An Analysis of LANDSAT-4 Thematic Mapper Geometric Properties

Landsat-4 Thematic Mapper data of Washington, DC, Harrisburg, PA, and Salton Sea, CA were analyzed to determine geometric integrity and conformity of the data to known Earth surface geometry. Several tests were performed. Intraband correlation and interband registration were investigated. No problems were observed in the intraband analysis, and aside from indications of slight misregistration between bands of the primary versus bands of the secondary focal planes, interband registration was well within the specified tolerances. A substantial number of ground control points were found and used to check the images' conformity to the Space Oblique Mercator (SOM) projection of their respective areas. The means of the residual offsets, which included nonprocessing related measurement errors, were close to the one pixel level in the two scenes examined. The Harrisburg scene residual mean was 28.38 m (0.95 pixels) with a standard deviation of 19.82 m (0.66 pixels), while the mean and standard deviation for the Salton Sea scene were 40.46 (1.35 pixels) and 30.57 m (1.02 pixels), respectively. Overall, the data were judged to be a high geometric quality with errors close to those targeted by the TM sensor design specifications.     

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.     

High-accuracy band to band registration method for multi-spectral images of HJ-1A/B

Band-to-band registration accuracy is an important parameter of multispectral data. A novel band-to-band registration approach with high precision is proposed for the multi-spectral images of HJ-1A/B. Firstly, the main causes resulted in misregistration are analyzed, and a high-order polynomial model is proposed. Secondly, a phase fringe filtering technique is employed to Phase Correlation Method based on Singular Value Decomposition (SVD-PCM) for reducing the noise in phase difference matrix. Then, experiments are carried out to build nonlinear registration models, and images of green band and red band are aligned to blue band with an accuracy of 0.1 pixels, while near infrared band with an accuracy of 0.2 pixels.     

The impact of misregistration on change detection

The impact of misregistration on the detection of changes in land cover has been evaluated using spatially degraded Landsat MSS images, focusing on simulated images of the normalized difference vegetation index (NDVI). Single-date images from seven areas were misregistered against themselves, and the statistical properties of the differences were analyzed. In the absence of any actual changes to the land surface, the consequences of misregistration were very marked even for subpixel misregistrations. Pairs of images from different time periods were then misregistered. For four densely covered areas, an error equivalent to greater than 50% of the actual differences in the NDVI, as measured by the semivariance, was induced by a misregistration of only one pixel. To achieve an error of only 10%, registration accuracies of 0.2 pixels or less are required. For three more sparsely vegetated areas with semiarid climates, a registration accuracy of between 0.5 and 1.0 pixel was sufficient to achieve an error of 10% or less. The results indicate that high levels of registration are needed for reliable monitoring of global change     

LANDSAT-4 MSS And Thematic Mapper Data Quality And Information Content Analysis

Landsat-4 Thematic Mapper and Multispectral Scanner data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic Mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and numerous supervised classifiers on data from Iowa and Illinois. A detailed spectral class analysis (multispectral classification) was carried out on data from the Des Moines, Iowa area to compare the information content of the MSS and TM for a large number of scene classes.     

Evaluation of Corn/Soybeans Separability Using Thematic Mapper And Thematic Mapper Simulator Data

Multitemporal Thematic Mapper, Thematic Mapper Simulator, and detailed ground truth data were collected for a 9-by 1-km sample segment in Webster County, Iowa, in the summer of 1982. Three dates were acquired each with Thematic Mapper Simulator (June 7, June 23, and July 31) and Thematic Mapper (August 2, September 3, and October 21). The Thematic Mapper Simulator data were converted to equivalent TM count values using TM and TMS calibration data and model based estimates of atmospheric effects. The July 31, TMS image was compared to the August 2, TM image to verify the conversion process. A quantitative measure of proportion estimation variance (Fisher information) was used to evaluate the corn/soybeans separability for each TM band as a function of time during the growing season. The additional bands in the middle infrared allowed corn and soybeans to be separated much earlier than was possible with the visible and near-infrared bands alone. Using the TM and TMS data, temporal profiles of the TM principal components were developed. The greenness and brightness exhibited behavior similar to MSS greenness and brightness for corn and soybeans.     

