“I had the pleasure of working closely with Mariko at JPL in multiple capacities. She served as the Capture Lead for a mission proposal I was involved in and collaborated on formulation activities across the lab. In both roles, she showcased her exceptional leadership skills by working effectively in cross-interdisciplinary teams. This skill was also evident in my volunteering alongside her for the IEEE Geoscience and Remote Sensing Society. Overall, Mariko consistently excels at leading a team, fostering an inclusive environment where everyone feels empowered to contribute. Her talent for breaking down complex problems into smaller, more manageable tasks leads to quicker and more effective solutions. She's action-oriented and consistently motivates her colleagues to reach their full potential. Furthermore, her passion for mentorship and inclusivity truly makes her a joy to work with.”
Mariko Burgin
Los Angeles, California, United States
2K followers
500+ connections
About
I have over 10 years of technical and program management experience in NASA, academic…
Experience
Education
-
University of Michigan - Rackham Graduate School
-
Activities and Societies: ECE Graduate Student Council
Dissertation: “Physics-based modeling for high-fidelity radar retrievals”
[ Available at https://deepblue.lib.umich.edu/handle/2027.42/107290 ] -
-
Activities and Societies: ECE Graduate Student Council
-
-
Activities and Societies: Pink Noise, AMIV, SOSeth
Thesis: “Ionospheric Effects on Low-Frequency Radar Signals”
Licenses & Certifications
Volunteer Experience
-
President
IEEE Geoscience and Remote Sensing Society (GRSS)
- Present 1 year 8 months
Website: http://www.grss-ieee.org/
-
Executive Vice President
IEEE Geoscience and Remote Sensing (GRSS)
- 2 years
Science and Technology
Website: http://www.grss-ieee.org/
-
Vice-President of Information Resources
IEEE Geoscience and Remote Sensing (GRSS)
- 2 years
Science and Technology
The VP for Information Resources (IR) is responsible for maintaining and enhancing the communication between the Geoscience and Remote Sensing Society and the worldwide community involved in geoscience and remote sensing activities. The IR team is responsible for the GRSS e-Newsletter, the GRSS social media outreach, and the GRSS website.
Website: http://www.grss-ieee.org/ -
IDEA (Inspire, Develop, Empower, Advance) Committee Chair
IEEE Geoscience and Remote Sensing (GRSS)
- 3 years
Science and Technology
The IDEA Committee of the IEEE Geoscience and Remote Sensing Society is tasked to Inspire, Develop, Empower, and Advance (IDEA) all GRSS members and affiliates of accredited societies who are interested in the fields of interest of the Geoscience and Remote Sensing Society (GRSS). The committee is responsible for planning and organizing activities across regions, chapters, and conferences to develop, empower, and advance engineers and scientists from diverse backgrounds (technical, regional…
The IDEA Committee of the IEEE Geoscience and Remote Sensing Society is tasked to Inspire, Develop, Empower, and Advance (IDEA) all GRSS members and affiliates of accredited societies who are interested in the fields of interest of the Geoscience and Remote Sensing Society (GRSS). The committee is responsible for planning and organizing activities across regions, chapters, and conferences to develop, empower, and advance engineers and scientists from diverse backgrounds (technical, regional, gender, etc.), and inspire members around the world to follow their technical interests to a career in geoscience and remote sensing.
Website: http://www.grss-ieee.org/community/idea -
Member of the Administrative Committee (AdCom)
IEEE Geoscience and Remote Sensing (GRSS)
- Present 6 years 8 months
Science and Technology
The Geoscience and Remote Sensing Society Administrative Committee, known as the AdCom, consists of 18 elected persons, each of whom serves for a nominal term of 3 years. Their terms are intended to be overlapping to assure continuity.
Website: http://www.grss-ieee.org/community/adcom/ -
Volunteer
Union Station Homeless Services
- Present 9 years 6 months
Poverty Alleviation
Volunteering in the kitchen to prepare meals and organizing donation drives to collect much-needed items.
Website with Union Station wishlist: https://unionstationhs.org/wishlist/
Publications
-
P-band radar retrieval of subcanopy and subsurface soil moisture profile as a second-order polynomial: First AirMOSS Results.
