Generation of High-Resolution Blending Data Using Gridded Visibility Data and GK2A Fog Product

In this study, 10 min and 2 km high-resolution blended fog data (HRBFD) were generated using grid visibility data (GVD) and data from a GK2A (GEO-KOMPSAT-2A) fog product (GKFP) in Korea. As the blending method, the decision tree method (DTM) was used to consider the different characteristics of the...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2024-07, Vol.16 (13), p.2350
Main Authors: Suh, Myoung-Seok, Han, Ji-Hye, Yu, Ha-Yeong, Kang, Tae-Ho
Format: Article
Language:English
Subjects:
Accuracy
Altitude
Artificial satellites in remote sensing
Blending
Coasts
Data fusion
Data smoothing
Datasets
Decision tree
Decision trees
Fog
GK2A fog product
grid data
High resolution
Identification and classification
Image quality
Measurement
Meteorological satellites
Methods
Mountain regions
Mountainous areas
Precipitation
Technology application
Variables
Visibility
visibility data
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Summary:In this study, 10 min and 2 km high-resolution blended fog data (HRBFD) were generated using grid visibility data (GVD) and data from a GK2A (GEO-KOMPSAT-2A) fog product (GKFP) in Korea. As the blending method, the decision tree method (DTM) was used to consider the different characteristics of the two-input data (categorical data and continuity data). The blending of the two datasets was performed according to the presence or absence of the input data and considered the spatial representation of the GVD and the accuracy of the GKFP. The quality of the HRBFD was evaluated through visual comparison using GVD, GKFP, and visible images of the GK2A. The HRBFD seems to have partly solved the problem of fog detection in areas where visibility meters are rare or absent through the detection of fog occurring in the sea or mountain areas. In addition, the critical problem of the GKFP, which has limitations in detecting fog occurring under clouds, has been mostly overcome. Using the DTM, we generated 23 fog cases of 10 min and 2 km HRBFD. The results confirmed that detailed spatiotemporal characteristics of fog in Korea can be analyzed if such HRBFD is generated for a long time.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs16132350