐射计（VIRR）第3（3.65μm）、4（11.00μm）和5（12.13μm）波段的SSE进行模拟计算。模拟结果表明,SSE是观测角度、波长和海表粗糙度（海面风速）的函数。模拟值与IRAS、MERSI和VIRR红外通道波谱响应函数进行卷积计算得到波段SSE。在观测角度小于60°时,波段SSE对海面风速不敏感,使用风速为8m/s的SSE替代其他风速条件下的SSE所引起的误差小于0.5%。另外,使用波段SSE计算卫星观测值所导致的误差不超过0.05K,可以忽略不计。波段SSE随观测角度变化的规律可以用高斯函数进行描述,拟合误差小于0.02%,相关系数为1.000。本文的模拟结果可以用于SST的精确反演。     

卫星热红外遥感在地震预测中的应用——以中苏边界附近的斋桑泊1990年两次地震为例

一、卫星热红外遥感利用星载辐射仪器遥测目标物的辐射特性来测量它们的某些参数及变化规律,如我国风云一号卫星所载的主要探测仪器之一AVHRR(改进的甚高分辨率扫描辐射仪)具有5个波段,即可见光、近红外和热红外波段。其中可见光和近红外波段用于探测目标物的反射太阳辐射特征,而热红外波段用于探测地球     

Regression-based synergy of optical, shortwave infrared and microwave remote sensing for monitoring the grain-size of intertidal sediments

A method is developed for monitoring the sediment grain-size of intertidal flats in the Westerschelde (southwest Netherlands), using information from both space-borne microwave (SAR) and optical/shortwave infrared remote sensing. Estimates of the backscattering coefficient were extracted from time-series of C-band ERS SAR imagery. Surface reflectance in the visible, near-infrared (VNIR) and shortwave infrared (SWIR) part of the electromagnetic spectrum, as well as spectral indices, were derived from matching multi-temporal Landsat TM imagery. In addition, surface reflectances were derived from a set of airborne multispectral (VNIR) CASI images, and hyperspectral (VNIR) measurements using a field spectroradiometer. The data were related to matching field measurements of surface characteristics, including sediment properties. Regression-based algorithms were developed to map the spatio-temporal distribution of mud content using (a) the C-band SAR backscattering coefficient, (b) surface reflectance in the green and SWIR, and (c) a combination of these, with corroborative field measurements. Mud content of the sediment has been successfully mapped by all three algorithms, but a combination of information from microwave and VNIR/SWIR provided best results. The algorithms were generally consistent in time, making them suitable for generating time-series and for monitoring. However, they should be validated and calibrated in order to be applicable to other intertidal areas.     

Spectral indices for lithologic discrimination and mapping by using the ASTER SWIR bands

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a research facility instrument launched on NASA's Terra spacecraft in December 1999. Spectral indices, a kind of orthogonal transformation in the five-dimensional space formed by the five ASTER short-wave-infrared (SWIR) bands, were proposed for discrimination and mapping of surface rock types. These include Alunite Index, Kaolinite Index, Calcite Index, and Montmorillonite Index, and can be calculated by linear combination of reflectance values of the five SWIR bands. The transform coefficients were determined so as to direct transform axes to the average spectral pattern of the typical minerals. The spectral indices were applied to the simulated ASTER dataset of Cuprite, Nevada, USA after converting its digital numbers to surface reflectance. The resultant spectral index images were useful for lithologic mapping and were easy to interpret geologically. An advantage of this method is that we can use the pre-determined transform coefficients, as long as image data are converted to surface reflectance.     

Land cover classification in SE Asia using near and short wave infrared bands

A land cover classification map is necessary for modelling interactions between the land surface and the atmosphere, monitoring the environment and estimating food production. In order to classify land cover in SE Asia in 2000, Normalized Difference Vegetation Index (NDVI), reflectance of near-infrared (NIR) band, and reflectance of short wave infrared (SWIR) band of Systeme pour l'Observation de la Terre (SPOT) VEGETATION data were used in this study. First, ground data were collected for training data. In addition, supervised classification was performed on twelve months of NDVI data. As a result, some deserts and peripheral sparse vegetative areas were classified into urban, compared with the world atlas. Secondly, the number of months when the reflectance of the SWIR band is higher than that of the NIR band was counted (SWIR>NIR month-count condition) in each pixel, and pixels with counts of 10 were classified as Sparse Herbaceous/Shrub and of 11 or 12 were classified as Bare Areas, respectively. Finally, land cover was classified based on the SWIR>NIR month-count condition combined with NDVI, and it was compared with the existing land cover map. It was found that the SWIR>NIR month-count condition gives a better result for areas of non- or sparsely vegetative classification than when using only NDVI.     

