轻型飞机成像光谱图象几何校正技术研究

成像光谱测量技术是近年来遥感领域的发展前沿之一，该技术以高光谱分辩率、高空间分辩率、高时相分辨率及普像合一为主要特征，在国民经济各个领域得到广泛应用。在剖析轻型飞机成像光谱测量系统成像环境特征的基础上，深入研究了低空遥感图象几何学理论，并利用数学模型分析方法，建立了航空成像光谱图象几何畸变模式及几何校正模型；提出了适合本系统的几何处理流程。利用所建立的几何校正模型和软件，对机载可见光/短波红外成像光谱数据进行了几何特性分析及几何校正，取得较好的图象处理效果，并证实了系统的实用性。     

机载成像光谱数据的航带计算及其Internet发布

机载的成像光谱数据具有很大的应用价值,通过Internet发布有关成像光谱数据的信息,将推动成像光谱数据的应用。在用户检索成像光谱数据的过程中,有“何地”的数据是用户非常关注的内容。本文首先阐述了成像光谱仪的扫描原理与位置姿态数据的获取步骤,在此基础上指出机载成像光谱数据的航线与航带的计算方法。WebGIS是Internet上发布有关成像光谱数据的信息的有效平台,文章介绍了基于WebGIS发布有关成像光谱数据的信息的主要实现技术。     

一类特定目标的航空成像光谱数据辐射校正算法

针对宽视场线阵扫描成像光谱数据和农田地块这一特定目标,提出了一种基于统计原理的简化综合辐射校正方法。结果证明,该算法对由飞行方向、传感器扫描角度、太阳方位角和高度角以及路径辐射等造成的综合辐射畸变具有良好的校正效果。     

Offner成像光谱仪的设计与航拍实验

介绍一种Offner结构高分辨率推扫式成像光谱仪的设计,包括光学结构设计、数据获取与存储系统配置、基于数据库的光谱图像拼接软件设计以及成像光谱仪波长标定和辐射标定方法.其次介绍成像光谱仪在青藏高原陆面敏感因子航空遥感实验中的使用情况,包括实验概况、成像光谱仪及其采集系统在机舱内的安装调试、光谱仪的航拍参数以及航带光谱图像的拼接处理,最终获取到高分辨率的高光谱图像立方体.仪器的首次航拍飞行实验取得预期成果.     

机载多光谱扫描图象几何畸变的全自动校正

分析了引起机载多光谱扫描图象几何畸变的各种主要因素，提出并建立了利用由惯性导航系统同步记录的飞机姿态、运动和位置参数校正机载多光谱扫描图象几何畸变的方法模型。试验结果表明，与传统采用控制点的方法相比，该方法不仅具有较高的校正精度，而且可由计算机全自动完成。     

成像光谱仪图像数据特征和实时处理系统

一、引言本文通过分析成像光谱仪图像数据的特征,提出减少和压缩成像光谱仪数据率的可能性和实施方案,并研制了一套成像光谱仪图像实时处理系统。成像光谱仪以它高光谱分辨率的强大优势而将成为90年代新型的遥感仪器。它把传统的二维空间遥感技术与光谱仪的技术有机地相结合发展成“图谱合一”的三维遥感技术。为了探测到地物光谱的吸收和反射特征,目前的成像     

CCSDS压缩算法对高光谱数据质量的影响研究

成像光谱仪能够探测获取目标的空间信息和光谱信息,逐渐在军事/民用遥感领域广泛应用.然而随着成像光谱仪的空间分辨率和光谱分辨率的提高,数据量也飞速提高.受数据下行链路带宽限制,星载高分辨率成像光谱仪所获取的海量数据必须进行有损压缩,而采用有损压缩又带来了一个关键问题:有损压缩所造成的数据失真究竟会对高光谱数据质量及后续遥感应用造成怎样的影响.本文基于CCSDS压缩算法的两种压缩方案,从统计性能、辐射性能、空间性能、光谱性能和应用性能5个方面,系统性分析了数据压缩对高光谱数据质量造成的影响.结果表明,利用高光谱数据的高谱间相关性,采用谱间去相关与CCSDS空间数据压缩相结合的方案,与直接采用CCSDS进行空间数据压缩的方案相比,具有更好的压缩性能,对高光谱数据质量造成的影响更小.     

