Landsat-5 TM and Landsat-7 ETM+ absolute radiometric calibration using the reflectance-based method

The reflectance-based method of vicarious calibration has been used for the absolute radiometric calibration of the Landsat series of sensors since the launch of Landsat-4. The reflectance-based method relies on ground-based measurements of the surface reflectance and atmospheric conditions at a selected test site nearly coincident with the imaging of that site by the sensor of interest. The results of this approach are presented here for Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper Plus (ETM+). The data have been collected by two groups, one from the University of Arizona and the other from South Dakota State University. The test sites used by the University of Arizona group for this work are the Railroad Valley Playa, Lunar Lake Playa, and Roach Lake Playa all of which are in Nevada, Ivanpah Playa in California, and White Sands Missile Range, New Mexico. The test site for the South Dakota State group is a grass site in Brookings, SD. The gains derived from dates using these sites spanning the period from 1984 to 2003 are presented for TM and for the period of 1999 to 2003 for ETM+. Differences between the two groups are less than the combined uncertainties of the methods, and the data are thus treated as a single dataset. The results of these vicarious data indicate that there has been no degradation apparent in TM since 1995 and in ETM+ since launch. Agreement between the reflectance-based results and the preflight calibration of ETM+ is better than 4% in all bands, and the standard deviation of the average difference indicates a precision of the reflectance-based method on the order of 3%.     

Landsat-7 ETM+ on-orbit reflective-band radiometric stability and absolute calibration

Launched in April 1999, the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) instrument is in its sixth year of operation. The ETM+ instrument has been the most stable of any of the Landsat instruments. To date, the best onboard calibration source for the reflective bands has been the Full Aperture Solar Calibrator, a solar-diffuser-based system, which has indicated changes of between 1% to 2% per year in the ETM+ gain for bands 1-4 and 8 and less than 0.5%/year for bands 5 and 7. However, most of this change is believed to be caused by changes in the solar diffuser panel, as opposed to a change in the instrument's gain. This belief is based partially on vicarious calibrations and observations of "invariant sites", hyperarid sites of the Sahara and Arabia. Weighted average slopes determined from these datasets suggest changes of 0.0% to 0.4% per year for bands 1-4 and 8 and 0.4% to 0.5% per year for bands 5 and 7. Absolute calibration of the reflective bands of the ETM+ is consistent with vicarious observations and other sensors generally at the 5% level, though there appear to be some systematic differences.     

Landsat-7 ETM+ on-orbit reflective-band radiometric characterization

The Landsat-7 Enhanced Thematic Mapper Plus (ETM+) has been and continues to be radiometrically characterized using the Image Assessment System (IAS), a component of the Landsat-7 Ground System. Key radiometric properties analyzed include: overall, coherent, and impulse noise; bias stability; relative gain stability; and other artifacts. The overall instrument noise is characterized across the dynamic range of the instrument during solar diffuser deployments. Less than 1% per year increases are observed in signal-independent (dark) noise levels, while signal-dependent noise is stable with time. Several coherent noise sources exist in ETM+ data with scene-averaged magnitudes of up to 0.4 DN, and a noise component at 20 kHz whose magnitude varies across the scan and peaks at the image edges. Bit-flip noise does not exist on the ETM+. However, impulse noise due to charged particle hits on the detector array has been discovered. The instrument bias is measured every scan line using a shutter. Most bands show less than 0.1 DN variations in bias across the instrument lifetime. The panchromatic band is the exception, where the variation approaches 2 DN and is related primarily to temperature. The relative gains of the detectors, i.e., each detector's gain relative to the band average gain, have been stable to /spl plusmn/0.1% over the mission life. Two exceptions to this stability include band 2 detector 2, which dropped about 1% in gain about 3.5 years after launch and stabilized, and band 7 detector 5, which has changed several tenths of a percent several times since launch. Memory effect and scan-correlated shift, a hysteresis and a random change in bias between multiple states, respectively, both of which have been observed in previous Thematic Mapper sensors, have not been convincingly found in ETM+ data. Two artifacts, detector ringing and "oversaturation", affect a small amount of ETM+ data.     

