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Remotely Evaluating the Seasonality of Gross Primary Production at High Latitudes


Cheng, Rui (2023) Remotely Evaluating the Seasonality of Gross Primary Production at High Latitudes. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/3gnn-sy17.


A warming trend larger than the global average is changing high-latitude terrestrial ecosystems. The impact of climate change at high latitudes is especially notable on the seasonality of vegetation photosynthesis, such as the Arctic greening, lengthened growing season, and increased peak production in the growing season. As a critical component of the global carbon cycle and land carbon sink, continuously monitoring the seasonal trajectory of ecosystem-level photosynthesis, Gross Primary Production (GPP), is much needed to better understand the climate change impacts and the sensitivity of high-latitude plant communities under global climate change. GPP has been estimated from both ground and space. However, sparsely distributed ground-level measurements are not representative of heterogeneous land cover and complex terrain in high latitudes. Remote sensing techniques provide extensive spatial coverage for comparing GPP at the regional scale. In this thesis, I carefully examine the advances in remote sensing for monitoring GPP at high latitudes, including using hyperspectral reflectance and Solar-Induced chlorophyll Fluorescence (SIF). We show that reflectance near 531 nm can track the seasonality of Light Use Efficiency (LUE), complementing conventional normalized difference vegetation index which is only a proxy of Absorbed Photosynthetic Active Radiation (APAR). Tracking both LUE and APAR is critical for improving GPP estimation, especially in evergreen forests with photosynthetic phenology but sustained canopy color -- a typical land cover type at high latitudes. Satellite-measured SIF can also track both LUE and APAR. Here, it is shown that the empirical model predicting GPP using SIF is land cover dependent. The presence of snow and surface, heterogeneous land cover, and complex terrains in the high latitudes further complicate the interpretation of the SIF-GPP relationship. To improve the accuracy of interpreting SIF in complex terrain, a geometric model is developed to account for variations in APAR on tilted slopes. The results of this thesis enhance the use of both reflectance and SIF to help improve terrestrial biosphere models simulating GPP and cope with model-data uncertainties. The results are also a useful reference for future satellite missions designing instruments and correcting topographic impacts. Overall, this thesis contributes to better evaluating GPP and constraining climate projection uncertainties.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Gross Primary Productivity (GPP), Light Use Efficiency (LUE), hyperspectral reflectance, Solar-Induced Chlorophyll Fluorescence (SIF), length-of-day correction, clear sky bias
Degree Grantor:California Institute of Technology
Division:Geological and Planetary Sciences
Major Option:Environmental Science and Engineering
Minor Option:Electrical Engineering
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Frankenberg, Christian
Thesis Committee:
  • Schneider, Tapio (chair)
  • Frankenberg, Christian
  • Wennberg, Paul O.
  • Bloom, A. Anthony
Defense Date:10 August 2022
Funding AgencyGrant Number
Record Number:CaltechTHESIS:08112022-214313625
Persistent URL:
Related URLs:
URLURL TypeDescription adapted for Ch. 2 used in Ch. 2 adapted for Ch. 3 adapted for Ch. 4 used in Ch. 4
Cheng, Rui0000-0002-3003-8339
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:14999
Deposited By: Rui Cheng
Deposited On:17 Aug 2022 20:46
Last Modified:18 Nov 2022 21:14

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