POS数据在机载干涉SAR运动补偿中的应用

提出了一种利用高精度的定位定向系统(POS)数据,在SAR成像阶段实现机载干涉SAR运动补偿及图像配准的成像处理方法。该方法针对机载干涉SAR系统的双天线雷达数据对的特点,在成像阶段直接利用高精度的POS数据完成干涉SAR图像对的位置误差补偿、干涉相位误差补偿以及自动配准等过程。实际处理结果表明,该方法可以有效地提高机载干涉SAR的图像质量,改善复图像对之间的相干性,非常适用于机载双天线干涉SAR雷达数据的成像处理过程。     

成像光谱技术在土地利用动态遥感监测中的应用研究

随着数字化调查技术的发展，国土资源管理对土地利用动态遥感监测提出了更高的要求，目前主要采用的多光谱数据由于受光谱分辨率限制以及“同谱异物，同物异谱”现象的影响，难以满足管理需要。成像光谱数据具有较高光谱分辨率。在类别细分方面具有一定的优势，在当前土地利用动态遥感监测中具有一定的应用潜质。该文针对成像光谱数据特点，探索了与成像光谱数据相适应的土地利用动态遥感监测方法，提出了异常光谱检测法，该方法在试验区应用中取得了良好效果。     

地理因子对卫星成像质量影响预估方法研究

重点研究地理因子对卫星成像质量的影响,预估影响程度,为卫星规划调度提供辅助决策信息。本文分别分析光照、地形起伏、云层3个地理因子对可见光传感器成像质量的影响,给出考虑这些因素的可见光传感器辐射接收计算公式,并结合ArcGIS分析功能,建立了地理因子对可见光传感器成像质量影响预估模型。同时,考虑地形起伏对SAR成像的影响,给出了利用DEM数据求几何畸变系数的方法,利用ArcGIS建立地理因子对SAR成像质量影响预估模型。两个模型都给出了成像质量影响程度预估值计算方法,最后,本文基于ArcGIS软件实现其原型系统。     

Radiometric normalization of sensor scan angle effects in optical remote sensing imagery

Radiometric distortions along the scan line, caused mainly by the atmosphere, reflection properties of the imaged surface objects, and topography are observed frequently in images acquired by optical remote‐sensing sensors, especially airborne sensors with a wide field of view. In practical applications, such as classification or mosaicking of image data, a relative correction or normalization of these radiometric distortions is needed. Therefore, the goal of this paper is to derive a relative correction algorithm for multispectral line scanner images, which allows the spectral radiance values for different scan angles to be converted to radiance values of a defined reference scan angle. Under the simplifying assumption of complete diffuse reflectors, these radiometric distortions are modelled using a linear equation between the radiances of a pair of scan angles for each class of surface objects separately. A linear regression, applied to all these equations, results in a linear model for the radiance correction, a new empirical radiometric correction method, which is a generalization of earlier proposed strictly additive or multiplicative models. The proposed method is based solely on the digital image data. So, no additional information or user interaction is required, and the method is fully automatic. Applications for data acquired with the airborne multispectral scanner DAEDALUS AADS 1268 ATM show the effectiveness and potential of the proposed method especially for mosaicking and classification purposes.     

Refinement of wavelength calibrations of hyperspectral imaging data using a spectrum-matching technique

The concept of imaging spectrometry, or hyperspectral imaging, is becoming increasingly popular in scientific communities in recent years. Hyperspectral imaging data covering the spectral region between 0.4 and 2.5 μm and collected from aircraft and satellite platforms have been used in the study of the earth's atmosphere, land surface, and ocean color properties, as well as on planetary missions. In order to make such quantitative studies, accurate radiometric and spectral calibrations of hyperspectral imaging data are necessary. Calibration coefficients for all detectors in an imaging spectrometer obtained in a laboratory may need to be adjusted when applied to data obtained from an aircraft or a satellite platform. Shifts in channel center wavelengths and changes in spectral resolution may occur when an instrument is airborne or spaceborne due to vibrations, and to changes in instrument temperature and pressure. In this paper, we describe an algorithm for refining spectral calibrations of imaging spectrometer data using observed features in the data itself. The algorithm is based on spectrum-matching of atmospheric water vapor, oxygen, and carbon dioxide bands, and solar Fraunhofer lines. It has been applied to real data sets acquired with airborne and spaceborne imaging spectrometers.     