Four years of Landsat-7 on-orbit geometric calibration and performance

Unlike its predecessors, Landsat-7 has undergone regular geometric and radiometric performance monitoring and calibration since launch in April 1999. This ongoing activity, which includes issuing quarterly updates to calibration parameters, has generated a wealth of geometric performance data over the four-year on-orbit period of operations. A suite of geometric characterization (measurement and evaluation procedures) and calibration (procedures to derive improved estimates of instrument parameters) methods are employed by the Landsat-7 Image Assessment System to maintain the geometric calibration and to track specific aspects of geometric performance. These include geodetic accuracy, band-to-band registration accuracy, and image-to-image registration accuracy. These characterization and calibration activities maintain image product geometric accuracy at a high level-by monitoring performance to determine when calibration is necessary, generating new calibration parameters, and verifying that new parameters achieve desired improvements in accuracy. Landsat-7 continues to meet and exceed all geometric accuracy requirements, although aging components have begun to affect performance.     

In-flight absolute calibration of the Landsat-5 TM on the test site Salar de Uyuni

In Brazil, the increase of the application of quantitative approaches in the natural resources studies using remote sensing technology has required knowledge about the radiometric conditions of remote sensors as the Thematic Mapper (TM) and the Enhanced TM Plus, for instance. The establishment of a correlation between radiometric data and biophysical and geophysical ones has become a frequent need in the Brazilian remote sensing community, and it has increased the demand of calibration coefficients in order to transform digital numbers to physical values like radiance and reflectance. Since the China-Brazil Environmental Remote Sensing Satellite became a reality, the necessity to perform calibration campaigns increased significantly. Following Price and other researcher's suggestions, an in-flight absolute calibration of the Landsat-5 data was carried out in the Salar de Uyuni, Bolivia. It was only possible to determine calibration coefficients for bands TM2, TM3, and TM4 due to the saturation of band TM1 and surface moisture conditions that impacted the TM5 and TM7. The methodology applied here seemed to be sufficient to determine valid calibration coefficients for orbital sensors.     

Automatic calibration of Hall sensor microsystems

In many applications, a Hall element is used for contact-less measurement such as linear and angular positions, electrical current, power and energy, etc. The Hall element fabricated by means of CMOS technology features mediocre characteristics [R.S. Popovic, Z. Randjelovic, D. Manic, Integrated Hall-Effect Magnetic Sensors, EMSA, Germany, 2000; R.S. Popovic, Hall Effect Devices, Adam Hilger, Bristol, Philadelphia, New York, 1991]. It gives a weak output signal of the order of a few mV. This signal is often corrupted by sensor offset, noise, temperature and aging drift. This paper deals with the state of the art and main techniques capable to detect and compensate these issues. Case studies using mentioned techniques are also summarized.     

传感器的在线静态标定研究

过程控制系统测量环节是至关重要的。以传感器在线测量数据静态标定原则为依据通过调用NI DAQmx运行库和MATLAB引擎或组件库实现传感器的慢速或快速在线静态标定及其他数据处理工作,经调试后,系统工作稳定,达到预期的设计目的。思路及设计程序对过程控制系统传感器的在线静态标定有一定的现实指导意义及使用价值。     

压力传感器的非线性校正和迟滞补偿

针对压力传感器在桥梁支座压剪机应用中的非线性和迟滞现象,对其进行了分析,并采用最小二乘法对传感器输出信号进行非线性校正,然后利用函数校正法进行迟滞补偿。实验表明,该方法可以有效实现压力传感器的非线性校正和迟滞补偿。     

Design and calibration of a microfabricated floating-elementshear-stress sensor

A microfabricated floating-element shear-stress sensor for measurements in turbulent boundary-layers is reported. Using surface micromachining of polyimide, a 500-μm×500-μm probe has been fabricated incorporating a differential-capacitor readout circuit. A model for the sensor response is described and is used for the design of an element to measure shear stresses of 1 Pa in air. The sensor is packaged for calibration in laminar flow, and electrical results obtained match the expected response     

