Initial Cross-Calibration of Landsat 8 and Landsat 9 Using the Simultaneous Underfly Event

Gross, Garrison; Helder, Dennis L.; Begeman, Christopher; Leigh, Larry; Kaewmanee, Morakot; Shah, Ramita

doi:10.3390/rs14102418

Cited by 32 publications

(38 citation statements)

References 18 publications

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“…From the computational and storage point of view, only one hyperspectral product will be stored, serving both the S2L and the hyperspectral L2A users, and fewer computation-al resources will be required to convolve the hyperspectral L2A products to any other MS missions, even when the SRFs of MS missions change. These results also confirm that new MS sensors with more spectral bands than S2 can be easily included in the algorithm (e.g., S2 NG [68], L9 [69]).…”

Section: Adaptation To Further Optical Missionssupporting

confidence: 74%

Sen2Like: Paving the Way towards Harmonization and Fusion of Optical Data

Saunier¹,

Pflug

Moletto‐Lobos

et al. 2022

Remote Sensing

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Satellite Earth Observation (EO) sensors are becoming a vital source of information for land surface monitoring. The concept of the Virtual Constellation (VC) is gaining interest within the science community owing to the increasing number of satellites/sensors in operation with similar characteristics. The establishment of a VC out of individual missions offers new possibilities for many application domains, in particular in the fields of land surface monitoring and change detection. In this context, this paper describes the Copernicus Sen2Like algorithms and software, a solution for harmonizing and fusing Landsat 8/Landsat 9 data with Sentinel-2 data. Developed under the European Union Copernicus Program, the Sen2Like software processes a large collection of Level 1/Level 2A products and generates high quality Level 2 Analysis Ready Data (ARD) as part of harmonized (Level 2H) and/or fused (Level 2F) products providing high temporal resolutions. For this purpose, we have re-used and developed a broad spectrum of data processing and analysis methodologies, including geometric and spectral co-registration, atmospheric and Bi-Directional Reflectance Distribution Function (BRDF) corrections and upscaling to 10 m for relevant Landsat bands. The Sen2Like software and the algorithms have been developed within a VC establishment framework, and the tool can conveniently be used to compare processing algorithms in combinations. It also has the potential to integrate new missions from spaceborne and airborne platforms including unmanned aerial vehicles. The validation activities show that the proposed approach improves the temporal consistency of the multi temporal data stack, and output products are interoperable with the subsequent thematic analysis processes.

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Section: Adaptation To Further Optical Missionssupporting

confidence: 74%

Sen2Like: Paving the Way towards Harmonization and Fusion of Optical Data

Saunier¹,

Pflug

Moletto‐Lobos

et al. 2022

Remote Sensing

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“…Recent cross-calibrations [30] between Landsat 8 and Landsat 9 OLI instruments show that the TCU can be less than 1% if several potential error contributors are accounted for. While these cross-calibrations were not used to develop a new SI traceability, they were used to understand the relative gain differences between Landsat 8 and 9 for each spectral band.…”

Section: Transfer Calibration Uncertaintymentioning

confidence: 99%

Concept of a Satellite Cross-Calibration Radiometer for In-Orbit Calibration of Commercial Optical Satellites

