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Dive into the research topics where Dennis L. Helder is active.

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Featured researches published by Dennis L. Helder.


Remote Sensing of Environment | 2001

Effects of Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper plus radiometric and geometric calibrations and corrections on landscape characterization

James E. Vogelmann; Dennis L. Helder; Ron Morfitt; Michael Choate; James W. Merchant; Henry Bulley

The Thematic Mapper (TM) instruments onboard Landsats 4 and 5 provide high-quality imagery appropriate for many different applications, including land cover mapping, landscape ecology, and change detection. Precise calibration was considered to be critical to the success of the Landsat 7 mission and, thus, issues of calibration were given high priority during the development of the Enhanced Thematic Mapper Plus (ETM+). Data sets from the Landsat 5 TM are not routinely corrected for a number of radiometric and geometric artifacts, including memory effect, gain/bias, and interfocal plane misalignment. In the current investigation, the effects of correcting vs. not correcting these factors were investigated for several applications. Gain/bias calibrations were found to have a greater impact on most applications than did memory effect calibrations. Correcting interfocal plane offsets was found to have a moderate effect on applications. On June 2, 1999, Landsats 5 and 7 data were acquired nearly simultaneously over a study site in the Niobrara, NE area. Field radiometer data acquired at that site were used to facilitate crosscalibrations of Landsats 5 and 7 data. Current findings and results from previous investigations indicate that the internal calibrator of Landsat 5 TM tracked instrument gain well until 1988. After this, the internal calibrator diverged from the data derived from vicarious calibrations. Results from this study also indicate very good agreement between prelaunch measurements and vicarious calibration data for all Landsat 7 reflective bands except Band 4. Values are within about 3.5% of each other, except for Band 4, which differs by 10%. Coefficient of variation (CV) values derived from selected targets in the imagery were also analyzed. The Niobrara Landsat 7 imagery was found to have lower CV values than Landsat 5 data, implying that lower levels of noise characterize Landsat 7 data than current Landsat 5 data. It was also found that following radiometric normalization, the Normalized Difference Vegetation Index (NDVI) imagery and classification products of Landsats 5 and 7 were very similar. This implies that data from the two sensors can be used to measure and monitor the same landscape phenomena and that Landsats 5 and 7 data can be used interchangeably with proper caution. In addition, it was found that difference imagery produced using Landsat 7 ETM+ data are of excellent quality.


Canadian Journal of Remote Sensing | 2003

Landsat TM and ETM+ thermal band calibration

Julia A. Barsi; John R. Schott; F D Palluconi; Dennis L. Helder; Simon J. Hook; Brian L. Markham; Gyanesh Chander; E M O'Donnell

Landsat-5 has been imaging the Earth since March 1984, and Landsat-7 was added to the series of Landsat instruments in April 1999. The Landsat Project Science Office and the Landsat-7 Image Assessment System have been monitoring the on-board calibration of Landsat-7 since launch. Additionally, two separate university teams have been evaluating the on-board thermal calibration of Landsat-7 through ground-based measurements since launch. Although not monitored as closely over its lifetime, a new effort is currently being made to validate the calibration of Landsat-5. Two university teams are beginning to collect ground truth under Landsat-5, along with using other vicarious calibration methods to go back into the archive to validate the history of the calibration of Landsat-5. This paper considers the calibration efforts for the thermal band, band 6, of both the Landsat-5 and Landsat-7 instruments. Though stable since launch, Landsat-7 had an initial calibration error of about 3 K, and changes were made to correct for this beginning 1 October 2000 for data processed with the National Landsat Archive Production System (NLAPS) and beginning 20 December 2000 for data processed with the Landsat Product Generation System (LPGS). Recent results from Landsat-5 vicarious calibration efforts show an offset of ‐0.7 K over the lifetime of the instrument. This suggests that historical calibration efforts may have been detecting errors in processing systems rather than changes in the instrument. A correction to the Landsat-5 processing has not yet been implemented but will be in the near future.


