RESEARCH ARTICLE

Journal of Oil Palm Research Vol. 33 (1) March 2021, p. 84-92

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

ALBERTO MARTINEZ*; JAMES J CAMBERATO*; PHILLIP OWENS** and JENETTE ASHTEKAR*

DOI: https://doi.org/10.21894/jopr.2020.0092
Received: 8 July 2019   Accepted: 12 June 2020   Published Online: 27 October 2020
ABSTRACT

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 􏰆uantifying topography-driven variability of soil properties within oil palm plantations. The shutter radar topography mission (􏰏RTM) global digital elevation model (􏰈DEM) 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 (M􏰌􏰐)􏰑 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:

FIGURES & TABLES:

* Purdue University,
403 West State Street, West Lafayette,
Indiana 47907-2050, USA.
E-mail: mart1142@purdue.edu

** Agricultural Research Service,
US Department of Agriculture,
Dale Bumpers Small Farms Research Centre,
6883 South Highway 23,
Booneville AR 72927, Arkansas, USA


Arabelos, D (2000). Intercomparisons of the global DTMs ETOPO5, TerrainBase and JGP95E. Physics and hemistry of the Earth Part olid Earth and eodesy, 25: 8993.

Ashtekar, J M and Owens, P R (2013). Remembering knowledge: An expert knowledge based approach to digital soil mapping. oil orions ol. 5: 16.

Ashtekar, J M; Owens, P R; Brown, R A; Winzeler, H E; Dorantes, M; Libohova, Z; Dasilva, M and Castro, A (2014). Digital mapping of soil properties and associated uncertainties in the Llanos Orientales, South America. obaloilMap asis of lobal patial oil Information ystem (Arrouays, D; McKenzie, N; Hempel, J; Richer de Forges, A and McBratney, A eds.). CRC Press, Boca Raton, FL, SA. p. 367372.

Bhner, J and Selige, T (2006). Spatial prediction of soil attributes using terrain analysis and climate regionalisation. öttinger eographische bhandlungen, 115: 1328.

Carr, M K V (2011). The water relations and irrigation requirements of oil palm (Elaeis guineensis): A review. Eperimental griculture, : 629652.

Corley, R H V and Tinker, P B (2008). The Oil Palm. 5th Edition. John Wiley Sons, Hoboken, New
Jersey. 674 pp.

Fedepalma, C (2016). Mejores prcticas agroindustriales para una excelente palmicultura. oletn El Palmicultor, (53 oviem): 1718.

Florinsky, I (2016). Digital Terrain nalysis in oil cience and eology. 2nd Edition. Academic Press,
London, K. 475 pp.

Fox, J (2005). Getting started with the R commander: A basicstatistics graphical user interface to R. J. tat. oftw., 14: 142.

Henson, I E; Harun, M H and Chang, K C (2008). Some observations on the efects of high water tables and fooding on oil palm and a preliminary model of oil palm water balance and use in the presence of a high water table. Oil Palm ulletin o. 5 1422.

Hofmann, M P; Vera, A C; Van Wijk, M T; Giller, K E; Oberthr, T; Donough, C, and Whitbread, A M (2014). Simulating potential growth and yield of oil palm (Elaeis guineensis) with PALMSIM: Model description, evaluation and application. gricultural ystems, 131: 110.

Instituto Geogrfco Agustn Codazzi (IGAC) (2014). Estudio general de suelos y onifcacin de tierras Departamento de asanare. Bogot, D.C., Colombia.

Iqbal, J; Thomasson, J A; Jenkins, J N; Owens, P R and Whisler, F D (2005). Spatial variability analysis of soil physical properties of alluvial soils. oil ci. oc. m. . : 13381350.

Jenson, S K and Domingue, J O (1988). Extracting topographic structure from digital elevation data for geographic information system analysis. Photogrammetric Engineering and Remote ensing, 5: 15931600.

Jiang, P and Thelen, K D (2004). Efect of soil and topographic properties on crop yield in north central cornsoybean cropping system. gron. . : 252258.

Jipp, P H; Nepstad, D C; Cassel, D K and De Carvalho, C R (1998). Deep soil moisture storage and transpiration in forests and pastures of seasonally dry Amazonia. Potential Impacts of limate hange on Tropical Forest Ecosystems. Springer, Dordrecht. p. 255272.

Kaspar, T C; Colvin, T S; Jaynes, D B; Karlen, D L; James, D E; Meek, D M; Pulido, D and Butler, H (2003). Relationship between six years of corn yields and terrain attributes. Prec. gric. : 87101.

Lee, W K and Ong, B K (2006). The unseen food: Waterlogging in large oil palm plantations. Jurutera (January 200): 2831.

Marin, S and Ramirez, J A (2006). The response of precipitation and surface hydrology to tropical macroclimate forcing in Colombia. ydrological Processes, 20: 37593789.

Maestrini, B and Basso, B (2018). Drivers of within feld spatial and temporal variability of crop yield across the S Midwest. ci. Reports : 19.

Mfondoum, A H N; Mfondoum, R B N; Wokwenmendam, P N; Gbetkom, P G and Ntengo, M (2019). Modeling best oil palm site planting in Njimom, WestCameroon: A GISanalysis combining weighted linear combination, fuzzy analytical hierarchy process and utility function. . eographic Info. yst. 11: 138165.

Nikolakopoulos, K G; Kamaratakis, E K and Chrysoulakis, N (2006). SRTM vs. ASTER elevation products. Comparison for two regions in Crete, Greece. Int. . Remote ensing 2: 48194838.

Odeh, I O A; Chittleborough, D J and McBratney, A B (1991). Elucidation of soillandform interrelationships by canonical ordination analysis. eoderma., : 132.

Paramananthan, S (2000). Soil requirements of oil palm for high yields. Managing Oil Palm for igh ields gronomic Principles. Malaysian Society of Soil Science and Param Agricultural Surveys, Kuala Lumpur. p. 1838.

Pirker, J; Mosnier, A; Kraxner, F; Havlk, P and Obersteiner, M (2016). What are the limits to oil palm expansion? lobal Environmental hange, 0: 7381.

Quinn, P; Beven, K and Lamb, R (1995). The In (a/ tan/) index: How to calculate it and how to use it within the Topmodel framework. ydrological Processes, : 161182.

Simmons, F W; Cassel, D K and Daniels, R B (1989). Landscape and soil property efects on corn grain yield response to tillage. oil ci. oc. m. . 53: 534 539.

Zhang, N (2004). Comparative analysis of drainage networks derived from gridbased DEM. dvances in cience and Technology of ater Resources, 3: 110115.