Remote Sensing of Aboveground Vegetation Structure, Biomass, and Water Content Across Spatial and Temporal Scales

Vegetation plays a critical role in the interaction of terrestrial carbon, water, energy, and nutrient cycles at the Earth's surface, influencing global biospheric-atmospheric exchanges of carbon and water and regulating the climate system. However, natural and human-induced disturbances are in...

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Main Author: Devine, Charles John
Other Authors: Smith, William K., Moore, David J.P., Babst, Flurin, Behrangi, Ali
Format: Doctoral or Postdoctoral Thesis
Language:English
Published: The University of Arizona. 2024
Subjects:
Online Access:http://hdl.handle.net/10150/674747
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spelling ftunivarizona:oai:repository.arizona.edu:10150/674747 2024-09-09T19:27:32+00:00 Remote Sensing of Aboveground Vegetation Structure, Biomass, and Water Content Across Spatial and Temporal Scales Devine, Charles John Smith, William K. Moore, David J.P. Babst, Flurin Behrangi, Ali 2024 http://hdl.handle.net/10150/674747 en eng The University of Arizona. Devine, Charles John. (2024). Remote Sensing of Aboveground Vegetation Structure, Biomass, and Water Content Across Spatial and Temporal Scales (Doctoral dissertation, University of Arizona, Tucson, USA). http://hdl.handle.net/10150/674747 Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author. http://rightsstatements.org/vocab/InC/1.0/ Biomass Disturbance Hydrology Plant ecology Remote sensing Wildfire Electronic Dissertation text 2024 ftunivarizona 2024-08-27T14:11:40Z Vegetation plays a critical role in the interaction of terrestrial carbon, water, energy, and nutrient cycles at the Earth's surface, influencing global biospheric-atmospheric exchanges of carbon and water and regulating the climate system. However, natural and human-induced disturbances are increasingly affecting ecosystems, leading to reduced carbon storage by vegetation. Satellite remote sensing is used for spatiotemporal estimation of key vegetation variables such as structure, aboveground biomass (AGB), and vegetation water content (VWC), but coarse pixel resolution poses challenges for accurate calibration and validation of these estimates. In this dissertation, I explored novel remote sensing technologies and techniques to improve structure, AGB, and VWC estimation across multiple spatial and temporal scales. I incorporated environmental disturbance factors to benchmark the temporal sensitivity of these estimates to large-scale biomass change and to evaluate their accuracy in quantifying disturbance-driven biomass loss. Appendix A focused on enriching annual AGB estimates in North American arctic-boreal ecosystems using integrated of microwave and optical-multispectral satellite observations. This approach enhanced spatial AGB across the region and improved detection of biomass loss driven by large-scale wildfires. Appendix B explored the application of close-range photogrammetry and derived ultra-high spatial resolution 3D models for extracting structural plant information, improving biomass quantification, and assessing the impacts of physical disturbance for three morphologically distinct dryland shrub species. We found that the model integrating canopy area and mean shrub height yielded the most accurate species-agnostic AGB estimate, and adequately captured biomass loss driven by physical disturbance. Appendix C evaluated tower-level microwave reflectance and its relationship with eddy covariance flux measurements, vegetation greenness, soil moisture, and satellite microwave observations in a ... Doctoral or Postdoctoral Thesis Arctic The University of Arizona: UA Campus Repository Arctic
institution Open Polar
collection The University of Arizona: UA Campus Repository
op_collection_id ftunivarizona
language English
topic Biomass
Disturbance
Hydrology
Plant ecology
Remote sensing
Wildfire
spellingShingle Biomass
Disturbance
Hydrology
Plant ecology
Remote sensing
Wildfire
Devine, Charles John
Remote Sensing of Aboveground Vegetation Structure, Biomass, and Water Content Across Spatial and Temporal Scales
topic_facet Biomass
Disturbance
Hydrology
Plant ecology
Remote sensing
Wildfire
description Vegetation plays a critical role in the interaction of terrestrial carbon, water, energy, and nutrient cycles at the Earth's surface, influencing global biospheric-atmospheric exchanges of carbon and water and regulating the climate system. However, natural and human-induced disturbances are increasingly affecting ecosystems, leading to reduced carbon storage by vegetation. Satellite remote sensing is used for spatiotemporal estimation of key vegetation variables such as structure, aboveground biomass (AGB), and vegetation water content (VWC), but coarse pixel resolution poses challenges for accurate calibration and validation of these estimates. In this dissertation, I explored novel remote sensing technologies and techniques to improve structure, AGB, and VWC estimation across multiple spatial and temporal scales. I incorporated environmental disturbance factors to benchmark the temporal sensitivity of these estimates to large-scale biomass change and to evaluate their accuracy in quantifying disturbance-driven biomass loss. Appendix A focused on enriching annual AGB estimates in North American arctic-boreal ecosystems using integrated of microwave and optical-multispectral satellite observations. This approach enhanced spatial AGB across the region and improved detection of biomass loss driven by large-scale wildfires. Appendix B explored the application of close-range photogrammetry and derived ultra-high spatial resolution 3D models for extracting structural plant information, improving biomass quantification, and assessing the impacts of physical disturbance for three morphologically distinct dryland shrub species. We found that the model integrating canopy area and mean shrub height yielded the most accurate species-agnostic AGB estimate, and adequately captured biomass loss driven by physical disturbance. Appendix C evaluated tower-level microwave reflectance and its relationship with eddy covariance flux measurements, vegetation greenness, soil moisture, and satellite microwave observations in a ...
author2 Smith, William K.
Moore, David J.P.
Babst, Flurin
Behrangi, Ali
format Doctoral or Postdoctoral Thesis
author Devine, Charles John
author_facet Devine, Charles John
author_sort Devine, Charles John
title Remote Sensing of Aboveground Vegetation Structure, Biomass, and Water Content Across Spatial and Temporal Scales
title_short Remote Sensing of Aboveground Vegetation Structure, Biomass, and Water Content Across Spatial and Temporal Scales
title_full Remote Sensing of Aboveground Vegetation Structure, Biomass, and Water Content Across Spatial and Temporal Scales
title_fullStr Remote Sensing of Aboveground Vegetation Structure, Biomass, and Water Content Across Spatial and Temporal Scales
title_full_unstemmed Remote Sensing of Aboveground Vegetation Structure, Biomass, and Water Content Across Spatial and Temporal Scales
title_sort remote sensing of aboveground vegetation structure, biomass, and water content across spatial and temporal scales
publisher The University of Arizona.
publishDate 2024
url http://hdl.handle.net/10150/674747
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_relation Devine, Charles John. (2024). Remote Sensing of Aboveground Vegetation Structure, Biomass, and Water Content Across Spatial and Temporal Scales (Doctoral dissertation, University of Arizona, Tucson, USA).
http://hdl.handle.net/10150/674747
op_rights Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
http://rightsstatements.org/vocab/InC/1.0/
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