Rapid increase in the demand of Natural Rubber (NR) caused expansion of the rubber plantation in Thailand at a very fast rate to non-traditional and unsuitable areas with limiting conditions. These plantations produced lower yield despite more attention. This resulted in higher cost of production. At the same time, there is a rapid increase in domestic consumption of palm oil. Therefore, it is not surprising to see many rubber plantations switch to invest in oil palms now. Now it is feared that these may also expand to unsuitable areas. The objective of the study is to develop a methodology for the decision maker to replace non-suitable crop by the suitable crop. In this study the case of rubber and oil palm is considered. This was carried out using GIS and multi-factor evaluation. Analytical Hierarchical Processing (AHP) and Pairwise Comparison Method were used for factors weighting. A land potential for rubber and palm oil production are evaluate based on the crop requirements for rubber and oil palm, and climatic and physical-chemical soil properties, which will allow the prediction of yields and crop substitution between rubber and oil palm. In order to get a better agricultural production.
2. Study area and data used
Krabi province study area is situated between latitude 7 ° 22 ¢ to 8° 41¢ north and longitude 98° 21¢ to 99° 19¢ east, about 990 km from Bangkok by road. The total area is approximately 4708.51 km2. Climatic type of Krabi province is tropical monsoon climate “Am” according to Köppens’ (1931) classification described by Steele et al (1972) or “B2A’ra” (Hermid megathemal with season of litter or no water deficiency and a temperature efficiency regime normal to full megathermal) according to Thornth Waite’s classification. Annual rainfall is around 2,379.9 mm. Mean temperature is 27.4oC. Relative humidity is 80.0 %. Soil classification according to USDA soil taxonomy was recognized 5 orders namely: Spodosols, Ultisols, Alfisols, Inceptisols and Entisols.
Modified climatic and land characteristics requirements for rubber and oil palm production according to Somyot (1992), Nakorn et al. (1998) and Sutat et al. (1999). The 7 important factor such as; soil depth, soil texture, ground water table, soil drainage, organic carbon, slope and growing period or water deficit were classified into 3 classes.
GIS-database of study area including: 1. Digital soil series map, which are consist of 98-land unit and its profile description according to USDA format. Physical and chemical soil analysis of all land unit report. 2. The attribute data consist of digital slope, elevation, aspect, contour, soil data, geology, stream, transportation, factory, climatic data shape file etc.
3. The Analytic Hierarchy Process (AHP)
The purpose of weighting is to express the importance or preference of each factor relative to other factor affect on crop yield and growth rate. Since the land physical characteristics such as slope, soil texture, soil depth, ground water table depth, and soil drainage, etc., are uncorrected factors. These very severe factors should be considered as the first priority. Based on crops requirement, questionnaire with soil scientist senior researcher and experience, the multi-factor priority model was structured.
To avoid and reduce the individual biases of factor weighting, the weights in the study were determined by using a pairwise comparison method as developed by Saaty (1980) in the context of the analytical hierarchy process (AHP). Pairwise comparisons are based on forming judgments between two particular elements rather than attempting to prioritize an entire list of elements. A matrix is constructed, where each factor is compared with the other factors, relative to its importance, on a scale from 1 to 9. Then, a weight estimate is calculated and used to derive a consistency ratio (CR) of the pairwise comparisons. If the CR > 0.10, then some pairwise values needs to be reconsidered and the process is repeated till the desired value of CR < 0.10 is reached.
The pairwise comparison method showed that the consistency ratios (CR) of Rubber and Oil Palm were less than 0.1 - Rubber 0.06 and Oil Palm 0.02 (Table 1). This indicates that the comparisons of each factor were perfectly consistent, and the relative weights were suitable for use in the GIS multi-factor evaluation.
Table 1 Relative weights of factors affecting crop yield and growth rate
|| Oil Palm
|| Ground Water Table Depth
|Ground Water Table Depth
|| Soil Texture
|| Water Drainage
|| Soil Depth
|Growing period for Tree
|| Water deficit of Area
|OC (Organic Carbon)
|| OC (Organic Carbon)
|CR = 0.06
||CR = 0.02