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.     

Landsat-4/5 Band 6 relative radiometry

Relative radiometric responses for the thematic mapper (TM) band 6 data from Landsat-4 and Landsat-5 were analyzed, and an algorithm has been developed that significantly reduces the striping in Band 6 images due to detector mismatch. The TM internal calibration system as originally designed includes a DC restore circuit, which acts as a feedback system designed to keep detector bias at a constant value. There is a strong indication that the DC restore circuitry implemented in Band 6 does not function as it had been designed to. It operates as designed only during a portion of the calibration interval and not at all during acquisition of scene data. This renders the data acquired during the calibration shutter interval period virtually useless for correction of the individual responses of the four detectors in Band 6. It was observed and statistically quantified that the relative response of each of the detectors to the band average is stable over the dynamic range and throughout the lifetime of the instrument. This allows an alternate approach to relative radiometric correction of TM Band 6 images     

An Algorithm for Computing the Number of Distinct Spectral Vectors in Thematic Mapper Data

A computationally efficient method was developed to compute the number of distinct spectral vectors and their frequency of occurrence in Landsat-4 Thematic Mapper (TM) data. The algorithm first partitions the image into spectrally disjoint subsets and then computes the frequency distribution of distinct spectral vectors within each subset from a multidimensional histogram. The overall frequency distribution is tabulated by accumulating the results from each subset. The number of distinct spectral vectors could be used as a measure of potential storage compaction of alternate data representations for data compression, or as a measure of information content in the comparison of spectral band combinations and/or spatial resolutions for an image. Results from processing three 512 X 512 pixel Landsat-4 TM images and one Landsat-4 Multispectral Scanner (MSS) image are presented as examples. An algorithm for computing the frequency distribution of distinct spectral vectors in MSS data is given in the Appendix.     

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%.     

Characterization of LANDSAT-4 MSS And TM Digital Image Data

Engineering analyses conducted to assess image data quality are described and results are presented for the Landsat-4 Multispectral Scanner (MSS) and Thematic Mapper (TM). Also, coincident data from the two sensors are compared. Macroscopic studies addressed trends and characteristics of full frames of data, while ?microscopic? studies assessed differences between individual detector responses. Raw data, radiometrically corrected data, and fully corrected data were analyzed, as well as special calibration data. The Landsat-4 MSS was found to produce data of high quality, comparable to previous Landsats, except for a low-level coherent noise effect which is unique to the current sensor. Radiometric relationships between Landsat-2 and -3 MSS's and the Landsat-4 MSS were established through empirical analysis of simultaneously acquired data. The TM was found to produce image data of very good spatial resolution and overall good radiometric data quality, showing improvements over MSS. Radiometric equalization of detector responses was found to be close to the theoretical limit of quantization error, except for two relatively low-amplitude artifacts. One is a difference in response that depends on the direction of mirror scan. This produces scan-angle effects superimposed on scene-related effects. The second is a tendency for level shifts to occur between mirror scans at random times but with correlations between detector responses. Two forms or patterns of level shift were identified, corresponding to four system noise states. Preliminary correction models and/or procedures have been developed and recommended for further evaluation.     

Landsat sensor performance: history and current status

The current Thematic Mapper (TM) class of Landsat sensors began with Landsat-4, which was launched in 1982. This series continued with the nearly identical sensor on Landsat-5, launched in 1984. The final sensor in the series was the Landsat-7 Enhanced Thematic Mapper Plus (ETM+), which was carried into orbit in 1999. Varying degrees of effort have been devoted to the characterization of these instruments and data over the past 22 years. Extensive short-lived efforts early in the history, very limited efforts in the middle years, and now a systematic program for continuing characterization of all three systems are apparent. Currently, both the Landsat-5 TM and the Landsat-7 ETM+ are operational and providing data. Despite 20+ years of operation, the TM on Landsat-5 is fully functional, although downlinks for the data are limited. Landsat-7 ETM+ experienced a failure of its Scan Line Corrector mechanism in May 2003. Although there are gaps in the data coverage, the data remain of equivalent quality to prefailure data. Data products have been developed to fill these gaps using other ETM+ scenes.     

In-Flight Absolute Radiometric Calibration of the Thematic Mapper

Ground spectral reflectance and atmospheric spectral optical depth measurements made at White Sands, New Mexico on January 3, 1983, were used with an atmospheric radiative transfer program to determine the spectral radiance at the entrance pupil of the Landsat-4 Thematic Mapper (TM). A comparison with the output digital counts of the TM, when imaging the measured ground area, provided an absolute calibration for five detectors in TM bands 2, 3, and 4. By reference to an adjacent, larger uniform area, the calibration was extended to all 16 detectors in each of the three bands. Pre-flight calibration results agreed with these inflight measurements to 6.6, 2.4, and 12.9 percent in bands 2, 3, and 4, respectively.     

Cross calibration of the Landsat-7 ETM+ and EO-1 ALI sensor

As part of the Earth Observer 1 (EO-1) Mission, the Advanced Land Imager (ALI) demonstrates a potential technological direction for Landsat Data Continuity Missions. To evaluate ALI's capabilities in this role, a cross-calibration methodology has been developed using image pairs from the Landsat-7 (L7) Enhanced Thematic Mapper Plus (ETM+) and EO-1 (ALI) to verify the radiometric calibration of ALI with respect to the well-calibrated L7 ETM+ sensor. Results have been obtained using two different approaches. The first approach involves calibration of nearly simultaneous surface observations based on image statistics from areas observed simultaneously by the two sensors. The second approach uses vicarious calibration techniques to compare the predicted top-of-atmosphere radiance derived from ground reference data collected during the overpass to the measured radiance obtained from the sensor. The results indicate that the relative sensor chip assemblies gains agree with the ETM+ visible and near-infrared bands to within 2% and the shortwave infrared bands to within 4%.     

Revised Radiometric Calibration Technique for LANDSAT-4 Thematic Mapper Data

A technique for the radiometric correction of Landsat-4 Thematic Mapper (TM) data was proposed by the Canada Centre for Remote Sensing (CCRS) in 1982, and two reports defining the method and discussing preliminary results were presented by CCRS at the Landsat-4 Scientific Characterization Early Results Symposium [1] and [2]. Subsequent detailed observations of raw image data, raw radiometric calibration data, and background measurements extracted from the raw data stream on High Density Tape have highlighted in the proposed method, major shortcomings, which if left uncorrected, can cause severe radiometric striping in the output product. Observations presented here show that there are random fluctuations in the background level for spectral band 1 of magnitudes ranging from 2 to 3.5 digital numbers (DN), depending on detector number. Similar variability is observed in all the other reflective bands, but with smaller magnitude in the range 0.5 to 2.5 DN. More significantly, it is shown how measurements of the dc background level can be correlated with variations in both image data background and calibration samples. The effect on both raw data and on data corrected using the earlier proposed technique is explained, and the correction required for these factors as a function of individual scan line number for each detector is described. It is shown how the revised technique, which includes corrections for a line-dependent offset in addition to the scene-dependent gain and offset, can be incorporated into an operational environment.     

Spectral Variability of LANDSAT-4 Thematic Mapper And Multispectral Scanner Data for Selected Crop And Forest Cover Types

The performance of both the Landsat-4 TM and MSS sensors is evaluated through the analysis of image and digital data simultaneously acquired over agricultural and forestry study sites in California. Spectral statistics extracted for selected cover types include band means, variances, coefficients of variation, range values, skewness, kurtosis, and covariance and correlation matrices. Spectral characteristics are evaluated through analysis of these statistics and interpretation of image products. Image products are used to visually represent significant spectral variations between the TM bands. Significant results include: 1) the overall spectral, spatial, and radiometric quality of the TM data are excellent; 2) discrimination of crop types on single-date image data is significantly improved by the addition of the first short-wave infrared band (TM5); 3) the thermal infrared data (TM6) allows the discrimination of agricultural and forestry cover types based on differences in their radiant temperature responses; and 4) the higher TM spatial resolution (28.5 m versus 57 m) provides the ability to discriminate small agricultural fields and boundaries, forest stand boundary conditions, road and stream networks in rough terrain, and small clearings resulting from various forest management practices.     