基于列相关的热红外高光谱遥感图像非均匀性校正

由于探测单元之间响应不一致、电子增益和偏置发生变化、焦平面污染和损伤等因素,推扫式热红外成像光谱仪获取的图像常常表现为图像列之间不均匀,条带噪声严重,影响了热红外高光谱遥感图像的后续处理和应用。结合推扫式成像光谱仪非均匀性的来源和成因,以相邻地物的相关性为理论基础,提出了适用于热红外高光谱遥感图像的非均匀性校正方法。该方法的步骤是,首先逐波段对原始热红外高光谱遥感图像进行标准矩匹配校正,得到标准矩匹配校正图像;然后,以标准矩匹配校正图像为基础,选择相邻两列像元中相同的地物像元;最后,用两列中相同的地物像元,通过线性回归得到后一列的校正系数,并对其进行校正,顺次遍历一个波段的所有列,完成一个波段图像的非均匀性校正。按照此过程,遍历一幅热红外高光谱遥感图像的所有波段,完成一幅热红外高光谱遥感图像的非均匀性校正。将该方法应用于推扫式热红外光谱成像仪实际获取图像的非均匀性校正中。结果表明,相比矩匹配方法,在保证非均匀性校正效果的情况下,本文方法的各列均值和标准差更符合实际情况。     

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.     

Atmospheric effects on Landsat TM thermal IR data

The components of atmospherically attenuated target radiance and the path radiance emitted by the atmosphere are calculated to explain the fact that for certain meteorological conditions, properly calibrated thermal IR (infrared) data gathered from aircraft and spacecraft altitudes provide accurate temperature measurements of surface water bodies even when atmospheric corrections are not applied. Results show that although the 8-14-μm atmospheric window is far from being transparent (<50% transmission), the amount of atmospheric path radiance may be equal to the amount of attenuated target radiance. Errors in remotely sensed temperatures introduced by atmospheric effects are shown to be smaller than or of the same order of magnitude as those errors caused by sensor noise and the effects of applying a cubic convolution during the process of converting the TM (Thematic Mapper) data from A-tape to geometrically corrected P-tape data format     

An Overview of Progress in the Design And Implementation of Landsat-D Systems

Landsat-D will be launched in late 1981 or early 1982 into a Sun-synchronous orbit near 700 km. Landsat-D systems and the principal observing instrument, the Thematic Mapper, are being designed and implemented to provide a significantly improved Earth-resources monitoring capability. The Thematic Mapper will have seven spectral bands (0.45-0.52, 0.52-0.60, 0.63-0.69, 0.76-0.90, 1.55-1.75, 2.08-2.35, and 10.5-12.5 ?m), with an instantaneous field of view at nadir of 30 m except for the thermal band (120 m). The data from the Thematic Mapper and other Landsat-D flight segment systems will be relayed to the Landsat-D ground data processing system using a direct readout capability or the Tracking and Data Relay Satellite System and communications satellites. The ground systems will process the data as it arrives at rates up to 100 Mbit/s and a total volume of 2.6 × 1011 bit/day into standard digital and photographic products within 48 hours of data acquisition. This includes 200 Multispectral Scanner Subsystem and 100 Thematic Mapper scenes per day. The Thematic Mapper increased spatial, spectral, and radiometric resolution should be of primary benefit in agricultural and vegetation surveys, but substantial improvements in resource and land cover observations for geology, land use, and water resources applications are also to be anticipated.     

LASIS影像波段配准

针对大孔径静态干涉成像光谱仪(Large Aperture Static Interference Imaging Spectrometer,LASIS)各波段共视场扫描成像的特点,提出了基于在轨几何内检校的虚拟重成像方法进行波段高精度配准.此方法充分考虑姿轨的变化和镜头畸变等导致高光谱波段影像失配的几何因素,在内方位元素检校的基础上,对高光谱影像进行虚拟重成像,实现了对误差源的建模以及波段间相对误差的消除.利用遥感十四号LASIS在不同区域数据进行内检校和虚拟重成像实验,结果表明,进行LASIS数据的处理能够得到优于0.16像素的波段配准精度.     

Land-Use Mapping Using Edge Density Texture Measures on Thematic Mapper Simulator Data

Texture analysis was performed as part of an investigation of the information content of Landsat Thematic Mapper (TM) imagery. High-altitude aircraft scanner imagery from the Airborne Thematic Mapper (ATM) instrument was acquired over central California and used to simulate TM data. Edge density texture images were constructed by computation of proportions of edge pixels in a 31×31 moving window on a near-infrared ATM band. A training technique was employed to select computational parameters to maximize the difference between edge density measurements in urban and in rural areas. The results of classification of the texture images showed that urban and rural areas could be distinguished with texture alone, indicating that inclusion of texture in automated classification procedures could significantly improve their accuracy.     

