Design and development of the Sentinel-2 Multi Spectral Instrument and satellite system

Combining data from multiple sensors into a single seamless time series, also known as data interoperability, has the potential for unlocking new understanding of how the Earth functions as a system. However, our ability to produce these advanced data sets is hampered by the differences in design and function of the various optical remote-sensing satellite systems. A key factor is the impact that calibration of these instruments has on data interoperability. To address this issue, a workshop with a panel of experts was convened in conjunction with the Pecora 20 conference to focus on data interoperability between Landsat and the Sentinel 2 sensors. Four major areas of recommendation were the outcome of the workshop. The first was to improve communications between satellite agencies and the remote-sensing community. The second was to adopt a collections-based approach to processing the data. As expected, a third recommendation was to improve calibration methodologies in several specific areas. Lastly, and the most ambitious of the four, was to develop a comprehensive process for validating surface reflectance products produced from the data sets. Collectively, these recommendations have significant potential for improving satellite sensor calibration in a focused manner that can directly catalyze efforts to develop data that are closer to being seamlessly interoperable.

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Section: Sensor Descriptionmentioning

confidence: 99%

“…The MSI is a pushbroom imager with a three-mirror anastigmat design utilizing 10 focal plane modules forming 10 bands in the visible and near-infrared (VNIR) and 3 bands in the SWIR (see [12] for a complete description). A solar diffuser can be positioned at the entry of the telescope for radiometric calibration purposes.…”

Section: Sensor Descriptionmentioning

confidence: 99%

Observations and Recommendations for the Calibration of Landsat 8 OLI and Sentinel 2 MSI for Improved Data Interoperability

et al. 2018

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“…The SWIR detector is based on hybrid HgCdTe-CMOS technology where the Hg1-xCdxTe or Mercury Cadmium Telluride (MCT) is hybridized to a silicon readout circuit ROIC. The SWIR assembly has 3 spectral bands combined on a single detector respectively [3].…”

Section: Detector Specificitiesmentioning

confidence: 99%

Copernicus Sentinel-2A Calibration and Products Validation Status

et al. 2017

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As part of the Copernicus programme of the European Commission (EC), the European Space Agency (ESA) has developed and is currently operating the Sentinel-2 mission that is acquiring high spatial resolution optical imagery. This article provides a description of the calibration activities and the status of the mission products validation activities after one year in orbit. Measured performances, from the validation activities, cover both Top-Of-Atmosphere (TOA) and Bottom-Of-Atmosphere (BOA) products. The presented results show the good quality of the mission products both in terms of radiometry and geometry and provide an overview on next mission steps related to data quality aspects.

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“…For this study, we used Sentinel-2 optical imagery, which monitors the land surface conditions and serves for producing land-cover and land-change detection maps [17]. The optical sensors (Multi-Spectral Instrument [9]) sense 13 spectral bands (B1-B13) ranging in spatial resolution from 10𝑚 to 60𝑚. Out of the several processing levels in which the Sentinel-2 imagery is distributed, Level-1C and Level-2A are freely available to public.…”

Section: Creating Imagelet Feature Vectors From Satellite Imagesmentioning

confidence: 99%

Jane Jacobs in the Sky: Predicting Urban Vitality with Open Satellite Data

Šćepanović,

Joglekar,

Law

et al. 2021

Preprint

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The presence of people in an urban area throughout the day -often called 'urban vitality' -is one of the qualities world-class cities aspire to the most, yet it is one of the hardest to achieve. Back in the 1970s, Jane Jacobs theorized urban vitality and found that there are four conditions required for the promotion of life in cities: diversity of land use, small block sizes, the mix of economic activities, and concentration of people. To build proxies for those four conditions and ultimately test Jane Jacobs's theory at scale, researchers have had to collect both private and public data from a variety of sources, and that took decades. Here we propose the use of one single source of data, which happens to be publicly available: Sentinel-2 satellite imagery. In particular, since the first two conditions (diversity of land use and small block sizes) are visible to the naked eye from satellite imagery, we tested whether we could automatically extract them with a state-of-the-art deep-learning framework and whether, in the end, the extracted features could predict vitality. In six Italian cities for which we had call data records, we found that our framework is able to explain on average 55% of the variance in urban vitality extracted from those records.

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Design and development of the Sentinel-2 Multi Spectral Instrument and satellite system

Cited by 5 publications

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Observations and Recommendations for the Calibration of Landsat 8 OLI and Sentinel 2 MSI for Improved Data Interoperability

Observations and Recommendations for the Calibration of Landsat 8 OLI and Sentinel 2 MSI for Improved Data Interoperability

Copernicus Sentinel-2A Calibration and Products Validation Status

Jane Jacobs in the Sky: Predicting Urban Vitality with Open Satellite Data

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