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- VIIRS - an overview | ScienceDirect Topics
VIIRS is a key instrument for satellite missions like S-NPP and JPSS, designed to enhance and expand the capabilities of existing research and operational instruments It consists of an electronics module and an optomechanical module, and is used for making observations in various spectral bands to capture data about Earth's surface and atmosphere From: Comprehensive Remote Sensing, 2018
- Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical . . .
This study presents a comprehensive evaluation of eight aerosol optical depth (AOD) products from the latest MODIS C6 1 DT, DB and DTB, MISR V23, and …
- Quantitative Evaluation of Urban Expansion using NPP-VIIRS Nighttime . . .
The limitation of the overflow effect for NPP-VIIRS NTL data hampers the wide application of these data for the accurate extraction of urban expansion information In this study, we corrected the deficiency of NPP-VIIRS NTL data by combining the advantages of NTL and Landsat spectral data
- An improved approach for monitoring urban built-up areas by combining . . .
The blooming effects of NPP-VIIRS NTL data—especially in water bodies and vegetated regions of urban built-up areas—hinder the wide use of NPP-VIIRS data for accurately extracting urban land information
- Improvement of land surface phenology monitoring by fusing VIIRS . . .
Land Surface Phenology (LSP) has been widely derived from polar-orbiting satellite observations to characterize terrestrial vegetation dynamics Howev…
- Evaluation of the VIIRS BRDF, Albedo and NBAR products suite and an . . .
The VIIRS onboard the Suomi-NPP (National Polar-orbiting Partnership) satellite was launched on October 28, 2011, with the aim of building on the MODIS legacy and providing a continuous data record into the future (Román et al , 2011)
- Improved estimation of fire particulate emissions using a combination . . .
Improved estimation of fire particulate emissions using a combination of VIIRS and AHI data for Indonesia during 2015–2020
- A VIIRS direct broadcast algorithm for rapid response mapping of . . .
The VIIRS-DB algorithm was late (Δt VIIRS > 0 day) in identifying nearly 40% of burned grid points that were evaluated Possible reasons for a positive time lag include obscuration by clouds and or heavy smoke or insufficient fire intensity at the time of the VIIRS overpass
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