Mapping the Suitability of Planting Rubber Tree under Different Climatic Conditions

Constantino G. Medilo Jr., Alejandro F. Tongco, Rissa Fe M. Yuag


ThepapermapsthesuitabilityofplantingrubbertreeintheprovinceofSouthernLeyteusing different planting requirements under four types of climatic conditions through Quantum Geographic Information System or QGIS. Furthermore, this study tries to determine the size of areas in the province suitable for planting rubber tree under the four conditions and determine if there are significant variations. The use of QGIS in mapping the suitability and determining the size of the areas of the different suitability categories under various climatic conditions provided a clear picture of the fitness of planting rubber trees in the province. Analysis of variance was used to determine if there are significant differences in size of areas suitable for farming rubber tree under different climatic conditions. Results showed that the size of areas under different suitability categories significantly differed. Further, the size of the areas under different suitability categories also considerably varied under various climatic conditions where the more significant change is seen with the inclusion of flooding and landslide into the mapping. This study concluded that rubber tree cultivation in Southern Leyte is affected by different climatic conditions but most significantly by natural hazards like flooding and landslide.


Geophysical hazards,cultivation,investment, environmental sciences

Full Text:



Al-shalabi, M., Billa, L., Pradhan, B., Mansor, S., & Al-Sharif, A. A. (2013). Modeling urban growth evolution and land-use changes using GIS-based cellular automata and SLEUTH models: the case of Sana’a metropolitan city, Yemen. Environmental Earth Sciences, 70(1), 425-437.

Bathrellos, G. D., Gaki-Papanastassiou, K., Skilodimou, H. D., Papanastassiou, D., & Chousianitis, K. G. (2012). Potential suitability for urban planning and industry development using natural hazard maps and geological–geomorphological parameters. Environmental Earth Sciences,66(2),537-548.

Department of Agriculture, Philippines. (2013). Rubber. Retrieved from December2016

Department of Agriculture, Rubber Tree Investment Guide. Retrieved from

Fox, J., & Castella, J. C. (2013). Expansion of rubber (Hevea brasiliensis) in Mainland Southeast Asia: what are the prospects for smallholders? The Journal of Peasant Studies,40(1),155-170.

Gbanie, S. P., Tengbe, P. B., Momoh, J. S., Medo, J., & Kabba, V. T. S. (2013). Modelling landfill location using geographic information systems (GIS) and multi-criteria decision analysis (MCDA): case study Bo, Southern Sierra Leone. AppliedGeography,36,3-12.

Moss, R., Babiker, W., Brinkman, S., Calvo, E., Carter, T., Edmonds, J., & Jones, R.N. (2008). Towards new scenarios for the analysis of emissions: Climate change, impactsandresponsestrategies.

Rikalovic, A., Cosic, I., & Lazarevic, D. (2014). GIS based multi-criteria analysis for industrial site selection. Procedia Engineering,69,1054-1063.

Rodier, D., & Norton, S. (1992, February). Framework for ecological risk assessment. Environmental Protection Agency, Washington, DC (United States). Risk AssessmentForum.

Wayne, G. P. (2013). The beginner’s guide to representative concentration pathways. SkepticalScience,25


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.