Publications for: Ali GurbuzPeer-Reviewed Journals
Senyurek, V., Lei, F., Kurum, M., & Gurbuz, A. (2023). Quasi-Global Assessment of Deep Learning-Based CYGNSS Soil Moisture Retrieval. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. IEEE. 16, 5629-5644. DOI:10.1109/JSTARS.2023.3287591. [Abstract] [Document Site]
Senyurek, V., Farhad, M. M., Gurbuz, A., Kurum, M., & Adeli, A. (2022). Fusion of Reflected GPS Signals With Multispectral Imagery to Estimate Soil Moisture at Subfield Scale From Small UAS Platforms. Journal of Selected Topics in Applied Earth Observations and Remote Sensing. IEEE. 15, 6843-6855. DOI:10.1109/JSTARS.2022.3197794. [Abstract] [Document Site]
Senyurek, V., Farhad, M., Gurbuz, A., Kurum, M., & Moorhead, R. J. (2022). SoilMoistureMapper: a GNSS-R Approach for Soil Moisture Retrieval on UAV. UAAAI-22 AI for Agriculture and Food Systems (AIAFS) Workshop. Vancouver, BC (Canada). [Abstract] [Document Site]
Kurum, M., Gurbuz, A., Barnes, S., Boyd, D. R., Farhad, M., & Senyurek, V. (2021). A UAS-based RF Testbed for Water Utilization in Agroecosystems. Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VI. Proc. SPIE 11747: International Society for Optics and Photonics. 11747, 117470J. DOI:10.1117/12.2591895. [Abstract] [Document Site]
Lei, F., Senyurek, V., Boyd, D., Kurum, M., Gurbuz, A., & Moorhead, R. J. (2020). Machine-Learning Based Retrieval of Soil Moisture at High Spatio-Temporal Scales Using CYGNSS and SMAP Observations. IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium. International Geoscience and Remote Sensing Symposium: IEEE. 4470-4473. DOI:10.1109/IGARSS39084.2020.9323106. [Document Site]