Geology topics

Mahta Moghaddam

Publications and source records attributed to Mahta Moghaddam.

4 recordsLinked to original sources

USGS2026

Development and field testing of a UAS-based software-defined radar for measuring freshwater bathymetry

We provide an overview of an uncrewed aircraft system (UAS)-based software-defined radar (SDRadar) system for high-resolution geophysical observations. The radar transceiver is implemented on a Radio Frequency System-on-Chip (RFSoC) platform, along with an ultra-wideband Vivaldi antenna that has a starting operating frequency of 150 MHz, enabling the system to be used across different applications, including measurements of freshwater bathymetry. In addition to system design and subsystem performance assessments, this paper presents the results of field testing conducted along the Sacramento River near Glenn, California, USA. The radar-derived river depth measurements are compared with ground truth data collected from a crewed boat using an acoustic Doppler current profiler (ADCP). The results show good agreement, with a root mean square error (RMSE) of 0.079 m.

California↗

USGS2025

Integration of GNSS-R derived soil moisture into the USGS Wildland Fire Potential Index

Observations of soil moisture have been found to improve predictions of fire danger as soil moisture impacts both fuel load and fuel moisture. A relative soil moisture process was developed and integrated into the USGS Wildland Fire Potential Index data products. The process uses soil moisture estimates from the CYGNSS GNSS-R constellation and compares current to historical values which then modifies the fuel moisture term in the WFPI equations. Comparisons of WFPI with the soil moisture enhanced version over known large fire events indicate a potential improvement in predicting large fire probability. The goal of this process is to identify areas prone to large fire activity that can be used to target additional CYGNSS observations to assist with wildfire monitoring.

Conference Paper↗

USGS2023

Maps of active layer thickness in northern Alaska by upscaling P-band polarimetric synthetic aperture radar retrievals

Extensive, detailed information on the spatial distribution of active layer thickness (ALT) in northern Alaska and how it evolves over time could greatly aid efforts to assess the effects of climate change on the region and also help to quantify greenhouse gas emissions generated due to permafrost thaw. For this reason, we have been developing high-resolution maps of ALT throughout northern Alaska. The maps are produced by upscaling from high-resolution swaths of estimated ALT retrieved from airborne P-band synthetic aperture radar (SAR) images collected for three different years. The upscaling was accomplished by using hundreds of thousands of randomly selected samples from the SAR-derived swaths of ALT to train a machine learning regression algorithm supported by numerous spatial data layers. In order to validate the maps, thousands of randomly selected samples of SAR-derived ALT were excluded from the training in order to serve as validation pixels; error performance calculations relative to these samples yielded root-mean-square errors (RMSEs) of 7.5–9.1 cm, with bias errors of magnitude under 0.1 cm. The maps were also compared to ALT measurements collected at a number of in situ test sites; error performance relative to the site measurements yielded RMSEs of approximately 11–12 cm and bias of 2.7–6.5 cm. These data are being used to investigate regional patterns and underlying physical controls affecting permafrost degradation in the tundra biome.

Environmental Research Letters↗

USGS2022

Snow depth retrieval with an autonomous UAV-mounted software-defined radar

We present results from a field campaign to measure seasonal snow depth at Cameron Pass, Colorado, using a synthetic ultrawideband software-defined radar (SDRadar) implemented in commercially available Universal Software Radio Peripheral (USRP) software-defined radio hardware and flown on a small hexacopter unmanned aerial vehicle (UAV). We coherently synthesize an ultrawideband signal from stepped frequency 50-MHz subpulses across 600-2100-MHz frequency bands using a novel nonuniform nonlinear synthetic wideband waveform reconstruction technique that minimizes sweep time and completely eliminates problematic grating lobes and other processing artifacts traditionally seen in stepped waveform synthesis. We image seasonal snow across two transects: a 400-m open Meadow Transect and a 380-m forested transect. We present a surface detection algorithm that fuses data from LiDAR, global navigation satellite system (GNSS)/global positioning system (GPS), and features in the radargram itself to obtain high precision estimates of both snow and ground surface reflections, and thus total snow depth, represented as two-way travel time. The measurements are validated against independent ground-based ground-penetrating radar measurements with correlations coefficients as high as ρ = 0.9 demonstrated. Finally, we compare backscattered radar data collected by the UAV-SDRadar while hovering proximal to a known snow pit with in situ measured snow dielectric profiles and demonstrate imaging of snow stratigraphy.

Colorado↗