Investigating the Effect of California Wildfires using Satellite Observations of Solar-induced Chlorophyll Fluorescence

Investigating the Effect of California Wildfires using Satellite Observations of Solar-induced Chlorophyll Fluorescence

Dr. Manju Johny, JPL Postdoctoral Fellow

Thursday, February 2 at 12 pm (PT) in 186-von Karman and via WebEx

Abstract: Recent years have seen an increase in the frequency and severity of wildfires, driven by climate change and factors such as longer and more frequent droughts, and drier soil conditions. Of particular interest is understanding the impact of fires on plant health and monitoring vegetation recovery, as these have direct implications to forest preservation and more broadly, carbon cycle dynamics.

In this talk, we study the impact of the 2018 Mendocino complex fire on vegetation in the Mendocino National Forest using solar-induced chlorophyll fluorescence (SIF), a measure of photosynthetic activity. Satellite-based estimates of SIF were obtained from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Copernicus Sentinel-5 Precursor satellite and NASA’s Orbiting Carbon Observatory-2 (OCO-2). We utilize an analysis of variance (ANOVA) for functional data to facilitate comparisons among groups of time series data with complex spatio-temporal dependence. The proposed method is applicable to various scientific domains including physical and environmental sciences, where data are often naturally ordered and exhibit spatial and temporal dependence. With the influx of available data from satellites, we highlight the benefit of leveraging these measurements to better understand a changing climate.

About the speaker: Manju Johny is a Postdoctoral Scholar in the Uncertainty Quantification and Statistical Analysis Group at JPL working on spatio-temporal modeling of remote sensing data for the Orbiting Carbon Observatory-2 mission and a NASA-sponsored MEaSUREs task. Prior to JPL, she received her PhD in Statistics from Iowa State University in 2021. She has a MS in Statistics from Iowa State University, and a BA in Chemistry and Mathematics from Saint Louis University. In her PhD dissertation, she developed analysis of variance (ANOVA) methods for functional data for comparing groups of time series with complex spatio-temporal dependence. Broadly, her research interests are in spatio-temporal modeling, machine learning, and visualization, with a desire to use statistics to better understand scientific phenomena.

WebEx Info: https://jpl.webex.com/jpl/j.php?MTID=m4e917782adff8e2da9a8105a21b01044 
Meeting number (access code): 2760 310 0238
Meeting password: 8XQvdyEcF85

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Date/Time: 
02/02/2023 - 12:00
Presenter: 
Dr. Manju Johny, JPL Postdoctoral Fellow
Location: 
186-von Karman and via WebEx