Mehmet Kurum

Beyond SMAP: Can GNSS‐R Platforms Ensure Continuity of Global Soil Moisture Observations?

Ehsan Jalilvand, Sujay V. Kumar, Rajat Bindlish, Jerry Wegiel et autres

Abstract The absence of a definitive follow‐on strategy for the Soil Moisture Active Passive (SMAP) mission, which has already surpassed its planned mission lifetime, presents a significant challenge for the hydrological science community. GNSS‐Reflectometry (GNSS‐R), which exploits reflected satellite navigation signals, has …

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Trajectory-synchronized diode laser actuation and dose-response field evaluation for precision weed control using a delta robot

Muneeb Elahi Malik, Nicholas Basinger, Mehmet Kurum, Glen Rains et autres

Weed control in Vidalia onion production is constrained by a narrow management window, where delays in intervention can result in yield losses of up to 96% in direct-seeded systems. This challenge often forces growers to rely on costly transplanting practices and labor-intensive …

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Satellite Microwave Radiometry at L-Band for Monitoring Earth’s Essential Climate Variables: From Fundamental Physics to Sixteen Years of Global Climate Observations and Beyond

Yiwen Zhou, Mike Schwank, Jacqueline Boutin, Philippe Richaume et autres

L-band satellite radiometry has emerged as an important tool for monitoring Earth’s essential climate variables (ECVs). It relies on spaceborne radiometers operating in a protected band (1.4–1.427 GHz) to measure Earth’s surface thermal microwave emission in brightness temperatures. Observations at this band …

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Collection: UAV-Based Wireless Multi-modal Measurements from AERPAW Autonomous Data Mule (AADM) Challenge in Digital Twin and Real-World Environments

Md Sharif Hossen, Cole Dickerson, Ozgur Ozdemir, Anil Gurses et autres

In this work, we present an unmanned aerial vehicle (UAV) wireless dataset collected as part of the AERPAW Autonomous Aerial Data Mule (AADM) challenge, organized by the NSF Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW) project. The AADM challenge was …

Collection: UAV-Based Wireless Multi-modal Measurements from AERPAW Autonomous Data Mule (AADM) Challenge in Digital Twin and Real-World Environments

Md Sharif Hossen, Cole Dickerson, Ozgur Ozdemir, Anil Gurses et autres

In this work, we present an unmanned aerial vehicle (UAV) wireless dataset collected as part of the AERPAW Autonomous Aerial Data Mule (AADM) challenge, organized by the NSF Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW) project. The AADM challenge was …

Impact of Non-Ideal Antenna Characteristics on VOD Retrievals for GNSS-Transmissometry

Mohammad Ehsanul Hoque, Mehmet Kurum

Global Navigation Satellite System (GNSS) transmissometry is an emerging and highly accessible technique for monitoring Vegetation Optical Depth (VOD), a critical microwave parameter that quantifies the attenuation of electromagnetic waves through a canopy. As VOD is directly proportional to Vegetation Water Content …

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Modeling and Analysis of Vegetation Effects in UAV Network Coverage Prediction with LiDAR and NVIDIA SionnaRT

Joyita Halder, Mohammad Ehsanul Hoque, Tanvir Anjum, Mehmet Kurum

Realistic simulation of radio frequency (RF) signal behavior is essential for both wireless communication and microwave remote sensing. Exact RF coverage maps for base stations and UAVs (Unmanned Aerial Vehicles) are becoming a key focus area to optimize system performance, enhance signal …

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Toward Accurate P-Band SoOp-R from UAS: Antenna Constraints and Operational Parameters

Tanvir Anjum, Mehmet Kurum

Signals-of-Opportunity Reflectometry (SoOp-R) is an innovative approach to remote sensing- removing the need for heavy, expensive transmitters or protected bandwidth. The merits of SoOp-R have been well established using ubiquitously available L-band Global Navigation Satellite System (GNSS) signals captured by spaceborne and …

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RFI-Net: Enhancing Passive Sensing Through Deep Learning-Based Time–Frequency Domain Radio Frequency Interference Detection and Mitigation

Ahmed Manavi Alam, Mehmet Kurum, Ali Cafer Gürbüz

Radio-frequency interference (RFI) poses a significant challenge to passive sensing, which relies on extremely sensitive measurements of natural thermal emissions. As radiometers increasingly operate in spectrally congested environments, often outside protected bands, accurate RFI detection becomes critical to ensure data integrity and …

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Deep Learning Framework for High-Resolution Large-Scale Vegetation Optical Depth Mapping Using Airborne LiDAR and Mobile GNSS-T Data

Abesh Ghosh, Mohammad Ehsanul Hoque, Md Mehedi Farhad, Ali Cafer Gürbüz et autres

Accurate, high-resolution mapping of Vegetation Optical Depth (VOD) is critical for assessing forest biomass, ecosystem health yet current satellite products lack the spatial detail needed to capture fine-scale heterogeneity. Ground-based GNSS Transmissometry (GNSS-T) offers meter-scale VOD mea surements but is limited in …

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Collection: UAV-Based Wireless Multi-Modal Measurements From AERPAW Autonomous Data Mule (AADM) Challenge in Digital Twin and Real-World Environments

Md Sharif Hossen, Cole Dickerson, Ozgur Ozdemir, Anil Gurses et autres

In this work, we present an unmanned aerial vehicle (UAV) wireless dataset collected as part of the AERPAW Autonomous Aerial Data Mule (AADM) challenge, organized by the NSF Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW) project. The AADM challenge was …

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A review of forward modelling and retrieval approaches for forest soil moisture and vegetation optical depth using L-band radiometry

Andreas Colliander, Mike Schwank, Yiwen Zhou, Mehmet Kurum et autres

Forests are a critical component of the Earth system, accounting for approximately one-third of global photosynthetic activity and carbon storage. They also provide essential habitats for countless species and vital resources for human activities. Low-frequency (L-band; 1–2 GHz) microwave radiometry enables the …

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