Investigations on the Geometric Quality of AVHRR Level 1B Imagery Aboard MetOp-A

This article reviews the role that photogrammetry plays in evaluating the geometric quality of satellite products in connection to the long-term monitoring of essential climate variables (ECVs). The Global Climate Observing System (GCOS) is responsible for defining the observations required for climate monitoring. Only satellite products are capable of providing high-quality observations of a particular subset of ECVs on a global scale. Geometric calibration and validation of these products are crucial for ensuring the coherence of data obtained across platforms and sensors and reliable monitoring in the long term. Here, we analyzed the GCOS implementation plan and the data quality requirements and explored various geometric quality aspects, such as internal and external accuracy and band-to-band registration assessment, for a number of satellite sensors commonly used for climate monitoring. Both geostationary (GEO) and low-earth orbit (LEO) sensors with resolutions between 250 m and 3 km were evaluated for this purpose. The article highlights that the geometric quality issues vary with the sensor, and regular monitoring of data quality and tuning of calibration parameters are essential for identifying and reducing the uncertainty in the derived climate observations.

Section: Geometric Quality Assessment (Gqa) Of Ecvs Using Photogrammetrymentioning

confidence: 99%

Section: Avhrrmentioning

confidence: 99%

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Contribution of Photogrammetry for Geometric Quality Assessment of Satellite Data for Global Climate Monitoring

Kocaman,

Seiz

2023

“…Furthermore, a dense image matching approach was applied to the two datasets. This method is based on the Kanade-Lucas-Tomas (KLT) tracker [41], with an expected measurement accuracy of 0.1 pixel, and has been successfully applied in the assessment of lower-resolution satellite images in previous studies (e.g., [39,42,43]). The assessment was performed on the red band images, since this band has good contrast and a higher SNR.…”

Section: Geometric Calibration Quality Assessment Approachmentioning

confidence: 99%

SkySat Data Quality Assessment within the EDAP Framework

Saunier¹,

Karakas

Yalcin

et al. 2022

Self Cite

Cal/Val activities within the Earthnet Data Assessment Pilot (EDAP) Project of the European Space Agency (ESA) cover several Earth Observation (EO) satellite sensors, including Third-Party Missions (TPMs). As part of the validation studies of very-high-resolution (VHR) sensor data, the geometric and radiometric quality of the images and the mission compliance of the SkySat satellites owned by Planet were evaluated in this study. The SkySat constellation provides optical images with a nominal spatial resolution of 50 cm, and has the capacity for multiple visits of any place on Earth each day. The evaluations performed over several test sites for the purpose of the EDAP Maturity Matrix generation show that the high resolution requirement is fulfilled with high geometric accuracy, although various systematic and random errors could be observed. The 2D and 3D information extracted from SkySat data conform to the quality expectations for the given resolution, although improvements to the vendor-provided rational polynomial coefficients (RPCs) are essential. The results show that the SkySat constellation is compliant with the specifications and the accuracy results are within the ranges claimed by the vendor. The signal-to-noise ratio assessments revealed that the quality is high, but variations occur between the different sensors.

“…The feature points extracted with the Good Features algorithm of Shi and Tomasi [26] are employed in the process to increase the matching success and the reliability. This methodology was utilized in earlier projects [27][28][29][30][31][32] demonstrating that computer vision technics are beneficial for EO data processing. As shown in Figure 2, the geometric assessment results are obtained from the matching between near infrared (NIR) band images of both sensors and then extrapolated to all other bands for correction purposes.…”

Section: Geometric Correctionmentioning

confidence: 99%

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

Saunier¹,

Pflug

Moletto‐Lobos

et al. 2022

Self Cite

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.