A simplified method for retrieval of ground level reflectance of targets from airborne video imagery

This paper describes an efficient method for retrieval of ground reflectance characteristics of targets from calibrated multispectral airborne video data for routine operational airborne missions. The method uses a simplified atmospheric scattering model in combination with a dark-object subtraction procedure to estimate the effect of the atmosphere in the path between the target and the sensor, as well as the adjacent environmental effect, on the radiation signal received by an airborne sensor. The simplicity of the atmospheric scattering model is maintained by the assumption that the air density within the targetsensor path in the lower atmosphere is sufficiently uniform for operations of the Charles Sturt University's (CSU) Multispectral Airborne Video System (MAVS). The MAVS acquires imagery in blue, green, red and near-infrared (NIR) narrow spectral bands. The MAVS is radiometrically calibrated and has a consistent radiometric response in-flight. An important feature of the new method is the coupling of the image based brightness data (DN) of a dark-object and the system radiometric calibration coefficients to determine the path reflectance and the environmental reflectance of the target. The sum of the path reflectance and the environment reflectance is known as haze reflectance. The haze reflectance indicates the amount of atmospheric haze in the airborne imagery. The simplified atmospheric model is then employed to determine the actual ground reflectance of the targets using the haze subtracted apparent (total) reflectance of the target at the altitude of the airborne sensor. The apparent reflectance of the target at the sensor altitude is obtained directly from the image based DN data and the system radiometric calibration coefficients. An interesting aspect of this simplified method is that an estimate of the environmental reflectance can be obtained as a by-product of the atmospheric haze calculation using a dark-object subtraction technique. The retrieved ground reflectance characteristics from calibrated MAVS imagery are now being used routinely for remote quantitative monitoring of agricultural and environmental targets.     

Spectral and radiometric requirements for the airborne thermal imaging spectrometer ARES

ARES (Airborne Reflective/Emissive Spectrometer) is an airborne imaging spectrometer for remote sensing of land surfaces covering the wavelength regions 0.45–2.45?µm and 8–13?µm with 160 channels. The instrument is being built by Integrated Spectronics, financed by DLR and GFZ, and will be available to the scientific community from 2005 on.

This contribution presents the design of the thermal spectrometer covering the 8–13?µm region with 32 channels of 150?nm bandwidth while a separate paper treats the instrument specifications in the solar reflective region. The spectro‐radiometric design is based on scientific requirements derived from application scenarios comprising vegetation, soils of different compositions, and mineral exploration. The corresponding emissivity spectra are input for a simulation model that calculates at‐sensor radiance spectra, resamples them with the channel‐specific response functions, adds different amounts of sensor noise to the signal, and performs a retrieval to get the corresponding noisy surface emissivity spectra. The results of the simulation study indicate that a spectral wavelength accuracy of 3?nm and a sensor noise equivalent temperature of 0.05–0.1?K are required for an accurate retrieval of emissivity spectra.     

Generation of geometrically and radiometrically terrain corrected SAR image products

Terrain undulations affect the geometric and radiometric quality of synthetic aperture radar images. The correction of these effects becomes indispensable when quantitative image analysis is performed with respect to the derivation of geo- and biophysical parameters. The paper presents a rigorous approach for geometric and radiometric correction of SAR images. Using a digital elevation model, the imaging geometry is reconstructed and is used to perform geometric and radiometric correction of terrain induced distortions. The importance of a stringent radiometric correction based on the integration of the image brightness is emphasized. The approach guarantees that the energy contained in the image data is preserved throughout the geocoding process. The resulting backscattering images are fully terrain corrected and can be used for further quantitative investigations and may also improve qualitative studies as e.g. land cover classifications. The technique is applicable for different sensor types and image products, including already geocoded SAR images. The effect of different resolutions of digital elevation models used for the correction of the backscattering coefficient is investigated.     

Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/topographic correction

A method for the radiometric correction of wide field-of-view airborne imagery has been developed that accounts for the angular dependence of the path radiance and atmospheric transmittance functions to remove atmospheric and topographic effects. The first part of processing is the parametric geocoding of the scene to obtain a geocoded, orthorectified image and the view geometry (scan and azimuth angles) for each pixel as described in part 1 of this jointly submitted paper. The second part of the processing performs the combined atmospheric/ topographic correction. It uses a database of look-up tables of the atmospheric correction functions (path radiance, atmospheric transmittance, direct and diffuse solar flux) calculated with a radiative transfer code. Additionally, the terrain shape obtained from a digital elevation model is taken into account. The issues of the database size and accuracy requirements are critically discussed. The method supports all common types of imaging airborne optical instruments: panchromatic, multispectral and hyperspectral, including fore/aft tilt sensors covering the wavelength range 0.35-2.55 w m and 8-14 w m. The processor is designed and optimized for imaging spectrometer data. Examples of processing of hyperspectral imagery in flat and rugged terrain are presented. A comparison of ground reflectance measurements with surface reflectance spectra derived from airborne imagery demonstrates that an accuracy of 1-3% reflectance units can be achieved.     