IEEE Trans. Geosci. Remote Sensing
We propose a new model for estimating subsurface soil moisture using P-band radar data over barren, shrubland, and vegetated terrains. The unknown soil moisture profile is assumed to have a second-order polynomial form as a function of subsurface depth with three unknown coefficients that we estimate using the simulated annealing algorithm. These retrieved coefficients produce the value of soil moisture at any given depth up to a prescribed depth of validity. We use a discrete scattering model…
We propose a new model for estimating subsurface soil moisture using P-band radar data over barren, shrubland, and vegetated terrains. The unknown soil moisture profile is assumed to have a second-order polynomial form as a function of subsurface depth with three unknown coefficients that we estimate using the simulated annealing algorithm. These retrieved coefficients produce the value of soil moisture at any given depth up to a prescribed depth of validity. We use a discrete scattering model to calculate the radar backscattering coefficients of the terrain. The retrieval method is tested and developed with synthetic radar data and is validated with measured radar data and in situ soil moisture measurements. Both forward and inverse models are briefly explained. The radar data used in this paper have been collected during the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission flights in September and October of 2012 over a 100 km by 25 km area in Arizona, including the Walnut Gulch Experimental Watershed. The study area and the ancillary data layers used to characterize each radar pixel are explained. The inversion results are presented, and it is shown that the RMSE between the retrieved and measured soil moisture profiles ranges from 0.060 to 0.099 m3/m3, with a Root Mean Squared Error (RMSE) of 0.075 m3/m3 over all sites and all acquisition dates. We show that the accuracy of retrievals decreases as depth increases. The profiles used in validation are from a fairy dry season in Walnut Gulch and so are the accuracy conclusions.
Other authorsSee publication -
On the Accuracy of Averaging Radar Backscattering Coefficients for Bare Soils Using the Finite-Element Method
IEEE Trans. Geosci. Remote Sens.
Radar backscattering coefficients for heterogeneous pixels are traditionally assumed to be the average of the coefficients for the constitutive homogeneous pixels. We investigate the validity of this assumption for bare rough surfaces by using the 2-D finite-element method to compute the ensemble averaged “true” coefficients for heterogeneous pixels and compare these values with the computed averages for a variety of surfaces. We quantify the impact of heterogeneity in both soil moisture and…
Radar backscattering coefficients for heterogeneous pixels are traditionally assumed to be the average of the coefficients for the constitutive homogeneous pixels. We investigate the validity of this assumption for bare rough surfaces by using the 2-D finite-element method to compute the ensemble averaged “true” coefficients for heterogeneous pixels and compare these values with the computed averages for a variety of surfaces. We quantify the impact of heterogeneity in both soil moisture and surface roughness on the averaging assumption. We find that the validity of the assumption rests crucially on the surface correlation type (exponential or Gaussian) and length. In particular, when considering pixels with either heterogeneous soil moisture or roughness, we find that for high-contrast pixels, the backscatter averaging assumption breaks down by as much as 11 dB for Gaussian correlated surfaces for the longest correlation lengths considered (regardless of the source of heterogeneity), whereas for exponentially correlated surfaces, it breaks down by 6 dB for pixels with heterogeneous roughness and 2 dB for pixels with heterogeneous moisture. We attribute this behavior to Gaussian correlated surfaces possessing higher cross-pixel coherent interactions. Furthermore, conditions of validity for the backscatter averaging assumption are identified.
Other authorsSee publication -
Airborne Microwave Observatory of Subcanopy and Subsurface Radar Retrieval of Root Zone Soil Moisture: Preliminary Results
Proc. IEEE Radar
We present an overview of the radar retrieval processing system for estimation of root zone soil moisture (RZSM) in several major North American biomes as one of the products of the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) project. The AirMOSS mission is briefly described along with the methodologies implemented to collect field data, to prepare several data layers required for retrievals, and to ultimately retrieve the soil moisture profiles. The retrieved soil…
We present an overview of the radar retrieval processing system for estimation of root zone soil moisture (RZSM) in several major North American biomes as one of the products of the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) project. The AirMOSS mission is briefly described along with the methodologies implemented to collect field data, to prepare several data layers required for retrievals, and to ultimately retrieve the soil moisture profiles. The retrieved soil moisture maps over several sites will be available when the radar data from AirMOSS flights are fully processed and calibrated, which is anticipated in early 2013.
Other authorsSee publication -
Potential of L-Band Radar for Retrieval of Canopy and Subcanopy Parameters of Boreal Forests
IEEE Trans. Geosci. Remote Sens.