Thankappan,

Christopherson,

Cantrell

et al. 2024

Remote Sensing

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The satellite Earth observation (EO) sector is burgeoning with hundreds of commercial satellites being launched each year, delivering a rich source of data that could be exploited for societal benefit. Data streams from the growing number of commercial satellites are of variable quality, limiting the potential for their combined use in science applications that need long time-series data from multiple sources. The quality of calibration performed on optical sensors onboard many satellite systems is highly variable due to calibration methods, sensor design, mission objective, budget, or other operational constraints. A small number of currently operating well-characterised satellite systems with onboard calibration, such as Landsat-8/9 and Sentinel-2, and planned future missions, like the NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder, the European Space Agency (ESA)’s Traceable Radiometry Underpinning Terrestrial and Helio Studies (TRUTHS), and LIBRA from China, are considered benchmarks for optical data quality due to their traceability to international measurement standards. This paper describes the concept of a space-based transfer calibration radiometer called the Satellite Cross-Calibration Radiometer (SCR) that would enable the calibration parameters from satellites such as Landsat-8/9, Sentinel-2, or other benchmark systems to be transferred to a range of commercial optical EO satellite systems while in orbit. A description of the key characteristics of the SCR to successfully operate in orbit and transfer calibration from reference systems to client systems is presented. A system like the SCR in orbit could complement SI-Traceable satellites (SITSats) to improve data quality and consistency and facilitate the interoperable use of data from multiple optical sensor systems for delivering higher returns on the global investment in EO.

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“…Landsat 9, like Landsat 8, has a higher imaging capacity than previous Landsat, enabling the addition of more critical data to the Landsat global land archive-around 1400 scenes every day. Landsat 9 collects and archives moderate-resolution reflective and emissive multi-spectral picture data for a minimum of five years to provide seasonal coverage of the worldwide land mass [25,26]. Landsat 9 L2C2 data was tested in this study.…”

Section: Landsat 9 Oli-2mentioning

confidence: 99%

Method of Validating Satellite Surface Reflectance Product Using Empirical Line Method

et al. 2023

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Atmospherically corrected surface reflectance (SR) products are used for reliable monitoring of land surfaces and are the standard products of Landsat sensors. Due to increased demand for SR products, a need exists to verify that the L2C2 (Level-2 Collection-2) SR products are precise and accurate. The Level-2 Collection 2 (L2C2) SR Product has processed satellite imagery data that correct for atmospheric effects such as absorption and scattering, providing a more accurate representation of Earth’s surface. The validation of SR products using ground truth measurement is essential. This study aims to develop and evaluate a validation methodology for satellite SR products. Thus, the Empirical Line Method (ELM) is used here for atmospheric validation of remotely sensed data. Validation is performed using the SR derived from ELM tied to ground truth measurement. Absolute surface reflectance models of Algodones Dunes and the Salton Sea located in North America Sonoran Desert are developed to extend the temporally limited ground truth measurements. This model can give ground truth reflectance in any time frame independent of time constraints. The result of the absolute surface reflectance model of Algodones Dunes indicates that the model predicts the response of Algodones Dunes with an average accuracy of 0.0041 and precision of 0.0063 and gives ground measurements across all multispectral between 350 and 2500 nm. For the Salton Sea, the model predicts the response of the Salton Sea with mean absolute error (MAE) of 0.0035 and gives ground measurements across all multispectral between 350 and 2500 nm. The ELM generates atmospheric coefficients (gain and bias), which are applied to an image to obtain SR. Validation results indicated that for L9-OLI-2, L8-OLI, and L5-TM-SR products, the RMSE range is 0.0019 to 0.0106, 0.0019 to 0.0148 and 0.0026 to 0.0045 reflectance unit, respectively, and accuracy is within 0.0038, 0.0022, and 0.0055 reflectance unit across all spectral bands of L9, L8, and L5, respectively. On average, the validation result showed a strong linear relation between the L2C2 SR products and ELM SR within 0.5 to 1 reflectance units. These results demonstrate the high accuracy and reliability of the L2C2 SR product, providing valuable information for a wide range of remote sensing applications, including land cover and land use mapping, vegetation monitoring, and climate change studies.

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Initial Cross-Calibration of Landsat 8 and Landsat 9 Using the Simultaneous Underfly Event

Cited by 32 publications

References 18 publications

Sen2Like: Paving the Way towards Harmonization and Fusion of Optical Data

Sen2Like: Paving the Way towards Harmonization and Fusion of Optical Data

Concept of a Satellite Cross-Calibration Radiometer for In-Orbit Calibration of Commercial Optical Satellites

Method of Validating Satellite Surface Reflectance Product Using Empirical Line Method

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