China
Africa
Explore chapters and articles related to this topic
Remote Sensing Technologies for Multiscale Hydrological Studies: Advances and Perspectives
Published in Prasad S. Thenkabail, Remote Sensing Handbook, 2015
Sadiq I. Khan, Ni-Bin Chang, Yang Hong, Xianwu Xue, Yu Zhang
The 22-channel VIIRS will collect calibrated VIS/IR radiances to produce about 20 different Environmental Data Records including imagery, cloud and aerosol properties, albedo, land surface type, vegetation index, ocean color, and land and sea surface temperature to fulfill functions similar to what the Moderate Resolution Imaging Spectroradiometer (MODIS) does for National Aeronautics and Space Administration’s (NASA) EOS Terra and Aqua missions. VIIRS will provide complete daily global coverage over the VIS, short/medium IR, and longwave IR spectrum at horizontal spatial resolutions of 370 and 740 m at nadir. VIIRS will image at a near constant horizontal resolution across its ~3000 km swath (i.e., from 370 at nadir to ~800 m at edge of scan), a significant improvement over NOAA’s Advanced Very High Resolution Radiometer and NASA’s MODIS instruments.
Satellite Remote Sensing of Floods for Disaster Response Assistance
Published in George P. Petropoulos, Tanvir Islam, Remote Sensing of Hydrometeorological Hazards, 2017
The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is one of the five major Earth observation (EO) instruments onboard the National Oceanic and Atmospheric Administration’s (NOAA’s) S-NPP and JPSS satellites, essentially a continuation of NOAA’s AVHRR legacy sensors. With a very large swath width of 3060 km, it provides full daily coverage, both in the day and night sides of the Earth. The VIIRS has 22 spectral bands, including 16 moderate spatial resolution bands at 750 m pixel spacing at nadir, 5 imaging resolution bands at 375 m at nadir, and 1 panchromatic band with 750 m spatial resolution.
A Study of After-Effects of Kerala Floods Using VIIRS-OLS Nighttime Light Data
Published in Rakhee Kulshrestha, Chandra Shekhar, Madhu Jain, Srinivas R. Chakravarthy, Mathematical Modeling and Computation of Real-Time Problems, 2021
Remote sensing is a widely used technique for the study of the Earth’s surface features. Nighttime light imagery forms a useful data set in remote sensing. It is an essential dataset for the study of human activities on Earth and their effects. Such datasets are also found to be of great importance in the study of the atmosphere and other natural processes. A few common examples are the detection and monitoring of city lights, fires, dust storms, volcanoes, gas flares and population/economic geography (Chuvieco 2016). As the name suggests, nighttime light imagery data is collected during the night. It usually contains two types of features: self-illuminating features and moon-illuminated features. Some examples of self-illuminating features include gas flares, forest fires, human-caused disasters, volcanic lava and bioluminescence, whereas moonlight illuminating features include snow cover, sea ice and volcanic ash along with various surface features such as mountains, deserts, rivers and moon glint. Another source of illumination for the clouds can be airglow. It is the luminosity occurring due to chemical reactions in the upper atmosphere. Nighttime visible imaging was initiated by the Defense Meteorological Satellite Program – Operational Linescan System (DMSP-OLS) in the 1960s, which was the only source of visible nighttime images until the launch of Suomi National Polar-Orbiting Partnership – Visible Infrared Imaging Radiometer Suite (SNPP-VIIRS) in 2011. The VIIRS instrument collects visible and infrared imagery and global observations of the land, atmosphere, cryosphere and oceans. In Doll (2008) and Elvidge et al. (2017), a detailed explanation of the generation and usage of the Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS-DNB) satellite data is available.
Estimating PM2.5 concentrations in a central region of China using a three-stage model
Published in International Journal of Digital Earth, 2023
Yue Jing, Long Pan, Yanling Sun
VIIRS is a sensor mounted on the National Polar-orbiting Operational Environmental Satellite System Preparatory Pro (NPP). The overpass time of the NPP satellite was 13:30 pm locally. The instrument performance and bands of the VIIRS were adjusted and improved to be above those of the MODIS (Bian et al. 2018). The AOD inversion algorithm of the VIIRS is similar to the MODIS DT algorithm, but it differs in terms of spectral bandwidth, wavelengths, and calibration algorithms (Jackson et al. 2013; Choi et al. 2019). The VIIRS can generate a set of aerosol parameters (including 550 nm AOD) (Liu et al. 2014). The 6 km AOD product was released by the VIIRS aerosol team after the data were further processed (Jackson et al. 2013). This dataset contained four types of data quality products: none, low-quality, medium-quality, and high-quality data (quality flag = 0, 1, 2, and 3). Yao et al. (2018) showed that medium-quality data could not only meet the estimation accuracy of PM2.5, but also ensure sufficient spatial coverage in China. In this study, a 6 km AOD at 550 nm with medium-quality data was chosen. The daily product was downloaded from NOAA (www.class.noaa.gov/) and a total of 100 NetCDF(.nc) files were collected.
A time series decomposition approach to detect coal fires in parts of the Gondwana coalfields of India from VIIRS data
Published in Journal of Spatial Science, 2023
Ritesh Mujawdiya, R. S. Chatterjee, Dheeraj Kumar
VIIRS onboard the SNPP satellite scans the earth’s surface in 22 spectral bands ranging from 412 nm to 12 µm. VIIRS observes the earth’s surface in seven bands in the thermal infrared region of the electromagnetic spectrum. Of the seven bands, five have 750 m spatial resolution, and two have 375 m spatial resolution. The main data source of this study is the VIIRS VNP21A2 8-day LST product. The VNP21A2 LST product is produced at 1 km spatial resolution using the Temperature Emissivity Separation (TES) method, which uses three moderate resolution thermal infrared bands at 750 m spatial resolution, namely M14, M15, and M16 (Islam et al. 2017). The wavelength ranges of these thermal bands are given in Table 1. The data used in this research were collected from a web user interface of level-1 and atmosphere archive and distribution system (LAADS) distributed active archive centre for the period January 2013 to December 2019.
Development of S-NPP VIIRS global surface type classification map using support vector machines
Published in International Journal of Digital Earth, 2018
Rui Zhang, Chengquan Huang, Xiwu Zhan, Huiran Jin, Xiao-Peng Song
As the Earth Observing System (EOS) satellites (Terra and Aqua) age, the MODIS sensors onboard the EOS satellites will gradually retire over the next several years, and their functionalities will be taken over by the next generation of Earth-observing systems. Collaboratively developed by the National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA), the Joint Polar Satellite System (JPSS) is the United States’ next generation of polar-orbiting environmental satellites; it represents significant technological and scientific advancements in Earth observation capability, and aims for severe weather prediction and environmental monitoring (NOAA 2016a). The first satellite, Suomi National Polar-orbiting Partnership (S-NPP) in the JPSS program was launched in October 2011, and the JPSS-1 satellite will be launched in early 2017 (NOAA 2016a). The Visible Infrared Imaging Radiometer Suite (VIIRS), which is onboard S-NPP and planned for future JPSS satellites, provides data continuity for the current polar-orbiting satellite data record obtained from NOAA’s AVHRR and NASA’s MODIS sensors.