In this paper, we study the radar retrieval of soil moisture as well as canopy parameters in a range of boreal forests. The retrieval is formulated as an optimization problem where the difference between data and prediction of a forward scattering model is minimized. The forward model is a discrete scatterer radar model, and the optimization algorithm is a global optimization scheme known as simulated annealing. The inversion method is first applied to synthetic data assuming hypothetical…
In this paper, we study the radar retrieval of soil moisture as well as canopy parameters in a range of boreal forests. The retrieval is formulated as an optimization problem where the difference between data and prediction of a forward scattering model is minimized. The forward model is a discrete scatterer radar model, and the optimization algorithm is a global optimization scheme known as simulated annealing. The inversion method is first applied to synthetic data assuming hypothetical allometric relationships to make the retrieval possible by reducing the number of unknown vegetation parameters. The inversion algorithm is then validated using the data acquired with the National Aeronautics and Space Administration (NASA)/Jet Propulsion Laboratory (JPL) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) in June 2010 in central Canada boreal forests in support of the prelaunch calibration and validation activities of NASA's Soil Moisture Active and Passive (SMAP) mission. The inversion results for synthetic data show that the absolute retrieval error in soil moisture and relative retrieval error in canopy height are small, while the relative output error in trunk density could be large. The inversion results for actual field data show a great accuracy in soil moisture retrieval for Old Jack Pine and Young Jack Pine forests but show large retrieval errors for many of the radar pixels in the Old Black Spruce site. This paper shows that L-band radar is capable of retrieving surface soil moisture in forests with a high biomass where the forest structure allows soil moisture information to be carried by scattering mechanisms.
Other authorsSee publication -
A Generalized Radar Backscattering Model Based on Wave Theory for Multilayer Multispecies Vegetation
IEEE Trans. Geosci. Remote Sens.
A generalized radar scattering model based on wave theory is described. The model predicts polarimetric radar backscattering coefficients for structurally complex vegetation comprised of multiple species and layers. Compared to conventional two-layer crown-trunk models, modeling of actual forests has been improved substantially, allowing better understanding of microwave interaction with vegetation. The model generalizes an existing single-species discrete scatterer model and, by including…
A generalized radar scattering model based on wave theory is described. The model predicts polarimetric radar backscattering coefficients for structurally complex vegetation comprised of multiple species and layers. Compared to conventional two-layer crown-trunk models, modeling of actual forests has been improved substantially, allowing better understanding of microwave interaction with vegetation. The model generalizes an existing single-species discrete scatterer model and, by including scattering and propagation effects through judiciously defined vegetation layers, enables its application to an arbitrary number of species types. The scatterers within each layer are modeled as finite cylinders or disks having arbitrary size, density, and orientation, as in the predecessor model. The distorted Born approximation is used to represent the propagation through each layer, while scattering from each is modeled as a linear superposition of scattering from its respective random collection of scatterers. Interactions of waves within and between each layer and direct scattering from the ground are accounted for. Validation of the model is presented based on its application to 23 wooded savanna sites located in Queensland, Australia, and comparison with Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) and National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) Airborne Synthetic Aperture Radar (AIRSAR) data. Results indicate good agreement between simulated and actual backscattering coefficients, particularly at HH and VV polarizations. More discrepancies are found at HV polarizations and can be explained by uncertainties in the knowledge of input parameters, such as inaccuracies in the surface model, surface roughness parameterization, and soil moisture.