蓝宝石晶体高温传感器的信号解调及标定

为了使用蓝宝石晶体高温传感器对工业烟气温度进行长期在线监测,设计了蓝宝石晶体高温传感器的解调系统,并对其进行了标定。对蓝宝石晶体高温传感器的白光偏振干涉测温原理进行了理论分析,并利用离散腔长变换(DGT)解调算法对光程差信息进行解调。在此基础上建立了一套以热电偶为参照的标定系统,使用S型高温热电偶采集温度数据,得到了光程差-温度样本。分别利用二次多项式拟合法与BP神经网络法对传感器的输出曲线进行了拟合与泛化,并进行了对比。实验结果表明:在800~1 300℃温度范围内,与二次多项式拟合方法相比,BP神经网络的拟合精度较高,拟合残差均值达到0.33℃;泛化能力强,多次泛化结果误差均值为0.56℃,均方误差为0.55℃。最终使用BP神经网络方法对传感器进行标定,使得传感解调系统满足了工业测高温的精度要求。     

A geometric performance assessment of the EO-1 advanced land imager

The Earth Observing 1 (EO-1) Advanced Land Imager (ALI) demonstrates technology applicable to a successor system to the Landsat Thematic Mapper series. A study of the geometric performance characteristics of the ALI was conducted under the auspices of the EO-1 Science Validation Team. This study evaluated ALI performance with respect to absolute pointing knowledge, focal plane sensor chip assembly alignment, and band-to-band registration for purposes of comparing this new technology to the heritage Landsat systems. On-orbit geometric calibration procedures were developed that allowed the generation of ALI geometrically corrected products that compare favorably with their Landsat 7 counterparts with respect to absolute geodetic accuracy, internal image geometry, and band registration.     

采用ALR算法对Landsat-7图像缺行修复的应用研究

美国陆地卫星Landsat-7上搭载的专题扫描仪（ETM＋）上的扫描行校正器（SLC,scan line corrector）在2003年5月31日发生故障,导致Landsat-7影像出现坏行,难以正常使用。为了使剩余的78％的数据能够被利用,美国航空航天局（NASA）组织专家研究解决这一问题的方案,我们与NASA密切配合,探索了5种修复方法。经过对这5种方法的尝试与试验,其中自适应局部回归（ALR）算法修复后的图像完整没有明显的修复边界,达到理想的效果。本文介绍了ALR算法的基本原理、流程,并将该算法分别应用在美国和北京的缺行图像修复中,取得良好的效果。     

星敏感器地面标定设备的设计

为了实现星敏感器的地面标定试验,设计一套视场大且星间角距模拟精度高的星敏感器地面标定系统,对标定系统的组成、光学系统设计和模拟仿真精度等进行研究。根据星敏感器的地面标定要求介绍系统组成,提出实现星间角距模拟精度优于20的方法;采用新型显示器件LCOS 作为星图显示器,通过像面拼接的方法扩大视场,并据此利用Zemax 软件设计光学系统。在原有测量方法的基础上,给出地面标定设备的精度评价方法。并提出一种能够提高星间角距模拟精度的星点修正方法。实验结果表明:星敏感器地面标定设备的星间角距模拟精度小于20,满足对星敏感器进行地面标定试验的要求。     

星敏感器支架的指向性标定及校正

为保证星敏感器支架安装后具有高精度的指向性,提出了一种星敏感器支架定量修研的技术方法,首先通过构造虚拟水平轴建立星敏感器支架坐标系,然后利用经纬仪交互测量和逐级求解方法获得星敏感器支架和相机任意两坐标轴的夹角关系。根据该结果进行了星敏感器支架实际坐标系与相机坐标系姿态变换矩阵的求解,利用星敏感器支架与相机坐标系的技术指标要求,进行了星敏感器支架理论坐标系与航天相机坐标系的姿态变换矩阵求解。然后以相机坐标系进行中间传递,获得了星敏感器支架实际坐标系到理论坐标系的姿态变换矩阵。根据该结果精确求解了星敏感器支架的修调量。通过试验研究表明利用该方法装调完成的星敏感器支架,经过两次修研迭代,其指向精度由最初的760″提升至10″以内。证明了该方法的有效性,同时星敏感器支架的指向性标定及校正也可指导其他有空间自由角度关系的两部件的精密装调。     