Georegistration of Landsat data via robust matching of multiresolution features

The goal of the project described in this paper is to build a prototype of an operational system, which will provide registration within subpixel accuracy of multitemporal Landsat data, acquired by either Landsat-5 or Landsat-7 Thematic Mapper instruments. Integrated within an automated mass processing system for Landsat data, the input to our registration system consists of scenes that have been geometrically and radiometrically corrected, as well as preprocessed for detection of clouds and cloud shadows. Such preprocessed scenes are then georegistered relative to a database of Landsat chips. This paper describes the entire registration process, including the use of landmark chips, feature extraction performed by an overcomplete wavelet representation, and feature matching using statistically robust techniques. Knowing the approximate longitudes and latitudes or the UTM coordinates of the four corners of each incoming scene, a subset of the chips that represent landmarks included in the scene are selected to perform the registration. For each of these selected landmark chips, a corresponding window is extracted from the incoming scene, and each chip-window pair is registered using a robust wavelet feature-matching methodology. Based on the transformations from the chip-window pairs, a global transformation is then computed for the entire scene using a variant of a robust least median of squares estimator. Empirical results of this registration process, which provided subpixel accuracy for several multitemporal scenes from different study areas, are presented and discussed.     

MODIS On-Orbit Spatial Characterization Using Ground Targets

The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor is currently being operated on both Terra and Aqua spacecrafts. MODIS uses 36 bands arranged in four focal plane assemblies (FPAs)—visible, near infrared, short- and middle-wavelength infrared, and long-wavelength infrared. Misregistrations between spectral bands and FPAs and changes of spatial characterization on-orbit could impact the quality of science data products generated with multiple bands located on different FPAs. In this paper, an approach is presented to compute the MODIS band-to-band registration (BBR) using ground measurements. A special ground scene with unique features is selected to calculate the spatial registration along-scan and along-track. The monthly and yearly spatial deviations are calculated for the bands of both Terra and Aqua MODIS except for some ocean bands, cloud bands, and the Aqua MODIS band 6. The comparison with results derived from the spectroradiometric calibration assembly, a device operated on-orbit to track the BBR shift between any two of the spectral bands, generally shows good agreement. The measured differences between these two approaches are typically less than 100 m in the scan direction and 200 m in the track direction. This approach can provide more frequent characterization of the MODIS BBR and is extremely useful for other sensors that do not have an onboard spatial characterization device.      

Correction of Attitude Fluctuation of Terra Spacecraft Using ASTER/SWIR Imagery With Parallax Observation

Accurate attitude estimation of spacecrafts is the main requirement to provide good geometric performance of remote-sensing imagery. The Advanced Spaceborne Thermal Emission and Reflection Radiometer/short-wave-infrared subsystem has six linear-array sensors arranged in parallel, and each line scans the same ground target with a time interval of 356.238 ms between neighboring bands. The registration performance between bands becomes worse when attitude fluctuation occurs during a time lag between observations. Since the time resolution of the line scan is higher than that of the attitude information provided from the satellite, attitude data are estimated with a high frequency. We succeeded in correcting the image-registration error using the revised attitude information. As a result, the image distortion of 0.2 pixels caused by spacecraft-attitude jitter is reduced to less than 0.08 pixels, showing that band-to-band registration errors of a sensor with parallax observation are available to improve the image distortion caused by attitude fluctuation.     

Spectral linear mixing model in low spatial resolution image data

Different ways to estimate the spectral reflectance for the component classes in a mixture problem have been proposed in the literature (pure pixels, spectral library, field measurements). One of the most common approaches consists in the use of pure pixels, i.e., pixels that are covered by a single component class. This approach presents the advantage of allowing the extraction of the components' reflectance directly from the image data. This approach, however, is generally not feasible in the case of low spatial resolution image data, due to the large ground area covered by a single pixel. In this paper, a methodology aiming to overcome this limitation is proposed. The proposed approach makes use of the spectral linear mixing model. In the proposed methodology, the components' proportions in image data are estimated using a medium spatial resolution image as auxiliary data. The linear mixing model is then solved for the unknown spectral reflectances. Experiments are presented, using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Enhanced Thematic Mapper Plus, as low and medium spatial resolution image data, respectively, acquired on the same date over the Tapajos study site, Brazilian Amazon. Three component classes or endmembers are present in the scene covered by the experiment, namely vegetation, exposed soil, and shade. The components' spectral reflectance for the Terra MODIS spectral bands were then estimated by applying the proposed methodology. The reliability of these estimates is appraised by analyzing scatter diagrams produced by the Terra MODIS spectral bands and also by comparing the fraction images produced using both image datasets. This methodology appears appropriate for up-scaling information for regional and global studies.     

