Publications for Ali Gurbuz
10 Publications
Peer-Reviewed Journals
Lei, F.,
Senyurek, V.,
Kurum, M.,
Gurbuz, A., Boyd, D.,
Moorhead, R. J., & Crow, W. T. (2022). Quasi-global Machine Learning-based Soil Moisture Estimates at High Spatio-temporal Scales Using CYGNSS and SMAP Observations.
Remote Sensing of Environment. Elsevier.
276, 113041.
DOI:10.1016/j.rse.2022.113041. [
Abstract] [
Document Site]
Senyurek, V., Lei, F., Boyd, D.,
Gurbuz, A.,
Kurum, M., &
Moorhead, R. J. (2020). Evaluations of Machine Learning-Based CYGNSS Soil Moisture Estimates against SMAP Observations.
Remote Sensing.
12(21), 3503.
DOI:10.3390/rs12213503. [
Abstract] [
Document Site]
Senyurek, V., Lei, F., Boyd, D.,
Kurum, M.,
Gurbuz, A., &
Moorhead, R. J. (2020). Machine Learning-based CYGNSS Soil Moisture Estimates over ISMN Sites in CONUS.
Remote Sensing.
12(7), 1168.
DOI:10.3390/rs12071168. [
Abstract] [
Document Site]
Peer-Reviewed Conference Papers
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]
Lei, F.,
Senyurek, V.,
Kurum, M.,
Gurbuz, A., &
Moorhead, R. J. (2021). Quasi-Global GNSS-R Soil Moisture Retrievals at High Spatio-Temporal Resolution from Cygnss and Smap Data.
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. Brussels, Belgium: IEEE. 6303-6306.
DOI:10.1109/IGARSS47720.2021.9554005. [
Abstract] [
Document Site]
Senyurek, V.,
Gurbuz, A.,
Kurum, M., Lei, F., Boyd, D., &
Moorhead, R. J. (2021). Spatial and Temporal Interpolation of CYGNSS Soil Moisture Estimations.
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. Brussels, Belgium: IEEE. 6307-6310.
DOI:10.1109/IGARSS47720.2021.9553900. [
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]
Peer-Reviewed Conference Posters
Senyurek, V., Lei, F.,
Gurbuz, A.,
Kurum, M., &
Moorhead, R. J. (2022). Machine Learning-based Global Soil Moisture Estimation Using GNSS-R.
SoutheastCon 2022. Mobile, AL, USA: IEEE. 434-435.
DOI:10.1109/SoutheastCon48659.2022.9764039. [
Abstract] [
Document Site]