Lifetime Absolute Calibration of the EO-1 Hyperion Sensor and its Validation

Jing, Xin; Leigh, Larry; Helder, Dennis L.; Pinto, Cibele Teixeira; Aaron, David

doi:10.1109/tgrs.2019.2926663

Cited by 13 publications

(15 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…usgs.gov, accessed on 1 December 2018) over Cluster 13, and pixels containing more than 10 percent of cloud pixels are discarded, along with t images with a 5 degrees look angle or greater, as described by Shrestha et al [25]. A total of 213 hyperspectral images were obtained and were drift-corrected, along with absolute gain and bias correction [26]. Figure 2 shows the hyperspectral profiles extracted from Hyperion to estimate the hyperspectral profile of Cluster 13, where the yellow dots represent the mean hyperspectral signature.…”

Section: Estimation Of Spectral Band Adjustment Factormentioning

confidence: 99%

Extended Pseudo Invariant Calibration Site-Based Trend-to-Trend Cross-Calibration of Optical Satellite Sensors

et al. 2021

Self Cite

View full text Add to dashboard Cite

Satellite sensors have been extremely useful and are in massive demand in the understanding of the Earth’s surface and monitoring of changes. For quantitative analysis and acquiring consistent measurements, absolute radiometric calibration is necessary. The most common vicarious approach of radiometric calibration is cross-calibration, which helps to tie all the sensors to a common radiometric scale for consistent measurement. One of the traditional methods of cross-calibration is performed using temporally and spectrally stable pseudo-invariant calibration sites (PICS). This technique is limited by adequate cloud-free acquisitions for cross-calibration which would require a longer time to study the differences in sensor measurements. To address the limitation of traditional PICS-based approaches and to increase the cross-calibration opportunity for quickly achieving high-quality results, the approach presented here is based on using extended pseudo invariant calibration sites (EPICS) over North Africa. With the EPICS-based approach, the area of extent of the cross-calibration site covers a large portion of the North African continent. With targets this large, many sensors should image some portion of EPICS nearlydaily, allowing for evaluation of performance with much greater frequency. By using these near-daily measurements, trends of the sensor’s performance are then used to evaluate sensor-to-sensor daily cross-calibration. With the use of the proposed methodology, the dataset for cross-calibration is increased by an order of magnitude compared to traditional approaches, resulting in the differences between any two sensors being detected within a much shorter time. Using this new trend in trend cross-calibration approaches, gains were evaluated for Landsat 7/8 and Sentinel 2A/B, with the results showing that the sensors are calibrated within 2.5% (within less than 8% uncertainty) or better for all sensor pairs, which is consistent with what the traditional PICS-based approach detects. The proposed cross-calibration technique is useful to cross-calibrate any two sensors without the requirement of any coincident or near-coincident scene pairs, while still achieving results similar to traditional approaches in a short time.

show abstract

Section: Estimation Of Spectral Band Adjustment Factormentioning

confidence: 99%

Extended Pseudo Invariant Calibration Site-Based Trend-to-Trend Cross-Calibration of Optical Satellite Sensors

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…This suggests that the relative stability between different channels of Hyperion is at least 5% for the VNIR region and 10% for the SWIR region. Recently, Jing et al [17] derived a set of calibration gain and bias coefficients from reflectance-based vicarious calibration at the South Dakota State University vegetative site and available in-situ Radiometric Calibration Network (RadCalNet) data from the Railroad Valley site.…”

Section: Hyperion Sensor Description and Previous Radiometric Calibramentioning

confidence: 99%

“…where ρ λ is the TOA reflectance of different bands (λ) of Hyperion, Yr is the decimal year representing the acquisition date and overpass time, ρ λ, drift_cor is the Hyperion TOA profile after yearly drift correction, and %drift λ year is the percent yearly drift of band λ estimated from (1). For gain and bias correction, the latest set of calibration coefficients reported by Jing et al [17] should be applied after performing the drift correction:…”

Section: Drift Correction and Calibration Gain/bias Applicationmentioning

confidence: 99%

“…Drift correction using equations (1) and (2) was applied to 14 Hyperion channels exhibiting statistically significant drift in their response [17]. The resulting hyperspectral profiles are shown in Figure 7, with the red profile representing the original spectrum and the green profile representing the drift-corrected spectrum.…”

Section: Pre-processing Of Hyperspectral Profiles Of Cluster 13mentioning

confidence: 99%

“…The hyperspectral data from these 15 locations are subjected to drift correction, application of calibration gain and bias and BRDF correction before using them to estimate the Cluster 13 representative hyperspectral profile. Drift correction using equations (1) and (2) was applied to 14 Hyperion channels exhibiting statistically significant drift in their response [17]. The resulting hyperspectral profiles are shown in Figure 7, with the red profile representing the original spectrum and the green profile representing the drift-corrected spectrum.…”

Section: Pre-processing Of Hyperspectral Profiles Of Cluster 13mentioning

confidence: 99%

See 2 more Smart Citations

Derivation of Hyperspectral Profile of Extended Pseudo Invariant Calibration Sites (EPICS) for Use in Sensor Calibration

et al. 2019

Self Cite

View full text Add to dashboard Cite

Reference of Earth-observing satellite sensor data to a common, consistent radiometric scale is an increasingly critical issue as more of these sensors are launched; such consistency can be achieved through radiometric cross-calibration of the sensors. A common cross-calibration approach uses a small set of regions of interest (ROIs) in established Pseudo-Invariant Calibration Sites (PICS) mainly located throughout North Africa. The number of available cloud-free coincident scene pairs available for these regions limits the usefulness of this approach; furthermore, the temporal stability of most regions throughout North Africa is not known, and limited hyperspectral information exists for these regions. As a result, it takes more time to construct an appropriate cross-calibration dataset. In a previous work, Shrestha et al. presented an analysis identifying 19 distinct “clusters” of spectrally similar surface cover that are widely distributed across North Africa, with the potential to provide near-daily cloud-free imaging for most sensors. This paper proposes a technique to generate a representative hyperspectral profile for these clusters. The technique was used to generate the profile for the cluster containing the largest number of aggregated pixels. The resulting profile was found to have temporal uncertainties within 5% across all the spectral regions. Overall, this technique shows great potential for generation of representative hyperspectral profiles for any North African cluster, which could allow the use of the entire North Africa Saharan region as an extended PICS (EPICS) dataset for sensor cross-calibration. This should result in the increased temporal resolution of cross-calibration datasets and should help to achieve a cross-calibration quality similar to that of individual PICS in a significantly shorter time interval. It also facilitates the development of an EPICS based absolute calibration model, which can improve the accuracy and consistency in simulating any sensor’s top of atmosphere (TOA) reflectance.

show abstract

Validation of ZY1-02D Satellite Multispectral Sensor on-Orbit Radiometric Calibration Accuracy

Tang

Zhang

Hui

2022

Lecture Notes in Electrical Engineering

View full text Add to dashboard Cite

Lifetime Absolute Calibration of the EO-1 Hyperion Sensor and its Validation

Cited by 13 publications

References 20 publications

Extended Pseudo Invariant Calibration Site-Based Trend-to-Trend Cross-Calibration of Optical Satellite Sensors

Extended Pseudo Invariant Calibration Site-Based Trend-to-Trend Cross-Calibration of Optical Satellite Sensors

Derivation of Hyperspectral Profile of Extended Pseudo Invariant Calibration Sites (EPICS) for Use in Sensor Calibration

Validation of ZY1-02D Satellite Multispectral Sensor on-Orbit Radiometric Calibration Accuracy

Contact Info

Product

Resources

About