Journal of Oil Palm Research Vol.   p.  
DOI: https://doi.org/10.21894/jopr.2020.0092

USING TERRAIN ALGORITHMS ON A DIGITAL ELEVATION MODEL TO EVALUATE YIELD VARIABILITY IN OIL PALM

Author(s): ALBERTO MARTINEZ*; JAMES J CAMBERATO*; PHILLIP OWENS** and JENETTE ASHTEKAR*

Oil palm (Elaeis guineensis Jacq.) plantations face strong pressure to improve fertiliser-use efficiency. Digital soil mapping methods based on topographic analysis using globally-available digital elevation models (DEM) provide an efficient means of quantifying topography-driven variability of soil properties within oil palm plantations. The shutter radar topography mission (SRTM) global digital elevation model (GDEM) was used as the basis for modeling topography across an individual oil palm plantation. Terrain algorithms were used to model terrain attributes and generate continuous soil property maps along topographic soil classes in conjunction with georeferenced soil samples as model inputs. The resulting raster layers of soil property values were evaluated for mean error and their correlation to yield variability across the plantation. Modified catchment area (MCA), an iterative measure of a landscape position represented by a grid cell’s propensity to lose or gain soil water, was found to have a strong effect on yield, suggesting that soil moisture distribution was an important driver of yield variability in this system

Keywords: , , , ,

Author Information
* Purdue University - Agronomy 610 Purdue Mall , West Lafayette, Indiana 47907-2050 United States.
E-mail: mart1142@purdue.edu

** USDA ARS Booneville, Arkansas United States.


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