Special Issue "Advances in VIIRS Data"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 August 2021).

Special Issue Editors

Dr. Feng Chi Hsu
E-Mail Website
Guest Editor
Earth Observation Group, the Payne Institute for Public Policy, Colorado School of Mines, 1600 Jackson St, Golden, GO 80401, USA
Interests: nighttime remote sensing; space observed socio-economic activity
Special Issues, Collections and Topics in MDPI journals
Dr. Wenhui Wang
E-Mail Website
Guest Editor
CMNS-Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, MD 20740, USA
Interests: satellite instrument calibration and validation; climate data records; surface radiation budget

Special Issue Information

Dear Colleagues, 

The flagship of the US polar orbiting, earth observation satellite, with VIIRS as its primary payload, is receiving more attention than ever. Given its advanced design, it has improved the quality of older applications using visible and infrared bands as well as prompted new ideas and applications, bringing amazing new insights and inspiring us in new ways of exploration.

In this Special Issue, we welcome submissions that provide the community with advancements on all aspects related to VIIRS, including, but not limited to:

  • VIIRS data quality examination and improvement;
  • VIIRS data comparison and calibration between satellites;
  • Comparison of product generation and quality of VIIRS and other sensors
  • Legacy product continuity and improvement with VIIRS;
  • New products developed with VIIRS;
  • Anthropogenic activities observed by VIIRS;
  • Applications using VIIRS or VIIRS-derived products with other sources of data;
  • Product of temporal series to track changes

Dr. Feng Chi Hsu
Dr. Wenhui Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • VIIRS
  • JPSS
  • Ocean color
  • Chlorophyll-II
  • Land surface temperature
  • Land cover/usage
  • Sensor calibration and correction
  • Aerosol
  • Surface feature detection
  • Hot source detection/mapping
  • Time series
  • GDP
  • Power usage/outage
  • Population
  • Urban development

Published Papers (3 papers)

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Research

Article
Improved NOAA-20 Visible Infrared Imaging Radiometer Suite Day/Night Band Image Quality by Upgraded Gain Calibration
Remote Sens. 2021, 13(13), 2509; https://doi.org/10.3390/rs13132509 - 26 Jun 2021
Viewed by 793
Abstract
Due to complex radiometric calibration, the imagery collected by the Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar Partnership (Suomi-NPP) and the NOAA-20 follow-on satellite is subject to artifacts such as striping, which eventually affect [...] Read more.
Due to complex radiometric calibration, the imagery collected by the Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar Partnership (Suomi-NPP) and the NOAA-20 follow-on satellite is subject to artifacts such as striping, which eventually affect Earth remote sensing applications. Through comprehensive analysis using the NOAA-20 VIIRS DNB prelaunch-test and on-orbit data, it is revealed that the striping results from flaws in the calibration process. In particular, a discrepancy between the low-gain stage (LGS) Earth view (EV) gain and the onboard calibrator solar diffuser view gain makes the operational LGS gain coefficients of a few aggregation modes and detectors biased. Detector nonlinearity at low radiance level also induces errors to the mid-gain stage (MGS) and high-gain stage (HGS) gain through the biased gain ratios. These systematic errors are corrected by scaling the operational LGS gains using the factors derived from the NOAA-20 VIIRS DNB prelaunch test data and by adopting linear regression for evaluating the gain ratios. Striping in the NOAA-20 VIIRS DNB imagery is visibly reduced after the upgraded gain calibration process was implemented in the operational calibration. Full article
(This article belongs to the Special Issue Advances in VIIRS Data)
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Article
The Annual Cycling of Nighttime Lights in India
Remote Sens. 2021, 13(6), 1199; https://doi.org/10.3390/rs13061199 - 21 Mar 2021
Cited by 1 | Viewed by 947
Abstract
India is known to have unstable power supply, and many locations show an annual cycle in VIIRS Nighttime Light (VNL). In this study, autocorrelation function (ACF) analysis is used to identify the annual cycling in VNL. Two fundamentally different classification techniques are proposed [...] Read more.
India is known to have unstable power supply, and many locations show an annual cycle in VIIRS Nighttime Light (VNL). In this study, autocorrelation function (ACF) analysis is used to identify the annual cycling in VNL. Two fundamentally different classification techniques are proposed to classify the ACF profile into one of the three arch types, i.e., acyclic, single peak, and dual peak. The results from the two classification techniques are closely compared to verify their output. This analysis is carried out for the entire territory of India in 15 arc second grid cells. The power stability data acquired from the India Human Development Survey (IHDS) and the Electricity Supply Monitoring Initiative (ESMI) are used to verify their relationship to the annual cycling of VNL. To further aide the analysis, land use/land class are accounted for by data from the India National Remote Sensing Center (NRSC). As a result, the contribution of power stability to VNL annual cycling in India is inconclusive due to the limitation of power stability data. Furthermore, other potential factors should be further examined. Full article
(This article belongs to the Special Issue Advances in VIIRS Data)
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Article
Indicators of Electric Power Instability from Satellite Observed Nighttime Lights
Remote Sens. 2020, 12(19), 3194; https://doi.org/10.3390/rs12193194 - 30 Sep 2020
Cited by 4 | Viewed by 1682
Abstract
Electric power services are fundamental to prosperity and economic development. Disruptions in the electricity power service can range from minutes to days. Such events are common in many developing economies, where the power generation and delivery infrastructure is often insufficient to meet demand [...] Read more.
Electric power services are fundamental to prosperity and economic development. Disruptions in the electricity power service can range from minutes to days. Such events are common in many developing economies, where the power generation and delivery infrastructure is often insufficient to meet demand and operational challenges. Yet, despite the large impacts, poor data availability has meant that relatively little is known about the spatial and temporal patterns of electric power reliability. Here, we explore the expressions of electric power instability recorded in temporal profiles of satellite observed surface lighting collected by the Visible Infrared Imaging Radiometer Suite (VIIRS) low light imaging day/night band (DNB). The nightly temporal profiles span from 2012 through to mid-2020 and contain more than 3000 observations, each from a total of 16 test sites from Africa, Asia, and North America. We present our findings in terms of various novel indicators. The preprocessing steps included radiometric adjustments designed to reduce variance due to the view angle and lunar illumination differences. The residual variance after the radiometric adjustments suggests the presence of a previously unidentified source of variability in the DNB observations of surface lighting. We believe that the short dwell time of the DNB pixel collections results in the vast under-sampling of the alternating current lighting flicker cycles. We tested 12 separate indices and looked for evidence of power instability. The key characteristic of lights in cities with developing electric power services is that they are quite dim, typically 5 to 10 times dimmer for the same population level as in Organization for Economic Co-operation and Development (OECD) countries. In fact, the radiances for developing cities are just slightly above the detection limit, in the range of 1 to 10 nanowatts. The clearest indicator for power loss is the percent outage. Indicators for supply adequacy include the radiance per person and the percent of population with detectable lights. The best indicator for load-shedding is annual cycling, which was found in more than half of the grid cells in two Northern India cities. Cities with frequent upward or downward radiance spikes can have anomalously high levels of variance, skew, and kurtosis. A final observation is that, barring war or catastrophic events, the year-on-year changes in lighting are quite small. Most cities are either largely stable over time, or are gradually increasing in indices such as the mean, variance, and lift, indicating a trajectory that proceeds across multiple years. Full article
(This article belongs to the Special Issue Advances in VIIRS Data)
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