高温蓝宝石光纤温度传感器校准测试系统研究

为满足高温蓝宝石光纤温度传感器的标定和测试需要,分析了传感器的测量结构和标定原理,设计了一套基于氧乙炔高温综合测试平台和上位机测试应用软件的标定测试系统。试验结果表明,该系统能够实现传感器在多温度下的标定,并能模拟真实测温方式进行测试试验,具有较好的可靠性和稳定性。     

一种新型单片集成光谱传感器的波长定标方法

新型短波红外单片集成光谱传感器(MCSS)是光谱传感物联网的核心感知部件.提出了一种MCSS的波长定标方法, 根据相对光谱响应度和波长分配原则把相邻像素组成一个定标通道.分别采用MCSS和两款商用光谱仪测量标准物质的光谱.实验结果表明, 平均定标偏差为1.8 nm, 与一款具有相似FWHM和取样间隔的商用光谱仪接近, 能够满足实际应用的需要     

基于ZIGBEE的压力传感器标定系统的研究

针对随钻测量系统中压力传感器需要标定的问题,本文采用C8051F060作为微处理器,配合ZIGBEE无线传榆模块及标准自动加压台,设计了一种对未知压力传感器进行智能标定的系统,经过室内试验和现场试验验证,这种压力标定系统具有易操作、稳定性好、精度高等特点,可以满足压力传感器标定要求。     

Landsat ETM+ and SAR image fusion based on generalized intensity Modulation

This work presents a novel multisensor image fusion algorithm, which extends panchrmomatic sharpening of multispectral (MS) data through intensity modulation to the integration of MS and synthetic aperture radar (SAR) imagery. The method relies on SAR texture, extracted by ratioing the despeckled SAR image to its low-pass approximation. SAR texture is used to modulate the generalized intensity (GI) of the MS image, which is given by a linear transform extending intensity-hue-saturation transform to an arbitrary number of bands. Before modulation, the GI is enhanced by injection of high-pass details extracted from the available panchrmomatic image by means of the "a/spl grave/-trous" wavelet decomposition. The texture-modulated panchrmomatic-sharpened GI replaces the GI calculated from the resampled original MS data. Then, the inverse transform is applied to obtain the fusion product. Experimental results are presented on Landsat-7 Enhanced Thematic Mapper Plus and European Remote Sensing 2 satellite images of an urban area. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, which can be usefully applied for both visual analysis and classification purposes.     

Automatic Spectral Rule-Based Preliminary Mapping of Calibrated Landsat TM and ETM+ Images

Based on purely spectral-domain prior knowledge taken from the remote sensing (RS) literature, an original spectral (fuzzy) rule-based per-pixel classifier is proposed. Requiring no training and supervision to run, the proposed spectral rule-based system is suitable for the preliminary classification (primal sketch, in the Marr sense) of Landsat-5 Thematic Mapper and Landsat-7 Enhanced Thematic Mapper Plus images calibrated into planetary reflectance (albedo) and at-satellite temperature. The classification system consists of a modular hierarchical top-down processing structure, which is adaptive to image statistics, computationally efficient, and easy to modify, augment, or scale to other sensors' spectral properties, like those of the Advanced Spaceborne Thermal Emission and Reflection Radiometer and of the Satellite Pour l'Observation de la Terre (SPOT-4 and -5). As output, the proposed system detects a set of meaningful and reliable fuzzy spectral layers (strata) consistent (in terms of one-to-one or many-to-one relationships) with land cover classes found in levels I and II of the U.S. Geological Survey classification scheme. Although kernel spectral categories (e.g., strong vegetation) are detected without requiring any reference sample, their symbolic meaning is intermediate between those (low) of clusters and segments and those (high) of land cover classes (e.g., forest). This means that the application domain of the kernel spectral strata is by no means alternative to RS data clustering, image segmentation, and land cover classification. Rather, prior knowledge-based kernel spectral categories are naturally suitable for driving stratified application-specific classification, clustering, or segmentation of RS imagery that could involve training and supervision. The efficacy and robustness of the proposed rule-based system are tested in two operational RS image classification problems.