EO-1 Data Quality and Sensor Stability with Changing Orbital Precession at the End of a 16 Year Mission

Franks, Shannon; Neigh, C. S. R.; Campbell, Petya K. E.; Sun, Guoqing; Yao, Tian; Zhang, Qingyuan; Huemmrich, K. F.; Middleton, Elizabeth M.; Ungar, Stephen; Frye, Stuart

doi:10.3390/rs9050412

Cited by 18 publications

(22 citation statements)

References 45 publications

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“…In the analysis of data acquired by near polar orbiting satellites, especially those having large FOV instruments, like MODIS, directional and VZA effects are more important than SZA effects. Differently from the VZA, the SZA exhibits a seasonal cycle, having an amplitude that increases with latitude [42]. Therefore, illumination effects tend to be stronger in the southern Amazon (site 3), where the SZA amplitude reaches 18 • between the rainy and dry seasons.…”

Section: Discussionmentioning

confidence: 98%

Sensitivity of Seven MODIS Vegetation Indices to BRDF Effects during the Amazonian Dry Season

Petri

Galvão

2019

Remote Sensing

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We used Moderate Resolution Imaging Spectroradiometer (MODIS) data, processed by the multi–angle implementation of atmospheric correction (MAIAC) algorithm, to investigate the sensitivity of seven vegetation indices (VIs) to bidirectional reflectance distribution function (BRDF) effects in the dry season (June–September) of the Brazilian Amazon. The analysis was first performed over three sites, located from north to south of the Amazon, and then extended into the entire region. We inspected for differences in viewing–illumination parameters and pixel quality retrievals during MODIS data acquisition over the region. By comparing and correlating corrected and non–corrected data for bidirectional effects, we evaluated monthly changes in reflectance and VIs (2000–2014). Finally, we computed the effect size of the BRDF correction using non–parametric Mann–Whitney tests and Cohen’s r metrics. The results showed that the most anisotropic VIs were the enhanced vegetation index (EVI), photochemical reflectance index (PRI), and shortwave infrared normalized difference (SWND). These VIs presented the largest relative changes and the lowest correlation coefficients, between corrected and non–corrected data, because of the large effect size of the BRDF. The least anisotropic VI was the normalized difference water index (NDWI). The anisotropy of these VIs was stronger in the northern Amazon. It increased from the beginning to the end of the dry season, following changes in the relative azimuth angle (RAA) toward the BRDF hotspot in September. The modifications in the relative proportions of backscattering observations used in composite products caused a reflectance increase in all MODIS bands at the end of the dry season, especially in the near infrared (NIR). The reflectance decreased after BRDF correction. Because of the atmospheric effects, the view zenith angle (VZA) of the pixels selected in composite products decreased toward the south of the Amazon. In the southern Amazon, the seasonal amplitude in the solar zenith angle (SZA) reached values close to 18°. For the most anisotropic index, the BRDF correction removed, on average, 30% of the EVI signal in June, and 60% of the EVI signal in September, reducing dry season variations over time. The results reinforce the need for bidirectional correction of MODIS data before the seasonal and inter–annual analyses of the most anisotropic VIs.

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Section: Discussionmentioning

confidence: 98%

Sensitivity of Seven MODIS Vegetation Indices to BRDF Effects during the Amazonian Dry Season

Petri

Galvão

2019

Remote Sensing

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“…Any well-calibrated sensor with hyperspectral imaging capacity can be a useful source to structure the BRDF effect over a wide range of wavelengths. A good source of the hyperspectral system: Hyperion EO-1 has 220 unique spectral channels varying from 0.357 to 2.576 micrometers along with a 10-nm bandwidth and also has an absolute calibration capacity of 5% [23]. Forming a BRDF model using Hyperion helps to overcome the limitation of interpolating BRDF coefficients from the multispectral level to the hyperspectral one and can provide true coefficients even in absorption bands.…”

Section: Hyperspectral Brdf Modelmentioning

confidence: 99%

Hyperspectral Empirical Absolute Calibration Model Using Libya 4 Pseudo Invariant Calibration Site

et al. 2021

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The objective of this paper is to find an empirical hyperspectral absolute calibration model using Libya 4 pseudo invariant calibration site (PICS). The approach involves using the Landsat 8 (L8) Operational Land Imager (OLI) as the reference radiometer and using Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm as a hyperspectral source. This model utilizes data from a region of interest (ROI) in an “optimal region” of 3% temporal, spatial, and spectral stability within the Libya 4 PICS. It uses an improved, simple, empirical, hyperspectral Bidirectional Reflectance Distribution function (BRDF) model accounting for four angles: solar zenith and azimuth, and view zenith and azimuth angles. This model can perform absolute calibration in 1 nm spectral resolution by predicting TOA reflectance in all existing spectral bands of the sensors. The resultant model was validated with image data acquired from satellite sensors such as Landsat 7, Sentinel 2A, and Sentinel 2B, Terra MODIS, Aqua MODIS, from their launch date to 2020. These satellite sensors differ in terms of the width of their spectral bandpass, overpass time, off-nadir viewing capabilities, spatial resolution, and temporal revisit time, etc. The result demonstrates the efficacy of the proposed model has an accuracy of the order of 3% with a precision of about 3% for the nadir viewing sensors (with view zenith angle up to 5) used in the study. For the off-nadir viewing satellites with view zenith angle up to 20, it can have an estimated accuracy of 6% and precision of 4%.

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“…It images a 7 km by 100 km swath at a spatial resolution of 30 m. Between 2001 and 2007, Hyperion flew one minute behind the Landsat 7 ETM+, in the same orbital path; after 2007, its orbit was lowered by approximately 5 km. Beginning in 2011, its orbit steadily degraded as it used up its maneuvering fuel supply [9], resulting in its ultimate decommissioning from active service in March 2017.…”

Section: Hyperion Sensor Description and Previous Radiometric Calibramentioning

confidence: 99%

“…The Hyperion data were also affected by orbital precession. Beginning in 2011, inclination burns to maintain EO-1's initial orbital position were stopped due to lack of onboard fuel [9]. As a result, orbital precession effects led to successively earlier local overpass times and increased solar zenith (decreased solar elevation) angles.…”

Section: Data Filteringmentioning

confidence: 99%

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

et al. 2019

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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.

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EO-1 Data Quality and Sensor Stability with Changing Orbital Precession at the End of a 16 Year Mission

Cited by 18 publications

References 45 publications

Sensitivity of Seven MODIS Vegetation Indices to BRDF Effects during the Amazonian Dry Season

Sensitivity of Seven MODIS Vegetation Indices to BRDF Effects during the Amazonian Dry Season

Hyperspectral Empirical Absolute Calibration Model Using Libya 4 Pseudo Invariant Calibration Site

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

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