Terra MODIS on-orbit spatial characterization and performance

The Moderate Resolution Imaging Spectroradiometer (MODIS) Proto-Flight Model, onboard the National Aeronautics and Space Administration's Earth Observing System Terra spacecraft, has been in operation for over four years. It has 36 spectral bands and a total of 490 detectors located on four focal plane assemblies (FPAs). MODIS makes observations at three spatial resolutions (nadir): 0.25 km (bands 1-2), 0.5 km (bands 3-7), and 1 km (bands 8-36). The instrument's spatial characterization was measured prelaunch using an integration and alignment collimator. Parameters measured included the detectors' instantaneous field-of-view (IFOV), band-to-band registration (BBR), and line spread function in both the along-scan and along-track directions. On-orbit, the spatial characterization is periodically measured using the onboard spectro-radiometric calibration assembly (SRCA). This paper describes the SRCA BBR algorithms, characterization methodologies, and on-orbit results. A Fourier approach used to calculate the along-track BBR is also described. This approach enhances the algorithm's robustness in comparison with the conventional centroid approach. On-orbit results show that the Terra MODIS focal planes shifted slightly during launch and initial on-orbit operation. Since then they have been very stable. The BBR is within 0.16 km (nadir IFOV) in the along-scan direction and 0.23 km (nadir IFOV) in the along-track direction among all bands. The small but noticeable periodic variation of the on-orbit BBR can be attributed to the annual cycling of instrument temperature due to Sun-Earth distance variation. The visible FPA position has the largest temperature dependence among all FPAs, 17 m/K along-scan and 0.6 m/K along-track.     

Analysis And Processing of LANDSAT-4 Sensor Data Using Advanced Image Processing Techniques And Technologies

Techniques have been developed or improved to calibrate, repair, geometrically correct, and extract information from Landsat-4 satellite data. Statistical techniques to correct data radiometry have been evaluated and have minimized striping and banding. It is shown that unless these statistical techniques are used, striping will result even with perfect calibration parameters. Algorithms have been developed to replace data from failed detectors and to reduce coherent noise. The Landsat-4 data have been geometrically corrected to conform to a 1:100 000 map reference to an accuracy of about 41 m. The data were then recorded onto film, and image products produced that can serve as low-cost accurate map products. To decrease the dimensionality of the Landsat-4 data, principal component transformation of the data to four significant new bands was performed, and the results compared with latest available land use maps. The transformation is useful for land use analysis and in delineating vegetation anomalies which appear to reflect areas underlain by altered serpentinite. A range of image processing systems have been used to process the satellite data, including general purpose, special purpose, and personal computers. These systems are described, along with their processing performance. Index Terms-Digital Image Processing, Thematic Mapper, Multispectral Scanner, Calibration, Geometric Correction, Mapping, Digital Terrain, Enhancement, Noise Removal, Personal Computer, Entropy, Principal Components, Banding, Striping, Information Extraction, Geology, Land Use.     

MOS and SEASAT image geometric corrections

Results of studies to generate precise orthoimages from MOS-MESSR data in the visible spectral range and SEASAT-SAR data in the microwave range are reported. The raw MOS-MESSR image has four spectral bands, with an interband misregistration of three to four pixels. A methodology for orthoimage generation directly from each band of the raw image is described. For thematic applications with SEASAT images, most users have access only to slant range or ground range image products, which are often not georeferenced or geocoded with a standardized pixel spacing. The same methodology for creating orthoimages has been adapted for spaceborne SAR images, and tested with a ground range SEASAT image. The analysis of the sensor and satellite motion geometries and the use of a photogrammetric approach allows a rigorous mathematical model for the geometric correction and the rectification of the raw images to be derived. The final accuracy of the geometric corrections is about 25 m for both data types, using only six ground control points     

A Spectral-Knowledge-Based Approach for Urban Land-Cover Discrmination

A prototype expert system was developed to demonstrate the feasibility of classifying multispectral remotely sensed data on the basis of spectral knowledge. The spectral expert was developed and tested with Thematic Mapper Simulator (TMS) data having eight spectral bands and a spatial resolution of 5 m. A knowledge base was devloped that describes the target categories in terms of characteristic spectral relationships. The knowledge base was developed under the following assumptions: the data are calibrated to ground reflectance, the area is well illuminated, the pixels are dominated by a single category, and the target categories can be recognized without the use of spatial knowledge. Classification decisions are made on the basis of convergent evidence as derived from applying the spectral rules to a multiple spatial resolution representation of the image. The spectral expert achieved an accuracy of 80-percent correct or higher in recognizing 11 spectral categories in TMS data for the Washington, DC, area. Classification performance can be expected to decrease for data that do not satisfy the above assumptions as illustrated by the 63-percent accuracy for 30-m resolution Thematic Mapper data.