Continuous mapping of fine particulate matter (PM2.5) air quality in East Asia at daily 6 × 6 km2 resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data [PDF]
Atmospheric Measurement Techniques, 2022 We use 2011–2019 aerosol optical depth (AOD) observations from the Geostationary Ocean Color Imager (GOCI) instrument over East Asia to infer 24 h daily surface fine particulate matter (PM2.5) concentrations at a continuous 6 × 6 km2 resolution over ...
D. C. Pendergrass +9 more
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Two new species of the genus Cryptopimpla Taschenberg (Hymenoptera, Ichneumonidae, Banchinae) with an updated key to African species [PDF]
Journal of Hymenoptera Research, 2023 A revised illustrated key to Afrotropical species of the genus Cryptopimpla Taschenberg is provided, with the inclusion of two new South African species, C. orenji Reynolds & van Noort, sp. nov. and C. hoerikwagga Reynolds & van Noort, sp.
Terry Reynolds, Simon van Noort
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GOCI data processing and ocean applications [PDF]
Ocean Science Journal, 2012 GOCI, the world’s first geostationary ocean color sensor, has been developed with the purpose of monitoring the marine environment and providing a quick and timely warning of marine dangers. It takes eight times a day the images of the Northeast Asian region while the polar orbiters have only a 2-3 day revisit occasion.
Joo-Hyung Ryu, Joji Ishizaka
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A MULTI-TEMPORAL APPROACH FOR DETECTING SNOW COVER AREA USING GEOSTATIONARY IMAGERY DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 In this study, we attempt to detect snow cover area using multi-temporal geostationary satellite imagery based on the difference of spectral and temporal characteristics between snow and clouds. The snow detection method is based on sequential processing
H.-S. Lee, K.-S. Lee
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AUTOMATED MOSAICKING OF GEOSTATIONARY OCEAN COLOR IMAGER BY COMBINATION OF SPATIAL AND FREQUENCY MATCHING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 In general, image mosaicking is a useful and important processing for handling images with narrow field of view. It is being used widely for images from commercial cameras as well as from aerial and satellite cameras. For mosaicking images with geometric
H. G. Kim, J. H. Son, T. Kim
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Improved Vegetation Profiles with GOCI Imagery Using Optimized BRDF Composite [PDF]
Journal of Sensors, 2016 The purpose of this study was to optimize a composite method for the Geostationary Ocean Color Imager (GOCI), which is the first geostationary ocean color sensor in the world. Before interpreting the sensitivity of each composite with ground measurements, we evaluated the accuracy of bidirectional reflectance distribution function (BRDF) performance by
Sang-Il Kim +3 more
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Journal of Marine Science and Engineering, 2023 The Geostationary Ocean Color Imager (GOCI) provided images at hourly intervals up to 8 times per day with a spatial resolution of 500 m from 2011 to 2021.
Yixin Yang +6 more
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Fluorescence Line Height Extraction Algorithm for the Geostationary Ocean Color Imager
Remote Sensing, 2022 Chlorophyll fluorescence is an important indicator of the physiological state of phytoplankton in water bodies. The new generation of ocean color satellite remote sensors usually sets fluorescence bands to detect the phytoplankton fluorescence line ...
Min Zhao +5 more
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Improving air quality forecasting with the assimilation of GOCI aerosol optical depth (AOD) retrievals during the KORUS-AQ period [PDF]
Atmospheric Chemistry and Physics, 2020 The Korean Geostationary Ocean Color Imager (GOCI) satellite has monitored the East Asian region in high temporal (e.g., hourly) and spatial resolution (e.g., 6 km) every day for the last decade, providing unprecedented information on air ...
S. Ha, Z. Liu, W. Sun, Y. Lee, L. Chang
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An Improved Cloud Masking Method for GOCI Data over Turbid Coastal Waters [PDF]
Remote Sensing, 2021 Clouds severely hinder the radiative transmission of visible light; thus, correctly masking cloudy and non-cloudy pixels is a preliminary step in processing ocean color remote sensing data. However, cloud masking over turbid waters is prone to misjudgment, leading to loss of non-cloudy pixel data. This research proposes an improved cloud masking method
Shiming Lu +6 more
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