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The University of Arizona.

Understanding Carbon Uptake Using Multi-Scale Novel Remote Sensing Techniques

Abstract

dc:description.abstract

Drylands cover 40% of the global terrestrial area and support roughly 2 billion people for grazing and cropping. With hotter, drier climate forecasts for dryland, in particular, there are new challenges in understanding dryland responses and vulnerability. This has emerged as a priority research frontier because dryland carbon dynamics have been identified as disproportionately important in regulating interannual variability of atmospheric CO2 concentrations. Remote sensing can be used to monitor multiple aspects of vegetation dynamics as well as its sensitivity to climate to improve dryland carbon uptake estimations. The thesis integrated existing cutting-edge remote sensing proxies to reduce uncertainties in dryland carbon uptake estimations from global to ecosystem scale. The results suggested that at a global scale, solar-induced fluorescence (SIF) captures gross primary productivity (GPP) phenology more accurately than the normalized difference vegetation index (NDVI) and vegetation optical depth (VOD). In dryland regions, integrating near-infrared reflectance of terrestrial vegetation (NIRv), SIF and heterogeneity will improve satellite-based GPP estimates. In a semi-arid grassland ecosystem, integrating SIF and the photochemical reflectance index (PRI) will improve the understanding of photosynthesis during extreme droughts. Overall, this research integrated multiple available remotely sensed proxies to improve understanding of vegetation response to climate change across scales, across heterogeneous regions, and during extreme droughts. My research has the potential to revolutionize the way we monitor dryland vegetation productivity through integrating different and independent proxies or adjusting GPP models’ inputs. These understandings will also provide a valuable vegetation productivity map to inform adaptive ecosystem management strategies in support of climate mitigation in drylands.

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Graduate College
Grantor dc:publisher
The University of Arizona.
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Wang, Xian
Advisor dc:contributor.advisor
  • Smith, William
Committee members dc:contributor.committeemember
  • Moore, David
  • Leeuwen, Willem
  • Barron-Gafford, Greg

Rights

dc:rights
Statement dc: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.
Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/10150/666147
OAI identifier oai:identifier
oai:repository.arizona.edu:10150/666147

Chain of custody

source
Harvested from
University of Arizona
Base URL
repository.arizona.edu/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Wang, Xian. Understanding Carbon Uptake Using Multi-Scale Novel Remote Sensing Techniques. doctoral thesis, The University of Arizona., 2022. http://hdl.handle.net/10150/666147