Cover. Wind energy mapping of coastal zones by synthetic aperture radar (SAR) for siting potential windmill locations

MERIS (Medium Resolution Imaging Spectrometer) is a fine spectral and medium spatial resolution satellite sensor and is part of the core instrument payload of Envisat, the European Space Agency's (ESA) environmental research satellite, launched in March 2002. Designed primarily for ocean (‘MER’) and coastal zone remote sensing, this imaging spectrometer (‘IS’) now has a much broader environmental remit covering also land and atmospheric applications. This paper reviews (i) MERIS's development history, focusing on its changing mission objectives; (ii) MERIS's technical specification, including its radiometric, spectral and geometric characteristics, programmability and onboard calibration; (iii) decisions that led to modifications of MERIS's spectral, geometric and radiometric performance for land applications; (iv) MERIS's data products; and (v) some of the ways in which MERIS data might be used to provide information on terrestrial vegetation.     

Satellite-driven modelling of Net Primary Productivity (NPP): Theoretical analysis

Ecological models are central to understanding the global hydrological and carbon cycles, and need data from Earth Observation to function effectively at regional to global scales. Here, we develop and apply an end-to-end analysis that relates the requirements of ecological models to the capabilities of satellite-sensors, starting with radiometric noise at the instrument, which collects the information, running through to the error on the estimated NPP output from the ecological model. In the process, the input requirements of current ecological models are reviewed. Our aim is to establish a better informed framework for the design and development of future satellite-sensor missions, which meet the needs of ecological modellers. Three mathematical models (PROSPECT, FLIGHT and 6S) are coupled and inverted using a technique based on LUT. The LUT are used to estimate biophysical variables of vegetation canopies from remotely-sensed data observed at the TOA in a number of viewing directions and in several wavebands within the visible and near-infrared spectrum. The five variables considered here are LAI, leaf chlorophyll content (C_ab), fAPAR, cover fraction and AOT. Different sensor configurations are investigated, in terms of directional and spectral sampling. The retrieval uncertainty is linked with the instrument radiometric accuracy by analysing the impact of different levels of radiometric noise. The parameters retrieved via the inversion are used to drive two LSP models, namely Biome-BGC and JULES. The effects of different sensor configurations and levels of radiometric noise on the NPP estimated are analysed. The system is used to evaluate the sensor characteristics best suited to drive models of boreal forest productivity. The results show that multiangular information improves dramatically the accuracy with which forest canopy properties are estimated. Due to problems of equifinality, the results show a persistence of error even in the presence of zero noise from the sensor, although decreasing the level of radiometric noise from 0.02 to 0.001 reduces error in the estimated NPP by 10% to 25%.     

Projection‐type integral 3‐D display with distortion compensation

Abstract— Our research is aimed at developing a spatial‐imaging‐type integral three‐dimensional (3‐D) display based on an integral photography method using an extremely high‐resolution projector. One problem with the projection‐type integral 3‐D display is that geometrical distortion in projected elemental images causes spatial deformation of the displayed 3‐D image. In this study, a general relationship between the geometric distortion of elemental images and the spatial deformation of reconstructed 3‐D images were analyzed. A projection‐type integral 3‐D display with a distortion compensator which corrects the geometrical distortions of projected images in real‐time have been developed. The deformation of the displayed 3‐D images was significantly reduced by the distortion compensation, and the displayed 3‐D images had a resolution of 182 (H) × 140 (V) pixels and a viewing angle of 24.5°.     

MAIS图像大气订正及其在岩矿制图中的应用

：针对１９９５年９月１３日在内蒙大青山地区的一次ＭＡＩＳ航空遥感飞行试验,给出了一种以地面大气同步测量为前提、基于计算机查找表的大气订正方法。该方法具有简单、实用等特点,特别适合于像航空成像光谱遥感这样大数据量的图像定量信息获取。在可见、近红外光谱区（０．４～１．２μｍ）,该方法的订正精度约为８．５％（总误差）,即反射率在３％～５０％范围内时,反射率获取精度约为０．００２～０．０５反射率单位。利用大气订正后的ＭＡＩＳ反射率图像,得到了中粒钾长花岗岩、绿泥化片麻岩和灰岩这三种岩矿在该试验区的空间分布。与地面勘查结果比较表明,大气订正后的高光谱分辨率航空成像遥感数据（如ＭＡＩＳ）可用于干旱、半干旱地区的岩矿分布研究与制图。