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Conference Paper: Imaging Spectroscopy for Advancing Agricultural and Environmental Sciences II Posters

TitleImaging Spectroscopy for Advancing Agricultural and Environmental Sciences II Posters
Authors
Issue Date2019
PublisherAmerican Geophysical Union.
Citation
American Geophysical Union (AGU) Fall Meeting, San Francisco, USA, 9-13 December 2019 How to Cite?
AbstractHigh spectral resolution remote sensing provides unique spectral-spatial information that remains a largely untapped resource for understanding many aspects of global change. Particularly, hyperspectral measurements from on-site, close-range, and remote platforms are increasingly used in interdisciplinary research that integrates state-of-the-art techniques and domain knowledge in response to agricultural and environmental challenges. The growing availability of hyperspectral data along with improved earth system models will stimulate more studies in monitoring, mapping, understanding, and modeling agricultural and natural ecosystems at various scales. The following topics are encouraged (not limited to): imaging spectroscopy in response to society challenges (e.g., food insecurity and biodiversity loss); environmental monitoring (e.g., toxic wastes, water pollution, and biomass burning); precision agriculture (e.g., discrimination of crop stress, diseases, and pesticide residuals); integration of hyperspectral data with earth system models for understanding agricultural, urban, and natural ecosystems; next generation of hyperspectral sensors, platforms, and missions for agricultural and environmental challenges.
DescriptionPoster Session: B31K - Conveners / Chairman
Persistent Identifierhttp://hdl.handle.net/10722/306063

 

DC FieldValueLanguage
dc.contributor.authorFu, P-
dc.contributor.authorWu, J-
dc.contributor.authorLiang, B-
dc.contributor.authorSerbin, S-
dc.contributor.authorBernacchi, C-
dc.date.accessioned2021-10-20T10:18:16Z-
dc.date.available2021-10-20T10:18:16Z-
dc.date.issued2019-
dc.identifier.citationAmerican Geophysical Union (AGU) Fall Meeting, San Francisco, USA, 9-13 December 2019-
dc.identifier.urihttp://hdl.handle.net/10722/306063-
dc.descriptionPoster Session: B31K - Conveners / Chairman-
dc.description.abstractHigh spectral resolution remote sensing provides unique spectral-spatial information that remains a largely untapped resource for understanding many aspects of global change. Particularly, hyperspectral measurements from on-site, close-range, and remote platforms are increasingly used in interdisciplinary research that integrates state-of-the-art techniques and domain knowledge in response to agricultural and environmental challenges. The growing availability of hyperspectral data along with improved earth system models will stimulate more studies in monitoring, mapping, understanding, and modeling agricultural and natural ecosystems at various scales. The following topics are encouraged (not limited to): imaging spectroscopy in response to society challenges (e.g., food insecurity and biodiversity loss); environmental monitoring (e.g., toxic wastes, water pollution, and biomass burning); precision agriculture (e.g., discrimination of crop stress, diseases, and pesticide residuals); integration of hyperspectral data with earth system models for understanding agricultural, urban, and natural ecosystems; next generation of hyperspectral sensors, platforms, and missions for agricultural and environmental challenges.-
dc.languageeng-
dc.publisherAmerican Geophysical Union.-
dc.relation.ispartofAmerican Geophysical Union (AGU) Fall Meeting, 2019-
dc.rightsAmerican Geophysical Union (AGU) Fall Meeting, 2019. Copyright © American Geophysical Union.-
dc.rights©[copyright year]. American Geophysical Union. All Rights Reserved. This article is available at https://doi.org/[DOI].-
dc.titleImaging Spectroscopy for Advancing Agricultural and Environmental Sciences II Posters-
dc.typeConference_Paper-
dc.identifier.emailWu, J: jinwu@hku.hk-
dc.identifier.authorityWu, J=rp02509-
dc.identifier.hkuros327783-
dc.publisher.placeUnited States-

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