Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Kentaro Aida"'
Publikováno v:
AgriEngineering, Vol 6, Iss 1, Pp 574-596 (2024)
Having an additional tool for swiftly determining the extent of flood damage to crops with confidence is beneficial. This study focuses on estimating rice crop damage caused by flooding in Candaba, Pampanga, using open-source satellite data. By analy
Externí odkaz:
https://doaj.org/article/7bc5b7ce9e7a47bcbbbc8828c018e42a
Autor:
Kohei Hosonuma, Kentaro Aida, Vicente Ballaran, Naoko Nagumo, Patricia Ann J. Sanchez, Tsuyoshi Sumita, Koki Homma
Publikováno v:
Remote Sensing, Vol 16, Iss 3, p 499 (2024)
Floods are some of the most devastating crop disasters in Southeast Asia. The Pampanga River Basin in the Philippines is a representative flood-prone area, where cultivation patterns vary according to the flood risk. However, quantitative analyses of
Externí odkaz:
https://doaj.org/article/975de1f2f3e749a5b0a29f99b9966d2a
Autor:
Mohamed Rasmy, Masaki Yasukawa, Tomoki Ushiyama, Katsunori Tamakawa, Kentaro Aida, Sugeeshwara Seenipellage, Selvarajah Hemakanth, Masaru Kitsuregawa, Toshio Koike
Publikováno v:
Water, Vol 15, Iss 6, p 1199 (2023)
Flood early warning systems (FEWS) are crucial for flood risk management; however, several catchments in the developing world are still far behind in all aspects of FEWS and thus, they encounter devastating damage recurrently due to limitations in da
Externí odkaz:
https://doaj.org/article/f4eeea0292a04af9b8ae0eac932b684a
Publikováno v:
Progress in Earth and Planetary Science, Vol 5, Iss 1, Pp 1-18 (2018)
Abstract We analyze the hourly rainfall data of 30 rain gauges in Cambodia from 2010 to 2015 to focus on the diurnal pattern of rainfall and its regional characteristics, with the underlying mechanisms inferred from the observed data. The observed an
Externí odkaz:
https://doaj.org/article/fb64a63ed5bf434ab481b3b624708c13
Publikováno v:
Sensors, Vol 19, Iss 18, p 3924 (2019)
The assimilation of radiometer and synthetic aperture radar (SAR) data is a promising recent technique to downscale soil moisture products, yet it requires land surface parameters and meteorological forcing data at a high spatial resolution. In this
Externí odkaz:
https://doaj.org/article/8ca72bd18d6d41eca18d1d3e6e874627
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 59:1355-1368
Satellite-based passive microwave (PMW) remote sensing is an essential technique to clarify long-term and large-scale distribution patterns of cloud water content (CWC). However, most CWC estimation methods are not implemented over land because of hi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7543264a00e269a5e1c47056685ab58b
https://doi.org/10.1109/tgrs.2020.2996239
https://doi.org/10.1109/tgrs.2020.2996239
Autor:
Kentaro AIDA, Miho OHARA, Naoko NAGUMO, Patricia Ann JARANILLA-SANCHEZ, Keijiro KUBOTA, Takafumi SHINYA
Publikováno v:
Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering). 78:I_985-I_990
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3fd8b27bce92eedb0374253d75a836fc
https://doi.org/10.2208/jscejhe.78.2_i_985
https://doi.org/10.2208/jscejhe.78.2_i_985
Autor:
Fan Chen, Kentaro Aida, Jun Asanuma, Wade T. Crow, Mariko Burgin, Andreas Colliander, Rajat Bindlish
Publikováno v:
Remote Sens Environ
Global-scale surface soil moisture products are currently available from multiple remote sensing platforms. Footprint-scale assessments of these products are generally restricted to limited number of densely-instrumented validation sites. However, by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3ad2f4a00668e607d8a3a6af5be5139
https://doi.org/10.1016/j.rse.2018.05.008
https://doi.org/10.1016/j.rse.2018.05.008
Autor:
Pierre Gentine, Heather McNairn, Simone Bircher, Thomas J. Jackson, Andreas Colliander, A. Pacheco, Jun Asanuma, Jana Kolassa, Michael H. Cosh, Jeffrey P. Walker, Seyed Hamed Alemohammad, José Martínez-Fernández, Todd G. Caldwell, Rolf H. Reichle, Kentaro Aida, Qiang Liu, C. Holifield Collins, M. Thibeault
Publikováno v:
Remote Sensing of Environment. 204:43-59
A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2–3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::095f29b2966ad64e1f964459880cf30a
https://doi.org/10.1016/j.rse.2017.10.045
https://doi.org/10.1016/j.rse.2017.10.045
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 55:6195-6206
Uncertainty in surface soil roughness strongly degrades the performance of surface soil moisture (SSM) and vegetation water content (VWC) retrieval from passive microwave observations. This paper proposes an algorithm to objectively determine the sur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddc90bf350d93de9777d5a342823b3e7
https://doi.org/10.1109/tgrs.2017.2722468
https://doi.org/10.1109/tgrs.2017.2722468