Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Junhwa Chi"'
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 125, Iss , Pp 103583- (2023)
Remote sensing is an invaluable tool for monitoring the rapid changes in Arctic vegetation distribution caused by global warming. Although hyperspectral data consisting of contiguous spectral bands enables the quantitative analysis of remote sensing
Externí odkaz:
https://doaj.org/article/418262afa7c8470fb04cf58ff36b341a
Autor:
Jae‐In Kim, Junhwa Chi, Ali Masjedi, John Evan Flatt, Melba M. Crawford, Ayman F. Habib, Joohan Lee, Hyun‐Cheol Kim
Publikováno v:
Geoscience Data Journal, Vol 9, Iss 2, Pp 221-234 (2022)
Abstract Hyperspectral data are gaining popularity in remote sensing and signal processing communities because of the increased spectral information relative to multispectral data. Several airborne and spaceborne hyperspectral datasets are publicly a
Externí odkaz:
https://doaj.org/article/cee4c7e1d0c94bba97c827a79d29bda7
Autor:
Junhwa Chi, Jae-In Kim, Sungjae Lee, Yongsik Jeong, Hyun-Cheol Kim, Joohan Lee, Changhyun Chung
Publikováno v:
Drones, Vol 7, Iss 7, p 411 (2023)
Unmanned aerial vehicles (UAVs), also known as drones, are a cost-effective alternative to traditional surveying methods, and they can be used to collect geospatial data over inaccessible or hard-to-reach locations. UAV-integrated miniaturized remote
Externí odkaz:
https://doaj.org/article/c1f7a9614cf54668bbbe3fdf039ac538
Autor:
Junhwa Chi, Hyun-Cheol Kim
Publikováno v:
GIScience & Remote Sensing, Vol 58, Iss 6, Pp 812-830 (2021)
Recently, measurement of sea ice thickness (SIT) has received increasing attention due to the importance of thinning ice in the context of global warming. Although altimeter sensors onboard satellite missions enable continuous SIT measurements over l
Externí odkaz:
https://doaj.org/article/d9a6a10dad474ddc9b2c538a3a5a48cd
Publikováno v:
Remote Sensing, Vol 13, Iss 17, p 3413 (2021)
Arctic sea ice plays a significant role in climate systems, and its prediction is important for coping with global warming. Artificial intelligence (AI) has gained recent attention in various disciplines with the increasing use of big data. In recent
Externí odkaz:
https://doaj.org/article/43272f774c2d45918f18dc057d75fcb5
Publikováno v:
Remote Sensing, Vol 13, Iss 13, p 2470 (2021)
Spectral information is a proxy for understanding the characteristics of ground targets without a potentially disruptive contact. A spectral library is a collection of this information and serves as reference data in remote sensing analyses. Although
Externí odkaz:
https://doaj.org/article/0a4ab155d6664257a098143395c050f4
Publikováno v:
Remote Sensing, Vol 13, Iss 13, p 2490 (2021)
The spatial patterns of species richness can be used as indicators for conservation and restoration, but data problems, including the lack of species surveys and geographical data gaps, are obstacles to mapping species richness across large areas. La
Externí odkaz:
https://doaj.org/article/a82fd57baa534b52af703c8ebd587ee4
Publikováno v:
Remote Sensing, Vol 13, Iss 11, p 2118 (2021)
Recently, the mapping industry has been focusing on the possibility of large-scale mapping from unmanned aerial vehicles (UAVs) owing to advantages such as easy operation and cost reduction. In order to produce large-scale maps from UAV images, it is
Externí odkaz:
https://doaj.org/article/ee4743b9214f4f40827c9eb2e4bc5723
Autor:
Jongmin Shin, Jeong Yeon Do, Raeyeong Kim, Namgyu Son, No-Kuk Park, Ho-Jung Ryu, Myung Won Seo, Junhwa Chi, Young-Sang Youn, Misook Kang
Publikováno v:
Catalysts, Vol 9, Iss 5, p 467 (2019)
This study introduces NiWO4 as a main photocatalyst, where the Ni component promotes methanation to generate a WO3-based catalyst, as a new type of catalyst that promotes the photoreduction of carbon dioxide by slowing the recombination of electrons
Externí odkaz:
https://doaj.org/article/60b3fb616ef54a41afded3d585811456
Autor:
Junhwa Chi, Hyun-choel Kim
Publikováno v:
Remote Sensing, Vol 9, Iss 12, p 1305 (2017)
The Arctic sea ice is an important indicator of the progress of global warming and climate change. Prediction of Arctic sea ice concentration has been investigated by many disciplines and predictions have been made using a variety of methods. Deep le
Externí odkaz:
https://doaj.org/article/80c8891a9fe3447c92f5b93f64862480