File Download

There are no files associated with this item.

Supplementary

Conference Paper: Novel integration of high resolution satellites with drone flights improves monitoring of tree-crown scale autumn leaf phenology

TitleNovel integration of high resolution satellites with drone flights improves monitoring of tree-crown scale autumn leaf phenology
Authors
Issue Date2020
PublisherAmerican Geophysical Union.
Citation
American Geophysical Union (AGU) Fall Meeting, Virtual Meeting, USA, 1-17 December 2020 How to Cite?
AbstractAutumn leaf phenology signals the end of leaf growing season and shows large inter-crown variability in response to global climate change, which strongly regulates the carbon, water, and nutrient cycles from individual tree-crowns up to ecosystems. However, critical challenges remain with the monitoring of tree-crown scale autumn leaf phenology over large spatial coverage due to the lack of spatially explicit information of individual tree-crowns and high-quality and high-resolution time-series observations. Traditional field and proximate remote sensing methods (eg field observations, phenocam measurements and UAV flights) are the commonly-used means to monitor crown-scale leaf phenology, but are constrained to a very limited footprint and time span. Satellite remote sensing might provide another alternative solution, but most satellites remain too coarse spatial resolution to resolve individual tree-crowns.
DescriptionB051: Understanding Phenological Responses and Feedbacks in Terrestrial Vegetation: Patterns, Mechanisms, and Consequences II Posters - abstract no. B051-0014
Persistent Identifierhttp://hdl.handle.net/10722/306062

 

DC FieldValueLanguage
dc.contributor.authorWu, S-
dc.contributor.authorWang, J-
dc.contributor.authorYan, Z-
dc.contributor.authorSONG, G-
dc.contributor.authorChen, Y-
dc.contributor.authorMa, Q-
dc.contributor.authorDeng, M-
dc.contributor.authorWu, Y-
dc.contributor.authorZHAO, Y-
dc.contributor.authorGUO, Z-
dc.contributor.authorXu, X-
dc.contributor.authorYang, X-
dc.contributor.authorSu, Y-
dc.contributor.authorLiu, L-
dc.contributor.authorWu, J-
dc.date.accessioned2021-10-20T10:18:15Z-
dc.date.available2021-10-20T10:18:15Z-
dc.date.issued2020-
dc.identifier.citationAmerican Geophysical Union (AGU) Fall Meeting, Virtual Meeting, USA, 1-17 December 2020-
dc.identifier.urihttp://hdl.handle.net/10722/306062-
dc.descriptionB051: Understanding Phenological Responses and Feedbacks in Terrestrial Vegetation: Patterns, Mechanisms, and Consequences II Posters - abstract no. B051-0014-
dc.description.abstractAutumn leaf phenology signals the end of leaf growing season and shows large inter-crown variability in response to global climate change, which strongly regulates the carbon, water, and nutrient cycles from individual tree-crowns up to ecosystems. However, critical challenges remain with the monitoring of tree-crown scale autumn leaf phenology over large spatial coverage due to the lack of spatially explicit information of individual tree-crowns and high-quality and high-resolution time-series observations. Traditional field and proximate remote sensing methods (eg field observations, phenocam measurements and UAV flights) are the commonly-used means to monitor crown-scale leaf phenology, but are constrained to a very limited footprint and time span. Satellite remote sensing might provide another alternative solution, but most satellites remain too coarse spatial resolution to resolve individual tree-crowns.-
dc.languageeng-
dc.publisherAmerican Geophysical Union.-
dc.relation.ispartofAmerican Geophysical Union (AGU) Fall Meeting, 2020-
dc.rightsAmerican Geophysical Union (AGU) Fall Meeting, 2020. Copyright © American Geophysical Union.-
dc.rights©2020. American Geophysical Union. All Rights Reserved. This article is available at https://agu.confex.com/agu/fm20/meetingapp.cgi/Paper/696068-
dc.titleNovel integration of high resolution satellites with drone flights improves monitoring of tree-crown scale autumn leaf phenology-
dc.typeConference_Paper-
dc.identifier.emailWu, S: shengwu@hku.hk-
dc.identifier.emailWang, J: lucyjing@hku.hk-
dc.identifier.emailYan, Z: zbyan@hku.hk-
dc.identifier.emailWu, J: jinwu@hku.hk-
dc.identifier.authorityWu, J=rp02509-
dc.identifier.hkuros327782-
dc.publisher.placeUnited States-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats