2016
DOI: 10.1080/01431161.2016.1225177
|View full text |Cite
|
Sign up to set email alerts
|

Cloud motion in the GOCI/COMS ocean colour data

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
3
0

Year Published

2017
2017
2023
2023

Publication Types

Select...
6

Relationship

0
6

Authors

Journals

citations
Cited by 6 publications
(3 citation statements)
references
References 12 publications
0
3
0
Order By: Relevance
“…During the measurement process, the pulsed neutron tube continuously emits a high-energy fast neutron pulse to activate the oxygen element in the fluid. The flow rate of the fluid can be determined based on the count rate measured by the instrument and the characteristic exponential decay rate [4].…”
Section: State Of the Artmentioning
confidence: 99%
“…During the measurement process, the pulsed neutron tube continuously emits a high-energy fast neutron pulse to activate the oxygen element in the fluid. The flow rate of the fluid can be determined based on the count rate measured by the instrument and the characteristic exponential decay rate [4].…”
Section: State Of the Artmentioning
confidence: 99%
“…Hence, the multi-spectral displacement can be used as a feature to detect clouds or moving objects. This idea has been exploited for geostationary satellites, where spectral bands are acquired at slightly different times [3], [4], [5], and very high and moderate spatial resolution satellites, where a parallax angle between pan-chromatic and multi-spectral bands exist [6], [7], [8], [9], [10].…”
Section: Introductionmentioning
confidence: 99%
“…Obviously, improving AMV spatial and temporal resolution is essential to tracking cloud features in a TC system, especially in the high-speed zone of the eyewall [37], [41], [43], [44]. Since the 1960s, when cloud motion was manually identified and measured initially [45], various objective methods were developed to extract AMVs, such as block matching [36], [46]- [48], object feature matching [49]- [51], and optical flow algorithms [52]- [54].…”
mentioning
confidence: 99%