Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Jong-oh Ban"'
Publikováno v:
Ecological Informatics, Vol 84, Iss , Pp 102886- (2024)
This study introduces a novel crop modeling approach based on cutting-edge computational tools to advance crop production monitoring methodologies, and, thereby, tackle global food security issues. Our approach pioneers integrating deep learning and
Externí odkaz:
https://doaj.org/article/7917c9ac78474e20b9f8e7e63a35c006
Publikováno v:
Remote Sensing, Vol 14, Iss 6, p 1421 (2022)
This study aimed to simulate the spatiotemporal variation in cotton (Gossypium hirsutum L.) growth and lint yield using a remote sensing-integrated crop model (RSCM) for cotton. The developed modeling scheme incorporated proximal sensing data and sat
Externí odkaz:
https://doaj.org/article/44de24b2f207472081a2dbf47a71ad7d
Publikováno v:
Agronomy, Vol 11, Iss 12, p 2544 (2021)
This study sought to simulate regional variation in staple crop yields in Chonnam Province, Republic of Korea (ROK), in future environments under climate change based on the calibration of crop models in the Decision Support System for Agricultural T
Externí odkaz:
https://doaj.org/article/4c46db6503b0417aae5a8a92d91fc1e6
Publikováno v:
Energies, Vol 14, Iss 24, p 8463 (2021)
Agro-photovoltaic systems are of interest to the agricultural industry because they can produce both electricity and crops in the same farm field. In this study, we aimed to simulate staple crop yields under agro-photovoltaic panels (AVP) based on th
Externí odkaz:
https://doaj.org/article/1a61953edd8e4652907c0a7afac17e71
Autor:
Ki-Hyeon Kwon, Jong Oh Ban
Publikováno v:
Journal of the Korea Academia-Industrial cooperation Society. 13:1319-1324
Tomatoes were harvested at different ripening stages. To determine the ripening stages, We analyzed the relation between the compound concentrations of tomato measured with HPLC and the tomato RGB images. Among the compound concentrations, tomato qua
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1b89993785d7e65783fb89add1eba3c
https://doi.org/10.5762/kais.2012.13.3.1319
https://doi.org/10.5762/kais.2012.13.3.1319
Publikováno v:
Journal of Applied Remote Sensing. 9:096067
The GRAMI crop growth model uses remote sensing data and thus has the potential to produce maps of crop growth and yield. A pixel-based crop information delivery system (CIDS) to simulate and map rice (Oryza sativa) growth and yield was developed usi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8fb0f6af10f97defc0d2e71aeb74d93
https://doi.org/10.1117/1.jrs.9.096067
https://doi.org/10.1117/1.jrs.9.096067