Vegetation attenuation measurements and modeling in plantations for wireless sensor network planning

David Ndzi, L. Kamarudin, E. Mohammad, A. Zakaria, R. Ahmad, M. Fareq, A. Shakaff, M. Jafaar

    Research output: Contribution to journalArticlepeer-review

    248 Downloads (Pure)


    As wireless communication moves from long to short ranges with considerably lower antenna heights, the need to understand and be able to predict the impact of vegetation on coverage and quality of wireless services has become very important. This paper focuses on vegetation attenuation measurements for frequencies in the range 0.4{7.2 GHz in mango and oil palm plantations to evaluate vegetation attenuation models for application in wireless sensor network planning and deployment in precision agriculture. Although a number of models have been proposed and evaluated for specific frequencies, results show that these models do not perform well when applied to different vegetation types or at different frequencies. A global assessment of the models using a broad range of frequencies shows that the COST 235 model gives more consistent results when there is vegetation in the propagation path. For grid-like plantation, the study shows that the RET model provides the best prediction of path loss for measurements between two rows of trees. However, taking into account the limited number of parameter values available for the RET model and the potential inaccuracy that may results from the use of a wrong parameter value, a sub-optimal model which combines the ITUR model with ground reflection does offer a more consistent prediction. The differences in the average values of RMS error between RET, ITUR and free space loss models when combined with ground reflection is less than 1.6 dB.
    Original languageEnglish
    Pages (from-to)283-301
    Number of pages19
    JournalProgress in Electromagnetics Research B
    Issue number36
    Publication statusPublished - 2012


    Dive into the research topics of 'Vegetation attenuation measurements and modeling in plantations for wireless sensor network planning'. Together they form a unique fingerprint.

    Cite this