Results 11 to 20 of about 1,268 (218)

Retrievals of Chlorophyll-a from GOCI and GOCI-II Data in Optically Complex Lakes

Remote Sensing, 2023
The chlorophyll-a (Chla) concentration is a key parameter to evaluate the eutrophication conditions of water, which is very important for monitoring algal blooms.
Yuyu Guo, Xiaoqi Wei, Zehui Huang, Hanhan Li, Ronghua Ma, Zhigang Cao, Ming Shen, Kun Xue   +7 more
doaj   +2 more sources

Estimating GOCI daily PAR and validation

Remote Sensing of the Open and Coastal Ocean and Inland Waters, 2018
Photosynthesis available radiation (PAR) is the most important source for primary production at the ocean. In these days, satellite remote-sensing has an advantage in terms of cost-effectiveness and spatio-temporal resolutions for observing global ...
황득재, 유주형, Robert Frouin, 최종국   +3 more
core   +2 more sources

Progress in Current Research and Applications of the Geostationary Ocean Color Imager Series (GOCI and GOCI-II): A Bibliometric Analysis

Korean Journal of Remote Sensing
Since the launch of the Geostationary Ocean Color Imager (GOCI), the world’s first geostationary ocean color satellite, in 2010, and its successor, GOCI-II, in 2020, these satellites have made substantial contributions to advancing ocean color monitoring
김민주, 유주형, 이동욱
core   +2 more sources

Hypothetical Product Generation of Geostationary Ocean Color Imager Bands Over the Yellow Sea and Bohai Sea Using Deep Learning Technique

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
This study presents a deep learning model, using the conditional generative adversarial nets (CGAN) technique, that can produce daytime visible (VIS) band information, mimicking a narrow band sensor, by combining VIS and infrared (IR) broadband ...
Sumin Ryu, Sungwook Hong
doaj   +1 more source

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign [PDF]

Atmospheric Measurement Techniques, 2016
The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit.
M. Choi, J. Kim, J. Lee, M. Kim, Y.-J. Park, U. Jeong, W. Kim, H. Hong, B. Holben, T. F. Eck, C. H. Song, J.-H. Lim, C.-K. Song   +12 more
doaj   +1 more source

Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing Data

Remote Sensing, 2021
High temporal resolution aerosol optical depth (AOD) products are very important for the studies of atmospheric environment and climate change. Geostationary Ocean Color Imager (GOCI) is a suitable data source for AOD retrieval, as it can monitor hourly ...
Lijuan Chen, Ying Fei, Ren Wang, Peng Fang, Jiamei Han, Yong Zha   +5 more
doaj   +1 more source

Characterization of ocean color retrievals and ocean diurnal variations using the Geostationary Ocean Color Imager (GOCI)

International Journal of Applied Earth Observations and Geoinformation, 2023
Using measurements from the Geostationary Ocean Color Imager (GOCI) on the Communication, Ocean, and Meteorological Satellite (COMS), we characterize and quantify some advantages and applications of the satellite geostationary measurements, compared with
Menghua Wang, Wei Shi, Lide Jiang
doaj   +1 more source

Continuous mapping of fine particulate matter (PM_2.5) 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, S. Zhai, J. Kim, J. Kim, J.-H. Koo, S. Lee, M. Bae, S. Kim, H. Liao, D. J. Jacob   +9 more
doaj   +1 more source

Geostationary Ocean Color Imager (GOCI) Marine Fog Detection in Combination with Himawari-8 Based on the Decision Tree

Remote Sensing, 2020
Geostationary Ocean Color Imager (GOCI) observations are applied to marine fog (MF) detection in combination with Himawari-8 data based on the decision tree (DT) approach. Training and validation of the DT algorithm were conducted using match-ups between
Donghee Kim, Myung-Sook Park, Young-Je Park, Wonkook Kim   +3 more
doaj   +1 more source

Estimating ground-level PM_2.5 in eastern China using aerosol optical depth determined from the GOCI satellite instrument [PDF]

Atmospheric Chemistry and Physics, 2015
We determine and interpret fine particulate matter (PM2.5) concentrations in eastern China for January to December 2013 at a horizontal resolution of 6 km from aerosol optical depth (AOD) retrieved from the Korean geostationary ocean color imager (GOCI ...
J.-W. Xu, R. V. Martin, A. van Donkelaar, J. Kim, M. Choi, Q. Zhang, G. Geng, Y. Liu, Z. Ma, L. Huang, Y. Wang, H. Chen, H. Che, P. Lin, N. Lin   +14 more
doaj   +1 more source