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Design of the Business Model to Reduce the Damage of Heavy Snowfall in Greenhouse
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2022-04-11
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TitleTitleTitle ³ó¸²»ýÅ°è Áö¼Ó°¡´É¼º Á¦°í¸¦ À§ÇÑ ³ó¸²±â»óÇÐÀÇ µµÀü°ú °úÁ¦Àå±â °üÃø ¿¡µð Ç÷°½º ÀÚ·áÀÇ ¿¬¼Ó¼º È®º¸¿¡ ´ëÇÏ¿© : °³È¸·Î ¹× ºÀÆóȸ·Î ±âüºÐ¼®±âÀÇ ¾ß¿Ü »óÈ£ ºñ±³Anticipating global terrestrial ecosystem state change using fluxnet.The influence of tree structural and species diversity on temperate forest productivity and stability in korea.Impact of leaf area index from various sources on estimating gross primary production in temperate forests using the jules land surface model.Fluxnet-ch4 synthesis activity : Objectives, observations, and future directions.Gap-filling approaches for eddy covariance methane fluxes : A comparison of three machine learning algorithms and traditional method with principal component analysis.Modification of the moving point test method for nighttime eddy co2 flux filtering on hilly and complex terrains.New Gap-filling strategies for long-period flux data gaps using a data-driven approach.Making full use of hyperspectral data for gross primary productivity estimation with multivariate regression : Mechanistic insights from observations and process-based simulations.An Approximate Estimation of snow Weight Using KMA Weather Station Data and Snow Density Formulae.Simulation and Analysis of Solar Radiation Change Resulted from Solar-sharing for Agricultural Solar Photovoltaic SystemConstruction of NCAM-LAMP Precipitaion and Soil Moisture Database to Support Landslide Prediction Inferring co2 fertilization effect based on global monitoring land-atmosphere exchange with a theoretical model. ³ó°æÁö Åä¾ç¼öºÐ ÃßÁ¤ ±â¼ú °³¹ßÀ» À§ÇÑ Å×½ºÆ® º£µå µ¥ÀÌÅÍ ¼¼Æ®±¹Áö¿¹º¸¸ðµ¨°ú À§¼º¿µ»óÀ» ÀÌ¿ëÇÑ ±Ø»ó¸² Ç÷°½º °üÃøÀÇ °ø°£¿¬¼Ó¸é È®Àå ¹× ¿ì¸®³ª¶ó »ê¸²ÀÇ ÀÏÀÏ Åº¼ÒÈí¼ö´É °ÝÀÚÀÚ·á »êÃâ¼ö¾×·ù ÃøÁ¤ µ¥ÀÌÅÍ º£À̽º : ±×·¡´Ï¾î(granier)¼¾¼­ ¿­¼Õ½ÇŽħ¹ý(heat dissipation method) °ú ¿­Æĵ¿¹ý(heat pilse method) À» ÀÌ¿ëÇÑ ¼ö¾×·ù ÃøÁ¤.Changes in the Spatiotemporal Patterns of Precipitation Due to Climate Change
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Past, Present and Future of Geospatial Scheme based on Topo-Climatic Model and Digital Climate Map.
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Relationship between Solar Radiation in Complex Terrains and Shaded Relief Images.
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Analysis of Literatures Related to Crop Growth and Yield of Onion and Garlic Using Text-mining Approaches for Develop Productivity Prediction Models.
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A High-Resolution (20m) simulation of Nighttime Low Temperature Inducing Agricultural Crop Damage with the WRF-LES Modeling System
Development of Mask-RCNN Model for Detecting Greenhouses Based on Satellite Image
Spatial and Temporal Variations in AtmosphericVentilation Index Coupled with Particulate Matter Concentration in South Korea
Machine Learning-Based Hourly Forest-Prediction System Optimized for Orchards Using Automatic Weather Station and Digital Camera Image Data
Design of the Business Model to Reduce the Damage of Heavy Snowfall in Greenhouse
AuthorsAuthorsAuthorsAuthorsAuthors ÀÌÁ¾Çõ, ÀÌ»óÀÍ, Á¤¿µÁØ, ±èµ¿¼ö, À̽ÂÀç, ÃÖ¿ø
PublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublicationPublication 2018201820182018201820182018201920192019201920192019201920192019201920192019201920192019202020202020202020202020202020212021202120212021202120212021202120212021
JournalJournalJournal ´ëÇÑ¿ø°ÝŽ»çÇÐȸÁö 36Korean Journal of Agricultural and Forest Meteorology Korean Journal of Agricultural and Forest Meteorology Korean Journal of Agricultural and Forest Meteorology Korean Journal of Agricultural and Forest Meteorology Korean Journal of Agricultural and Forest Meteorology Korean Journal of Agricultural and Forest Meteorology Korean Journal of Agricultural and Forest Meteorology AtmosphereKorean Jounal of Agricultural and Forest MeteorologySustainability 13AtmosphereJournal of the Korean Society of Civil Engineers
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Drought Monitoring Based on Vegetation Type and Reanalysis Data in Korea
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TitleTitleTitleTitle ³ó¸²»ýÅ°è Áö¼Ó°¡´É¼º Á¦°í¸¦ À§ÇÑ ³ó¸²±â»óÇÐÀÇ µµÀü°ú °úÁ¦Àå±â °üÃø ¿¡µð Ç÷°½º ÀÚ·áÀÇ ¿¬¼Ó¼º È®º¸¿¡ ´ëÇÏ¿© : °³È¸·Î ¹× ºÀÆóȸ·Î ±âüºÐ¼®±âÀÇ ¾ß¿Ü »óÈ£ ºñ±³Anticipating global terrestrial ecosystem state change using fluxnet.The influence of tree structural and s..
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Machine Learning-Based Hourly Forest-Prediction System Optimized for Orchards Using Automatic Weather Station and Digital Camera Image Data
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TitleTitle ³ó¸²»ýÅ°è Áö¼Ó°¡´É¼º Á¦°í¸¦ À§ÇÑ ³ó¸²±â»óÇÐÀÇ µµÀü°ú °úÁ¦Àå±â °üÃø ¿¡µð Ç÷°½º ÀÚ·áÀÇ ¿¬¼Ó¼º È®º¸¿¡ ´ëÇÏ¿© : °³È¸·Î ¹× ºÀÆóȸ·Î ±âüºÐ¼®±âÀÇ ¾ß¿Ü »óÈ£ ºñ±³Anticipating global terrestrial ecosystem state change using fluxnet.The influence of tree structural and species div..