Other authorsSee publication
Courses
-
Acoustics II
-
-
Analysis I, II & III
-
-
Antenna Theory & Design
-
-
Applied Mechanics
-
-
Boundary Value Problems for Partial Differential Equations
-
-
Complex Analysis & Applications
-
-
Computer Engineering I & II
-
-
Control Systems
-
-
Digital Electronics
-
-
Discrete Mathematics
-
-
Electromagnetic Theory I & II
-
-
Electronic Networks & Circuits I & II
-
-
Energy Systems with Renewable Sources
-
-
Industrial Control System Design
-
-
Informatics I & II
-
-
Information Processing in Neural Networks
-
-
Information Transfer Theory
-
-
Language Processing
-
-
Linear Algebra
-
-
Mechatronics
-
-
Microwave Circuits I & II
-
-
Microwave Measurement Lab
-
-
Microwave Remote Sensing I & II
-
-
Mobile Communication
-
-
Numerical Analysis
-
-
Numerical Electromagnetics
-
-
Physical Processes in Plasma
-
-
Physics I & II
-
-
Probability Theory & Statistics
-
-
Radiowave Propagation & Link Design
-
-
Reliability of Circuits & Systems
-
-
Remote Sensing and Inversion Theory
-
-
Semiconductor Devices
-
-
Signal & System Theory I & II
-
-
Stochastic Models & Signal Processing
-
-
Transmission Lines & Theory
-
-
Wearable Systems
-
Projects
-
Energy-efficient Wireless Sensor Network
-
In this work, Ripple-2 WSN architecture,novel hardware and cross-layer networking techniques are used to achieve an overall network overhead of less than 1% and sleep mode for both regular nodes and cluster-heads. In comparison with the state-of-the-art solutions, Ripple-2 is at least 150% more efficient in terms of energy. The solution is appropriate for data-collection application that require very long operation without maintenance (or exchange of batteries). The current solution is being…
In this work, Ripple-2 WSN architecture,novel hardware and cross-layer networking techniques are used to achieve an overall network overhead of less than 1% and sleep mode for both regular nodes and cluster-heads. In comparison with the state-of-the-art solutions, Ripple-2 is at least 150% more efficient in terms of energy. The solution is appropriate for data-collection application that require very long operation without maintenance (or exchange of batteries). The current solution is being applied for the support of the NASA SMAP Mission. Other uses: mold control of buildings (sensor installed inside the walls with 10+ years of lifetime), and wireless underground communications.
Other creatorsSee project
Honors & Awards
-
JPL Award: Earth System Explorer Proposal Team
NASA JPL
The NASA Earth System Explorer (ESE) program is a new 2-step PI-led medium-class mission opportunity designed to accomplish high-quality Earth system science investigations that address one or more of seven Targeted Observables as detailed in the Decadal Survey. The individuals provided exceptional leadership and contributions to JPL's ESE mission portfolio, going above and beyond to deliver high-quality proposals to NASA, especially in the final weeks of proposal completion and consistency…
The NASA Earth System Explorer (ESE) program is a new 2-step PI-led medium-class mission opportunity designed to accomplish high-quality Earth system science investigations that address one or more of seven Targeted Observables as detailed in the Decadal Survey. The individuals provided exceptional leadership and contributions to JPL's ESE mission portfolio, going above and beyond to deliver high-quality proposals to NASA, especially in the final weeks of proposal completion and consistency checking. They are team players, hard-working, responsible, detail-oriented, knowledgeable, and able to communicate their work thoughtfully and carefully.
-
JPL Award: IGARSS 2023 Planning Team
NASA JPL
IGARSS 2023 was the largest ever, bringing together nearly 3,000 scientists and engineers from all over the world. The team organized the technical sessions, social events, student summer school, young professional networking, and skill-building events.
-
JPL Award: OS as PCV Team
NASA JPL
-
JPL Voyager Award
NASA JPL
For significant contributions to perform A-Team and Team X remote studies since early 2020 and thereafter successfully
-
Outstanding Contribution to Promoting Women in Engineering
IEEE Metropolitan Los Angeles Section, Region 6
-
JPL Voyager Award
JPL
-
NASA Group Achievement Award: AirMOSS Team
NASA
For outstanding contributions to the AirMOSS Earth Venture Mission in understanding the impact of root-zone soil moisture on the carbon cycle and global climate variability
-
NASA Group Achievement Award: SMAP Science and Calibration/Validation Team
NASA
For contribution to the preparation of science algorithm and calibration/validation activities for the Soil Moisture Active Passive Mission
Languages
-
German, English, French, Latin
-
-
QGIS, Gamma, ENVI, TuiView, ArcGIS, PCI Geomatica, Latex
-
-
Matlab/Simulink, Ansoft HFSS/Designer, Agilent Advanced Design Systems (ADS)
-
-
Fortran, Python (GDAL, RSGISLib, Matplotlib), C/C++, Assembler
-
Organizations
-
IEEE Geoscience and Remote Sensing Society (GRSS) Administrative Committee (AdCom)
Vice-President for Information Resources
- Present -
IEEE Geoscience and Remote Sensing Society (GRSS) Administrative Committee (AdCom)
Voting member-elect
- Present -
IEEE Metropolitan Los Angeles Section Geoscience and Remote Sensing Society (GRSS) Chapter
Treasurer (2016), Vice-Chair (2017-2018), Treasurer (2019)
- Present
Recommendations received
1 person has recommended Mariko
Join now to viewOther similar profiles
Explore collaborative articles
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
Explore More