Results 31 to 40 of about 793 (204)

GIS‐Based Remote Sensing Image Information Analysis of the South Atlantic Ecological Environment and Diversity of Deep‐Sea Microorganism with Antifungal Effects

Advances in Mathematical Physics, Volume 2022, Issue 1, 2022., 2022
This paper uses the GIS technology to collect location and geographic information of the South Atlantic ecological environment and then uses the remote sensing image technology to extract and analyse the collected information to provide a strong basis for maintaining a healthy marine ecological environment. Based on multitemporal remote sensing images,
Jingjing Xu, Peisheng Yan, Miaochao Chen
wiley   +1 more source

Atmospheric Correction of GOCI Using Quasi-Synchronous VIIRS Data in Highly Turbid Coastal Waters

Remote Sensing, 2019
The Geostationary Ocean Color Imager (GOCI) sensor, with high temporal and spatial resolution (eight images per day at an interval of 1 hour, 500 m), is the world’s first geostationary ocean color satellite sensor. GOCI provides good data for ocean
Jie Wu, Chuqun Chen, Sravanthi Nukapothula   +2 more
doaj   +1 more source

Evaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay)

Remote Sensing, 2021
Validation of remote-sensing reflectance (Rrs) products is necessary for the quantitative application of ocean color satellite data. While validation of Rrs products has been performed in low to moderate turbidity waters, their performance in highly ...
Yuzhuang Xu, Xianqiang He, Yan Bai, Difeng Wang, Qiankun Zhu, Xiaosong Ding   +5 more
doaj   +1 more source

Assessing Net Growth of Phytoplankton Biomass on Hourly to Annual Time Scales Using the Geostationary Ocean Color Instrument

Geophysical Research Letters, Volume 48, Issue 23, 16 December 2021., 2021
Abstract Questions of whether diurnal changes in carbon fixation affect the global carbon budget cannot be answered using the present generation of polar orbiting ocean color sensors that can only retrieve one image daily. Here, we present novel satellite‐derived indices of chlorophyll‐based production based on the Geostationary Ocean Color Imager ...
Joseph E. Salisbury, Bror F. Jönsson, Antonio Mannino, Wonkook Kim, Joaquim I. Goes, Jin‐Yong Choi, Javier A. Concha   +6 more
wiley   +1 more source

Geometric accuracy analysis of the Geostationary Ocean Color Imager (GOCI) Level 1B (L1B) product

Optics Express, 2020
The Geostationary Ocean Color Imager (GOCI) has been used for many remote sensing applications to observe and monitor the ocean color of East Asia around the Korean Peninsula. However, to date, its geometric accuracy has not been thoroughly investigated; the only studies conducted so far have focused on verifying its radiometric quality.
Jaehoon, Jeong, Heejeong, Han, Youngje, Park   +2 more
openaire   +2 more sources

Quasi‐Global Maps of Daily Aerosol Optical Depth From a Ring of Five Geostationary Meteorological Satellites Using AERUS‐GEO

Journal of Geophysical Research: Atmospheres, Volume 126, Issue 20, 27 October 2021., 2021
Abstract Geostationary meteorological satellites are recently receiving a great deal of attention from the aerosol remote sensing community due to their increasingly advanced performances including their ability to acquire multiple views of the Earth per day.
Xavier Ceamanos, Bruno Six, Jérôme Riedi   +2 more
wiley   +1 more source

Simulation of Sedimentation in Lake Taihu with Geostationary Satellite Ocean Color Data

Remote Sensing, 2019
In this study, the goal is to estimate the sedimentation on the bottom bed of Lake Taihu using numerical simulation combined with geostationary satellite ocean color data.
Anpeng He, Xianqiang He, Yan Bai, Qiankun Zhu, Fang Gong, Haiqing Huang, Delu Pan   +6 more
doaj   +1 more source

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

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 satellite observations and in situ visibility data for three Korean islands.
Donghee Kim, Myung-Sook Park, Young-Je Park, Wonkook Kim   +3 more
openaire   +2 more sources

Detection and Tracking of Chattonella spp. and Skeletonema spp. Blooms Using Geostationary Ocean Color Imager (GOCI) in Ariake Sea, Japan

Journal of Geophysical Research: Oceans, Volume 126, Issue 7, July 2021., 2021
Abstract Algal blooms dominated by the raphidophyte Chattonella spp. and diatom Skeletonema spp. are a regular summer‐time phenomenon in the Ariake Sea (Japan). Given its high‐temporal frequency, the Geostationary Ocean Color Imager (GOCI) affords us the extraordinary ability to investigate short‐temporal scale dynamic of these blooms.
Chi Feng, Joji Ishizaka, Katsuya Saitoh, Takayuki Mine, Zhenjia Zhou   +4 more
wiley   +1 more source

Evaluation of Stray Light Correction for GOCI Remote Sensing Reflectance Using in Situ Measurements

Remote Sensing, 2016
The Geostationary Ocean Color Imager (GOCI) is the world’s first ocean color sensor in geostationary orbit. Although the GOCI has shown excellent radiometric performance with little long-term radiometric degradation and a high signal-to-noise ratio ...
Wonkook Kim, Jeong-Eon Moon, Jae-Hyun Ahn, Young-Je Park   +3 more
doaj   +1 more source