Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Hideaki, Takenaka"'
Autor:
Osamu Iwase, Hideaki Takenaka
Publikováno v:
Energy Science & Engineering, Vol 10, Iss 9, Pp 3471-3492 (2022)
Abstract This study describes the estimation of solar radiation from photovoltaic (PV) power generation in smart streetlights (SSL) with a heat transfer model. The distribution of solar radiation is important for managing PV power generation. In part
Externí odkaz:
https://doaj.org/article/aca2425ed01c4e44bba98b739d724bdd
Autor:
Masahiro Momoi, Hitoshi Irie, Miho Sekiguchi, Teruyuki Nakajima, Hideaki Takenaka, Kazuhiko Miura, Kazuma Aoki
Publikováno v:
Progress in Earth and Planetary Science, Vol 9, Iss 1, Pp 1-22 (2022)
Abstract We developed lookup tables for the correlated k-distribution (CKD) method in the 940 nm water vapor absorption region (WV-CKD), with the aim of rapid and accurate computation of narrow-band radiation around 940 nm (10,000–10,900 $${\mathrm
Externí odkaz:
https://doaj.org/article/5efe344feba84cd89e09626b494dabe2
Autor:
Hirofumi Hashimoto, Weile Wang, Jennifer L. Dungan, Shuang Li, Andrew R. Michaelis, Hideaki Takenaka, Atsushi Higuchi, Ranga B. Myneni, Ramakrishna R. Nemani
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
Cloud cover and scarcity of ground-based validation hinder remote sensing of forest dynamics in the Amazon basin. Here, the authors analyse imagery from a high-frequency geostationary satellite sensor to study monthly NDVI patterns in the Amazon fore
Externí odkaz:
https://doaj.org/article/23a00371dcb94f4197d5aecbbb118679
Publikováno v:
Earth and Space Science, Vol 7, Iss 11, Pp n/a-n/a (2020)
Abstract A clustering and classification method using a Gaussian mixture model (GMM) is used to summarize and simplify meteorological data from a numerical weather prediction (NWP) model. Each horizontal grid in the integration domain of the NWP mode
Externí odkaz:
https://doaj.org/article/a5f8f72f263f4a91b47a47860aef4b54
Autor:
Tatsuhiro Furuyama, Masahide Ueda, Asuka Okada, Sae Hato, Yuma Watabe, Yusuke Inui, Takahiro Ibaraki, Fumitaka Mito, Hideaki Takenaka, Sumito Choh
Publikováno v:
Haigan. 62:1048-1055
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::163f4475c4de57aaef28830763a5d8e2
https://doi.org/10.2482/haigan.62.1048
https://doi.org/10.2482/haigan.62.1048
Publikováno v:
Remote Sensing, Vol 12, Iss 15, p 2472 (2020)
This study describes a high-speed correction method for geolocation information of geostationary satellite data for accurate physical analysis. Geostationary satellite observations with high temporal resolution provide instantaneous analysis and prom
Externí odkaz:
https://doaj.org/article/1408d1a025a647d8bf015aa7842cd484
Autor:
Weile Wang, Shuang Li, Hirofumi Hashimoto, Hideaki Takenaka, Atsushi Higuchi, Satya Kalluri, Ramakrishna Nemani
Publikováno v:
Remote Sensing, Vol 12, Iss 8, p 1267 (2020)
GeoNEX is a collaborative project led by scientists from NASA, NOAA, and many other institutes around the world to generate Earth monitoring products using data streams from the latest Geostationary (GEO) sensors including the GOES-16/17 Advanced Bas
Externí odkaz:
https://doaj.org/article/3f6f3849f36a4b5f90fe3590ff4a2d24
Publikováno v:
Remote Sensing, Vol 12, Iss 9, p 1372 (2020)
Recent advancements in new generation geostationary satellites have facilitated the application of their datasets to terrestrial monitoring. In this application, geolocation accuracy is an essential issue because land surfaces are generally heterogen
Externí odkaz:
https://doaj.org/article/257eba16f3654e518f080e2d395631f0
Autor:
Sumito Choh, Yuma Watabe, Fumitaka Mito, Asuka Okada, Hideaki Takenaka, Yusuke Inui, Masahide Ueda, Tatsuhiro Furuyama, Katsumasa Koyama, Takahiro Ibaraki
Publikováno v:
Haigan. 61:347-352
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d1bdbfaf1f9869b177b6e1f14ba0650
https://doi.org/10.2482/haigan.61.347
https://doi.org/10.2482/haigan.61.347
Publikováno v:
Solar Energy. 223:202-216
The numerical weather prediction (NWP) model still produces forecast errors. In this study, a correction method for the data from the NWP model is developed to obtain more skillful forecast data. The proposed method fuses information about surface gl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8011d27cfeb9d7056f2154bdf492970
https://doi.org/10.1016/j.solener.2021.05.055
https://doi.org/10.1016/j.solener.2021.05.055