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Application of Geographic Information System for Potential Productivity Evaluation of Lowland Rice Area in Chachoengsao Province, Thailand
Dissertation Abstract:
The study adopted the United Nations Food and Agriculture Organization (FAO) and SoiI Taxonomy frameworks as the concepts for land evaluation and productivity ratings. Land suitability classification and productivity evaluation of lowland rice areas were conducted using spatial and non-spatial data on soil. land use, and climate from secondary data, field survey, and laboratory analysis. These data were encoded. stored, analyzed. and manipulated to generate the desired information with the aid of a Geographic Information System (GIS) called Spatial Analysis System (SPANS). The results presented both spatial and nonspatial information. Important information included land suitability map and inherent and potential productivity maps for lowland rice plantations. The SPANS GIS processing displayed these maps in terms of geographic images with other map elements that complement the geographic maps.
The land suitability map was created based on 10 land qualities recommended by the Department of Land Development in Thailand. Most of the lowland rice areas (28.73% of the total area) were classified under moderately suitable (S2) for lowland rice production. The inherent productivity map, using the FAO approach, showed similar results where about 28.73 percent of the lowland rice areas of the province were identified under class 2. Also, the potential productivity evaluation showed that all areas classified under class 2 could be improved to productivity class 1 (excellent productivity) with proper inputs.
Productivity ratings based on Soil Taxonomic framework were generally higher than the FAO approach, resulting in higher predicted yields. Areas with inherent excellent productivity (class 1) constituted about 28.34 percent and could be raised to 39.32 percent with proper management.
The validation of the GIS processing revealed that in both FAO and Soil Taxonomy approaches, the predicted inherent yields were high in relation to the actual yields obtained by the farmers, with coefficients of correlation computed at 0.64 and 0.70, respectively.
The GIS technology could provide capabilities for land evaluation as well as productivity assessment for rice production. It not only rapidly organizes or analyzes the spatial data, it also gives greater accuracy in obtaining them. In addition, the storage of information in a GIS means that the data do not become stagnant once the task is completed but can be re-used to evaluate future or alternative development proposals.