Constraints and Opportunities for Detecting Land Surface Phenology in Drylands

Land surface phenology (LSP) enables global-scale tracking of ecosystem processes, but its utility is limited in drylands due to low vegetation cover and resulting low annual amplitudes of vegetation indices (VIs). Due to the importance of drylands for biodiversity, food security, and the carbon cyc...

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Autores principales:	Shawn D. Taylor, Dawn M. Browning, Ruben A. Baca, Feng Gao
Formato:	article
Lenguaje:	EN
Publicado:	American Association for the Advancement of Science (AAAS) 2021
Materias:	Environmental sciences GE1-350 Physical geography GB3-5030
Acceso en línea:	https://doaj.org/article/c7b250ee324a45a89129da057f6e3c15
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spelling	oai:doaj.org-article:c7b250ee324a45a89129da057f6e3c152021-11-08T08:26:27ZConstraints and Opportunities for Detecting Land Surface Phenology in Drylands2694-158910.34133/2021/9859103https://doaj.org/article/c7b250ee324a45a89129da057f6e3c152021-01-01T00:00:00Zhttp://dx.doi.org/10.34133/2021/9859103https://doaj.org/toc/2694-1589Land surface phenology (LSP) enables global-scale tracking of ecosystem processes, but its utility is limited in drylands due to low vegetation cover and resulting low annual amplitudes of vegetation indices (VIs). Due to the importance of drylands for biodiversity, food security, and the carbon cycle, it is necessary to understand the limitations in measuring dryland dynamics. Here, using simulated data and multitemporal unmanned aerial vehicle (UAV) imagery of a desert shrubland, we explore the feasibility of detecting LSP with respect to fractional vegetation cover, plant functional types, VI uncertainty, and two different detection algorithms. Using simulated data, we found that plants with distinct VI signals, such as deciduous shrubs, can require up to 60% fractional cover to consistently detect LSP. Evergreen plants, with lower seasonal VI amplitude, require considerably higher cover and can have undetectable phenology even with 100% vegetation cover. Our evaluation of two algorithms showed that neither performed the best in all cases. Even with adequate cover, biases in phenological metrics can still exceed 20 days and can never be 100% accurate due to VI uncertainty from shadows, sensor view angle, and atmospheric interference. We showed how high-resolution UAV imagery enables LSP studies in drylands and highlighted important scale effects driven by within-canopy VI variation. With high-resolution imagery, the open canopies of drylands are beneficial as they allow for straightforward identification of individual plants, enabling the tracking of phenology at the individual level. Drylands thus have the potential to become an exemplary environment for future LSP research.Shawn D. TaylorDawn M. BrowningRuben A. BacaFeng GaoAmerican Association for the Advancement of Science (AAAS)articleEnvironmental sciencesGE1-350Physical geographyGB3-5030ENJournal of Remote Sensing, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Environmental sciences GE1-350 Physical geography GB3-5030
spellingShingle	Environmental sciences GE1-350 Physical geography GB3-5030 Shawn D. Taylor Dawn M. Browning Ruben A. Baca Feng Gao Constraints and Opportunities for Detecting Land Surface Phenology in Drylands
description	Land surface phenology (LSP) enables global-scale tracking of ecosystem processes, but its utility is limited in drylands due to low vegetation cover and resulting low annual amplitudes of vegetation indices (VIs). Due to the importance of drylands for biodiversity, food security, and the carbon cycle, it is necessary to understand the limitations in measuring dryland dynamics. Here, using simulated data and multitemporal unmanned aerial vehicle (UAV) imagery of a desert shrubland, we explore the feasibility of detecting LSP with respect to fractional vegetation cover, plant functional types, VI uncertainty, and two different detection algorithms. Using simulated data, we found that plants with distinct VI signals, such as deciduous shrubs, can require up to 60% fractional cover to consistently detect LSP. Evergreen plants, with lower seasonal VI amplitude, require considerably higher cover and can have undetectable phenology even with 100% vegetation cover. Our evaluation of two algorithms showed that neither performed the best in all cases. Even with adequate cover, biases in phenological metrics can still exceed 20 days and can never be 100% accurate due to VI uncertainty from shadows, sensor view angle, and atmospheric interference. We showed how high-resolution UAV imagery enables LSP studies in drylands and highlighted important scale effects driven by within-canopy VI variation. With high-resolution imagery, the open canopies of drylands are beneficial as they allow for straightforward identification of individual plants, enabling the tracking of phenology at the individual level. Drylands thus have the potential to become an exemplary environment for future LSP research.
format	article
author	Shawn D. Taylor Dawn M. Browning Ruben A. Baca Feng Gao
author_facet	Shawn D. Taylor Dawn M. Browning Ruben A. Baca Feng Gao
author_sort	Shawn D. Taylor
title	Constraints and Opportunities for Detecting Land Surface Phenology in Drylands
title_short	Constraints and Opportunities for Detecting Land Surface Phenology in Drylands
title_full	Constraints and Opportunities for Detecting Land Surface Phenology in Drylands
title_fullStr	Constraints and Opportunities for Detecting Land Surface Phenology in Drylands
title_full_unstemmed	Constraints and Opportunities for Detecting Land Surface Phenology in Drylands
title_sort	constraints and opportunities for detecting land surface phenology in drylands
publisher	American Association for the Advancement of Science (AAAS)
publishDate	2021
url	https://doaj.org/article/c7b250ee324a45a89129da057f6e3c15
work_keys_str_mv	AT shawndtaylor constraintsandopportunitiesfordetectinglandsurfacephenologyindrylands AT dawnmbrowning constraintsandopportunitiesfordetectinglandsurfacephenologyindrylands AT rubenabaca constraintsandopportunitiesfordetectinglandsurfacephenologyindrylands AT fenggao constraintsandopportunitiesfordetectinglandsurfacephenologyindrylands
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Constraints and Opportunities for Detecting Land Surface Phenology in Drylands

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