Remote Sensing | 2014

Landsat-8 Operational Land Imager Radiometric Calibration and Stability

Brian L. Markham; Julia A. Barsi; Geir Kvaran; Lawrence Ong; Edward Kaita; Stuart F. Biggar; Jeffrey S. Czapla-Myers; Nischal Mishra; Dennis L. Helder

The Landsat-8 Operational Land Imager (OLI) was radiometrically calibrated prior to launch in terms of spectral radiance, using an integrating sphere source traceable to National Institute of Standards and Technology (NIST) standards of spectral irradiance. It was calibrated on-orbit in terms of reflectance using diffusers characterized prior to launch using NIST traceable standards. The radiance calibration was performed with an uncertainty of ~3%; the reflectance calibration to an uncertainty of ~2%. On-orbit, multiple calibration techniques indicate that the sensor has been stable to better than 0.3% to date, with the exception of the shortest wavelength band, which has degraded about 1.0%. A transfer to orbit experiment conducted using the OLI’s heliostat-illuminated diffuser suggests that some bands increased in sensitivity on transition to orbit by as much as 5%, with an uncertainty of ~2.5%. On-orbit comparisons to other instruments and vicarious calibration techniques show the radiance (without a transfer to orbit adjustment), and reflectance calibrations generally agree with other instruments and ground measurements to within the uncertainties. Calibration coefficients are provided with the data products to convert to either radiance or reflectance units.


IEEE Transactions on Geoscience and Remote Sensing | 2004

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

Kurtis J. Thome; Dennis L. Helder; David Aaron; James D. Dewald

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%.


IEEE Transactions on Geoscience and Remote Sensing | 2004

Landsat-5 TM reflective-band absolute radiometric calibration

Gyanesh Chander; Dennis L. Helder; Brian L. Markham; James D. Dewald; Ed Kaita; Kurtis J. Thome; Esad Micijevic; Timothy A. Ruggles

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 instruments 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 instruments 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.


IEEE Transactions on Geoscience and Remote Sensing | 2004

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

Gyanesh Chander; David J. Meyer; Dennis L. Helder

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 ALIs 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%.


IEEE Transactions on Geoscience and Remote Sensing | 2013

Applications of Spectral Band Adjustment Factors (SBAF) for Cross-Calibration

Gyanesh Chander; Nischal Mishra; Dennis L. Helder; David Aaron; Amit Angal; Taeyoung Choi; Xiaoxiong Xiong; David R. Doelling

To monitor land surface processes over a wide range of temporal and spatial scales, it is critical to have coordinated observations of the Earths surface acquired from multiple spaceborne imaging sensors. However, an integrated global observation framework requires an understanding of how land surface processes are seen differently by various sensors. This is particularly true for sensors acquiring data in spectral bands whose relative spectral responses (RSRs) are not similar and thus may produce different results while observing the same target. The intrinsic offsets between two sensors caused by RSR mismatches can be compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of the two sensors. The motivation of this work comes from the need to compensate the spectral response differences of multispectral sensors in order to provide a more accurate cross-calibration between the sensors. In this paper, radiometric cross-calibration of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors was performed using near-simultaneous observations over the Libya 4 pseudoinvariant calibration site in the visible and near-infrared spectral range. The RSR differences of the analogous ETM+ and MODIS spectral bands provide the opportunity to explore, understand, quantify, and compensate for the measurement differences between these two sensors. The cross-calibration was initially performed by comparing the top-of-atmosphere (TOA) reflectances between the two sensors over their lifetimes. The average percent differences in the long-term trends ranged from -5% to +6%. The RSR compensated ETM+ TOA reflectance (ETM+*) measurements were then found to agree with MODIS TOA reflectance to within 5% for all bands when Earth Observing-1 Hyperion hyperspectral data were used to produce the SBAFs. These differences were later reduced to within 1% for all bands (except band 2) by using Environmental Satellite Scanning Imaging Absorption Spectrometer for Atmospheric Cartography hyperspectral data to produce the SBAFs.


Remote Sensing | 2015

The Ground-Based Absolute Radiometric Calibration of Landsat 8 OLI

Jeffrey S. Czapla-Myers; Joel McCorkel; Nikolaus Anderson; Kurtis J. Thome; Stuart F. Biggar; Dennis L. Helder; David Aaron; Larry Leigh; Nischal Mishra

This paper presents the vicarious calibration results of Landsat 8 OLI that were obtained using the reflectance-based approach at test sites in Nevada, California, Arizona, and South Dakota, USA. Additional data were obtained using the Radiometric Calibration Test Site, which is a suite of instruments located at Railroad Valley, Nevada, USA. The results for the top-of-atmosphere spectral radiance show an average difference of −2.7, −0.8, 1.5, 2.0, 0.0, 3.6, 5.8, and 0.7% in OLI bands 1–8 as compared to an average of all of the ground-based measurements. The top-of-atmosphere spectral reflectance shows an average difference of 1.6, 1.3, 2.0, 1.9, 0.9, 2.1, 3.1, and 2.1% from the ground-based measurements. Except for OLI band 7, the spectral radiance results are generally within ±5% of the design specifications, and the reflectance results are generally within ±3% of the design specifications. The results from the data collected during the tandem Landsat 7 and 8 flight in March 2013 indicate that ETM+ and OLI agree to each other to within ±2% in similar bands in top-of-atmosphere spectral radiance, and to within ±4% in top-of-atmosphere spectral reflectance.