面向多业务用户体验的基站节能策略研究

随着ICT行业的快速发展,无线通信网络的密集部署和应用普及,随之带来的高能耗和碳排放问题给环境造成了巨大影响。用户关联的基站关闭策略能有效减少能耗,现有策略主要针对用户接收服务质量进行方法设计,并未充分考虑具体业务特征以及用户体验。引入了用户体验质量指标QoE,提出了一种面向多业务用户体验的基站节能策略ES-MSUE。采用非线性整数规划对问题进行建模,实现了用户体验和能耗之间的均衡。通过与其他相关基站关闭策略进行对比实验,结果表明提出的方法具有较好的节能效果和用户体验质量。     

Influence of land surface effects on MODIS aerosol retrieval using the BAER method over Korea

As satellite receiving signals are affected by complex radiative transfer processes in the atmosphere and on land surfaces, aerosol retrieval over land from space requires the ability to determine surface reflectance from the remote measurements. To use the Bremen Aerosol Retrieval (BAER) method for aerosol optical thickness (AOT) retrieval over land at a spatial scale of 1×1 km² from Moderate Resolution Imaging Spectroradiometer (MODIS) data, a linear mixing model with a vegetation index was used to calculate surface reflectances. As the vegetation index is affected by the aerosol present in the atmosphere, an empirical linear relationship between short wavelength infrared (SWIR) channel reflectance and visible reflectance was estimated to calculate a modified aerosol free vegetation index (AFRI) value. Based on a modified AFRI obtained from MODIS SWIR channel reflectance, an improved linear mixing model was applied for aerosol retrieval. A comparison of results between calculated and apparent surface reflectance was satisfactory, with a linear fit slope above 0.94, correlation coefficients above 0.84, and standard deviation below 0.008 for the study area. These results can therefore be used for improved aerosol retrieval over land by the BAER method with MODIS Level 1 data.     

An object-oriented daytime land fog detection approach based on NDFI and fractal dimension using EOS/MODIS data

A new approach for land fog detection using daytime imagery from Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data based on the normalized difference fog index (NDFI) is proposed. NDFI is used to discriminate fog from clouds based on simulating and analysing the radiation characteristics of fog and cloud with MODIS data and the Streamer radiative transfer model. In this paper, in addition to the spectral and spatial characteristics of NDFI, the textural characteristics are introduced by using a fractal dimension. The fractal dimension is calculated with a differential box-counting approach to differentiate the texture characteristics of cloud and fog, and then the spectral and texture features are combined using an NDFI weighted fractal dimension algorithm as a new feature to improve the existing daytime fog detection approach. The performance of this approach is evaluated against ground-based measurements over China in winter, and the approach is proved to be effective in detecting land fog accurately based on the three cases.     

Influence of desert varnish on the reflectance of gossans in the context of Landsat TM data,southern Red Sea Hills,Sudan

Laboratory spectra have been used for studying the characteristics of desert varnish in the context of Landsat TM data in order to establish its influence on the reflectance of gossans and their discrimination. Supported by limited chemical analysis, reflectance values from selected rock samples have been processed using statistical methods, and spectral plots produced and visually interpreted. Spectral analysis shows that paucity and Mn/Fe proportion in desert varnish, lightness or darkness of the rock, its mineral composition, and the wavelength under consideration control the effect of desert varnish on Landsat TM data. In general, overall reflectance of rocks is reduced by up to 70% in the VIS parts and about 20% in the SWIR parts of the electromagnetic spectrum due to desert varnish. For acidic rocks this effect seems to be intense, whereas mafic rocks are less influenced. The latter generally display spectral crossovers partly due to Mn/Fe content. In the VIS region absorption bands turn to featureless spectra due to desert varnish, whereas in the SWIR spectra are generally subdued but preserved. This has apparently little consequence on the discrimination of gossans from other rock types on composites constituted by bands from the VIS, IR and SWIR parts.     

