A review of remote sensing based productivity models and their suitability for studying oil palm productivity in tropical regions

Kian Pang Tan, Kasturi Devi Kanniah, Arthur Philip Cracknell

    Research output: Contribution to journalReview articlepeer-review

    27 Citations (Scopus)


    Oil palm (Elaeis guineensis Jacq.) cultivation has been expanding and has become one of the fastest developing agricultural crops in tropical regions. Therefore, it is critical to understand the carbon balance and dynamics within oil palm estates to determine its role in the global carbon cycle. Estimating oil palm productivity on a large scale is most feasible with remote sensing based models. Thus, the objective of this paper is to review existing remote sensing based models (i.e. CASA, GLO-PEM, VPM, C-Fix, TURC, EC-LUE, VI, TG, 3-PGS and MOD17) that use light use efficiency (LUE) logic, and subsequently to evaluate the suitability of these models for estimating oil palm productivity. This paper also highlights the limitation of current remote sensing based models for estimating oil palm productivity. From the review of existing literature, it is clear that the existing remote sensing based models need to be modified in terms of meteorological inputs, maximum LUE and environmental constraints in order to improve the estimation of oil palm productivity.

    Original languageEnglish
    Pages (from-to)655-679
    Number of pages25
    JournalProgress in Physical Geography
    Issue number5
    Publication statusPublished - Oct 2012

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