Landsat-5 TM reflective-band absolute radiometric calibration

The Landsat-5 Thematic Mapper (TM) sensor provides the longest running continuous dataset of moderate spatial resolution remote sensing imagery, dating back to its launch in March 1984. Historically, the radiometric calibration procedure for this imagery used the instrument's response to the Internal Calibrator (IC) on a scene-by-scene basis to determine the gain and offset of each detector. Due to observed degradations in the IC, a new procedure was implemented for U.S.-processed data in May 2003. This new calibration procedure is based on a lifetime radiometric calibration model for the instrument's reflective bands (1-5 and 7) and is derived, in part, from the IC response without the related degradation effects and is tied to the cross calibration with the Landsat-7 Enhanced Thematic Mapper Plus. Reflective-band absolute radiometric accuracy of the instrument tends to be on the order of 7% to 10%, based on a variety of calibration methods.     

Comparison of the Information Content of Data from the LANDSAT-4 Thematic Mapper And the Multispectral Scanner

Simultaneous data acquisition by the Landsat-4 Thematic Mapper (TM) and the Multispectral Scanner (MSS) permits the comparison of the two types of image data with respect to engineering performance and data applications. In this paper the ?information? contained in data from the visible and near-IR channels is evaluated for five agricultural scenes, leading to the conclusion that the TM provides a significant advance in information gathering capability as expressed in terms of bits per pixel or bits per unit area. The six reflective channels of the TM acquire 18 bits of information per pixel out of a possible 6 × (8 bits) = 48 bits, while the four MSS channels acquire 10 bits of information per pixel out of a possible 4 × (7 bits) = 28 bits. Thus the TM and MSS are equally efficient in gathering information (18/48 ? 10/28), contrary to the expected tendency toward lower efficiency as spatial resolution is improved and spectral channels are added to an observing system. The result is attributed to: 1) Superior selection of spectral channels in the TM; 2) Higher precision of the TM data, i.e., lower system noise, and 3) the advantage of higher spatial resolution, even in agricultural areas where fields are larger than the MSS pixel size. Because the MSS lacks a thermal IR channel, the 10-12-micrometer data of the TM at 120-m resolution are analyzed theoretically using an energy balance approach.     

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.     

Perceptual-based image fusion for hyperspectral data

Three hierarchical multiresolution image fusion techniques are implemented and tested using image data from the Airborne Visual/Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The methods presented focus on combining multiple images from the AVIRIS sensor into a smaller subset of images white maintaining the visual information necessary for human analysis. Two of the techniques are published algorithms that were originally designed to combine images from multiple sensors, but are shown to work well on multiple images from the same sensor. The third method presented was developed specifically to fuse hyperspectral images for visual analysis. This new method uses the spatial frequency response (contrast sensitivity) of the human visual system to determine which features in the input images need to be preserved in the composite image(s) thus ensuring the composite image maintains the visually relevant features from each input image. The image fusion algorithms are analyzed using test images with known image characteristics and image data from the AVIRIS hyperspectral sensor. After analyzing the signal-to-noise ratios and visual aesthetics of the fused images, contrast sensitivity based fusion is shown to provide excellent fusion results and, in every case, outperformed the other two methods     

Validation and refinement of hyperspectral/multispectral atmospheric compensation using shadowband radiometers

First-principles atmospheric compensation of Earth-viewing spectral imagery requires atmospheric property information derived from the image itself or measured independently. A field experiment was conducted in May, 2003 at Davis, CA to investigate the consistency of atmospheric properties and surface reflectances derived from simultaneous ground-, aircraft- and satellite-based spectral measurements. The experiment involved the simultaneous collection of HyMap hyperspectral and Landsat-7 multispectral imagery, in situ reflectance spectra of calibration surfaces, and sun and sky radiances from ultraviolet and visible multifilter rotating shadowband radiometers (MFRSRs). The data were analyzed using several different radiation transport and atmospheric compensation algorithms. Reasonable self-consistency was found between aerosol property retrievals from the radiometers and from dark pixels of the imagery, and, when using the most accurate algorithm, there was excellent agreement between the retrieved surface spectra and the ground truth measurements.     

