Dr Muhammad Moshiur Rahman

Research Fellow, Precision Agriculture - Precision Agriculture Research Group (PARG); School of Science and Technology

Muhammad Moshiur Rahman

Phone: +61 2 6773 1491

Email: mrahma37@une.edu.au

Biography

Research Fellow
Precision Agriculture Research Group (UNE PARG)

Moshiur Rahman is a Research Fellow in Precision Agriculture within the School of Science and Technology at the University of New England (UNE). His research interest lies in the monitoring, analysis and forecast of land surface environmental variables and processes using remote sensing techniques coupled with physical modelling. He is also interested in 3D modelling using structure from motion (SFM) from UAV platform. In particular his main expertise resides in the use of proximal and active optical sensors including CropCircle, Quantum Bar Sensor, Radiometer, Time domain Reflectometry (TDR) etc. He has enough knowledge on electromagnetic induction sensors (mainly EM38), geographic information system (GIS) and remote sensing (RS). In his PhD he used proximal and optical remote sensors to estimate pasture growth rate (PGR) as decision support tools for the Graziers in Australia.

Qualifications

MSc (Agricultural and Bioresource Engineering), Wageningen University, The Netherlands
PhD (Precision Agriculture), University of New England, Australia

Memberships

International Society of Precision Agriculture

Publications

Selected Recent Publications

M. M. Rahman, D. W. Lamb, M J. N. Stanley (2015). The impact of solar illumination angle when using active optical sensing of NDVI to infer fAPAR in a pasture canopy. Agricultural and Forest Meteorology, Vol – 202, P. 39 – 43

M. M. Rahman, D. W. Lamb, M J. N. Stanley,. G. Trotter (2014) NDVI ‘depression’ in pastures following grazing. The 12th International conference in Precision Agriculture. Sacramento, California, USA 20-23 July 2014

M. M. Rahman,  D. W. Lamb, M J. N. Stanley,. G. Trotter (2014) Use of proximal sensors to evaluate at the sub-paddock scale a pasture growth-rate model based on light-use efficiency. Crop and Pasture Science. Vol – 65, No – 4, P. 400-409

M. M. Rahman,  J. N. Stanley, D. W. Lamb, M. G. Trotter (2014) Methodology for measuring fAPAR in crops using a combination of active optical and linear irradiance sensors: a case study in Triticale (X Triticosecale Wittmack). Precision Agriculture. Vol – 15, P. 532-542

Related Links

For more information on publications please see:

Researchgate profile

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