基于数据机理的植被叶面积指数遥感反演研究

定量获取地表植被高精度时序及空间覆盖的叶面积指数（Leaf Area Index, LAI）是生态监测及农业生产应用的重要研究内容。通过使用Moderate Resolution Imaging Spectroradiometer（MODIS）植被冠层多角度观测MOD09GA数据及叶面积指数MOD15A2数据,发展了一种参数化的叶面积指数遥感反演方法并完成了必要的检验分析。研究使用基于辐射传输理论的RossThick LiSparse Reciprocal（RTLSR）核驱动模型及Scattering by Arbitrarily Inclined Leaves with Hotspot（SAILH）模型进行植被冠层辐射特征的提取,使用Anisotropic Index （ANIX）异质性指数作为指示植被冠层二向反射分布Bidirectional Reflectance Distribution Function（BRDF）的辅助特征信息,发展了基于数据机理（Data-Based Mechanistic, DBM）的植被叶面积指数建模和估算方法。通过必要的林地、农作物、草地植被实验区反演及数值分析可得知：①时间序列多角度遥感观测数据结合数据机理的叶面积指数估算方法,可实现模型参数的时序动态更新,改进叶面积指数估算结果的时序完整性及精度。②异质性指数可以用做指示植被冠层二向反射分布特征信息,可降低因观测数据几何条件差异所导致的反演结果不确定情况,同时能够补充植被时序生长过程表现的植被结构变化等动态特征。经研究实践,可将算法应用于时空尺度的叶面积指数估算,并能够为生态、农业应用提供植被的高精度遥感监测指标。     

Identification of mineral components in tropical soils using reflectance spectroscopy and advanced spaceborne thermal emission and reflection radiometer (ASTER) data

Soil characteristics provide important support for understanding transformations that occur in environmental systems. Physical characteristics and chemical compositions of soils controlled by pedogenetic processes, climatic changes and land use imply different types of environmental transformations. Reflectance spectroscopy is an alternative soil mapping technique that uses spectral absorption features between visible (VIS) and short-wave infrared (SWIR) wavelengths (0.3-2.5 μm) for determining soil mineralogy. Soil analysis by means of reflectance spectroscopy and orbital optical sensors have provided favorable results in mapping transformation processes in environmental systems, particularly in arid and semiarid climates in extra-tropical terrains. In the case of inter-tropical environments, these methods cannot be readily applied due to local factors such as lack of exposed regolith, high amounts of soil moisture and the presence of dense vegetation. This study uses Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and reflectance spectroscopy data to map mineral components of soils covering a part of the state of São Paulo, Brazil, which could be linked to key aspects of environmental transformations in this tropical area (e.g., climate change, shifts in agriculture fronts, ph, and soil characteristics). We collected forty-two (42) soil samples at a depth of 0-20 cm, considering that this superficial layer corresponds to the highest correlation with soil properties detected by the ASTER sensor. These samples were measured using a FieldSpec FR spectrometer, and the derived spectra were interpreted for mineral composition. Interpretation was supported by X-ray diffraction analysis on the same samples. The spectral signatures were re-sampled to ASTER VNIR (AST1-4: 0.52-0.86 μm) and SWIR (AST5-9: 1.60-2.43 μm) spectral bandwidths and validated by comparing reflectance spectra of field samples with those extracted from atmospherically corrected and calibrated ASTER pixels. The agreement between spectral signatures measured from soil samples and those derived from ASTER imagery pixels proved plausible, with R² correlation values ranging from 0.6493 to 0.7886. This signifies that diagnostic spectral features of key minerals in tropical soils can be mapped at the spectral resolution of 9-band ASTER VNIR through SWIR reflectance. We used these spectral signatures as end-members in hyperspectral routine classifications adapted for use with ASTER data. Results proved possible the identification and remote mapping of minerals such as kaolinite, montmorillonite and gibbsite, as well as the distinction between iron-rich and iron-poor soils.