Cartographic Accuracy of LANDSAT-4 MSS And TM Image Data

Investigations of the cartographic quality of Landsat-4 MSS and TM image data in CCT-p formats have produced rectification accuracies (rmsexy values) of ± 2/3 to ± 1 data pixel for both whole and subscene areas using polynomials of the first through third degree. In order to achieve these accuracies with MSS data, 15 or more Ground Control Points (GCP's) are required, whereas with the TM data sets as few as 5-10 GCPs will suffice. Factors which limit the cartographic rectification accuracies of the Landsat-4 data include: 1) spatial resolution of the data; 2) map and digitizing errors; and 3) terrain relief. Of these factors, data resolution is the most significant, limiting the location of GCP's to about ± 0.5 pixel. Horizontal displacements due to terrain relief can be minimized by selecting GCP's at or near midrange elevations. Overall, the representative rmsexy values of ±25 and ±55 m for TM and MSS data sets are within U.S. National Map Accuracy Standards for cartographic products of 1:100 000 and 1:200 000 scale, respectively.     

Multisensor approach to automated classification of sea ice image data

A multisensor data fusion algorithm based on a multilayer neural network is presented for sea ice classification in the winter period. The algorithm uses European Remote Sensing (ERS), RADARSAT synthetic aperture radar (SAR), and low-resolution television camera images and image texture features. Based on a set of in situ observations made at the Kara Sea, a neural network is trained, and its structure is optimized using a pruning method. The performance of the algorithm with different combinations of input features (sensors) is assessed and compared with the performance of a linear discriminant analysis (LDA)-based algorithm. We show that for both algorithms a substantial improvement can be gained by fusion of the three different types of data (91.2% for the neural network) as compared with single-source ERS (66.0%) and RADARSAT (70.7%) SAR image classification. Incorporation of texture increases classification accuracy. This positive effect of texture becomes weaker with increasing number of sensors (from 8.4 to 6.4 percent points for the use of two and three sensors, respectively). In view of the short training time and smaller number of adjustable parameters, this result suggests that semiparametric classification methods can be considered as a good alternative to the neural networks and traditional parametric statistical classifiers applied for the sea ice classification.     

Vicarious calibration experiment in support of the Multi-angle Imaging SpectroRadiometer

On June 11, 2000, the first vicarious calibration experiment in support of the Multi-angle Imaging SpectroRadiometer (MISR) was conducted. The purpose of this experiment was to acquire in situ measurements of surface and atmospheric conditions over a bright, uniform area. These data were then used to compute top-of-atmosphere (TOA) radiances, which were correlated with the camera digital number output, to determine the in-flight radiometric response of the on-orbit sensor. The Lunar Lake Playa, Nevada, was the primary target instrumented by the Jet Propulsion Laboratory for this experiment. The airborne MISR simulator (AirMISR) on board a NASA ER-2 acquired simultaneous observations over Lunar Lake. The in situ estimations of top-of-atmosphere radiances and AirMISR measurements at a 20-km altitude were in good agreement with each other and differed by 9% from MISR measurements. The difference has been corrected by adjusting the gain coefficients used in MISR standard product generation. Data acquired simultaneously by other sensors, such as Landsat, the Terra Moderate-Resolution Imaging SpectroRadiometer (MODIS), and the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS), were used to validate this correction. Because of this experiment, MISR radiances are 9% higher than the values based on the on-board calibration. Semiannual field campaigns are planned for the future in order to detect any systematic trends in sensor calibration.     

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.     

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.