Remote Sensing | 2014

Radiometric Cross Calibration of Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM

Nischal Mishra; Md. Obaidul Haque; Larry Leigh; David Aaron; Dennis L. Helder; Brian L. Markham

This study evaluates the radiometric consistency between Landsat-8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) using cross calibration techniques. Two approaches are used, one based on cross calibration between the two sensors using simultaneous image pairs, acquired during an underfly event on 29–30 March 2013. The other approach is based on using time series of image statistics acquired by these two sensors over the Libya 4 pseudo invariant calibration site (PICS) (+28.55°N, +23.39°E). Analyses from these approaches show that the reflectance calibration of OLI is generally within ±3% of the ETM+ radiance calibration for all the reflective bands from visible to short wave infrared regions when the ChKur solar spectrum is used to convert the ETM+ radiance to reflectance. Similar results are obtained comparing the OLI radiance calibration directly with the ETM+ radiance calibration and the results in these two different physical units (radiance and reflectance) agree to within ±2% for all the analogous bands. These results will also be useful to tie all the Landsat heritage sensors from Landsat 1 MultiSpectral Scanner (MSS) through Landsat-8 OLI to a consistent radiometric scale.


IEEE Transactions on Geoscience and Remote Sensing | 2004

In-flight validation and recovery of water surface temperature with Landsat-5 thermal infrared data using an automated high-altitude lake validation site at Lake Tahoe

Simon J. Hook; Gyanesh Chander; Julia A. Barsi; Ronald E. Alley; Ali A. Abtahi; Frank D. Palluconi; Brian L. Markham; R.C. Richards; S.G. Schladow; Dennis L. Helder

The absolute radiometric accuracy of the thermal infrared band (B6) of the Thematic Mapper (TM) instrument on the Landsat-5 (L5) satellite was assessed over a period of approximately four years using data from the Lake Tahoe automated validation site (California-Nevada). The Lake Tahoe site was established in July 1999, and measurements of the skin and bulk temperature have been made approximately every 2 min from four permanently moored buoys since mid-1999. Assessment involved using a radiative transfer model to propagate surface skin temperature measurements made at the time of the L5 overpass to predict the at-sensor radiance. The predicted radiance was then convolved with the L5B6 system response function to obtain the predicted L5B6 radiance, which was then compared with the radiance measured by L5B6. Twenty-four cloud-free scenes acquired between 1999 and 2003 were used in the analysis with scene temperatures ranging between 4/spl deg/C and 22/spl deg/C. The results indicate L5B6 had a radiance bias of 2.5% (1.6/spl deg/C) in late 1999, which gradually decreased to 0.8% (0.5/spl deg/C) in mid-2002. Since that time, the bias has remained positive (predicted minus measured) and between 0.3% (0.2/spl deg/C) and 1.4% (0.9/spl deg/C). The cause for the cold bias (L5 radiances are lower than expected) is unresolved, but likely related to changes in instrument temperature associated with changes in instrument usage. The in situ data were then used to develop algorithms to recover the skin and bulk temperature of the water by regressing the L5B6 radiance and the National Center for Environmental Prediction (NCEP) total column water data to either the skin or bulk temperature. Use of the NCEP data provides an alternative approach to the split-window approach used with instruments that have two thermal infrared bands. The results indicate the surface skin and bulk temperature can be recovered with a standard error of 0.6/spl deg/C. This error is larger than errors obtained with other instruments due, in part, to the calibration bias. L5 provides the only long-duration high spatial resolution thermal infrared measurements of the land surface. If these data are to be used effectively in studies designed to monitor change, it is essential to continue to monitor instrument performance in-flight and develop quantitative algorithms for recovering surface temperature.

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Dive into the Dennis L. Helder's collaboration.

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Brian L. Markham

Goddard Space Flight Center

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Julia A. Barsi

Goddard Space Flight Center

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Gyanesh Chander

United States Geological Survey

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Nischal Mishra

South Dakota State University

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Kurtis J. Thome

Goddard Space Flight Center

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David Aaron

South Dakota State University

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John L. Barker

Goddard Space Flight Center

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Taeyoung Choi

South Dakota State University

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Amit Angal

Goddard Space Flight Center

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Esad Micijevic

United States Geological Survey

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