Exploring suitability for tropical crop cultivation in Hainan Island by SOTAL methodology

来源 :Journal of Geographical Sciences | 被引量 : 0次 | 上传用户:teiku
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A SOTER-based automatic procedure for qualitative land evaluation is developed. This procedure was created in the automated land evaluation system (ALES). The objective was to design a procedure that allows for a quick separation of potentially suitable from non-suitable SOTER units for the intended land use, indicating constraints to different kinds of land use. Different kinds of land are unequal1y suited to various uses, land eva1uation is the assessment of the suitability of a tract of land for a specified kind of land use. In practice this implicates the comparison (matching) between the requirements of a specified land use and the properties of the land. Land evaluation concepts and definitions are treated in the paper. The ALES is a computer program that allows land evaluators to build their own knowledge-based system with which they can compute the physical and economical suitability of map units in accordance with FAO framework for land evaluation. The ALES program works with so-called decision trees, being hierarchical multiway keys in which the leaves are results (e.g., severity levels of land qualities), and the interior nodes of the tree are decision criteria (e.g., land characteristic values). These trees are traversed by the program to compute an evaluation using actual land data for each map unit. SOTAL is a SOTER-based qualitative model developed in ALES for physical land evaluation in which presently three land utilization types (LUTs) are distinguished, i.e., cultivated banana, coffee and rubber under different input and technological conditions. These LUTs are characterized by 11 landuse requirements and evaluated by matching the land use requirements with the corresponding land qualities. The paper elaborates on the criteria used in SOTAL for land quality assessment and how a final suitability rating is achieved on the basis of the rated land qualities. Results are visualized through G1S-generated maps as products in response to the specific information and data needs of decision and policy makers. This procedure was created in the automated land evaluation system (ALES). The objective was to design a procedure that allows for a quick separation of potentially suitable non-suitable SOTER units for the intended land use, indicating constraints to different kinds of land use. different types of land are unequal1y suited to various uses, land eva1uation is the assessment of the suitability of a tract of land for a specified kind of land use. In practice this implicates the comparison (between) the requirements of a specified land use and the properties of the land. Land evaluation concepts and definitions are treated in the paper. The ALES is a computer program that allows land evaluators to build their own knowledge-based system with which they can compute the physical and economical suitability of map units in accordance with the FAO framework for land evaluation. The ALES program works with so-called decision trees, being hierarchical multiway keys in which the leaves are results (eg, severity levels of land qualities), and the interior nodes of the tree are decision criteria (eg, land characteristic values). These trees are traversed by the program to compute an evaluation using actual land data for each map unit. SOTAL is a SOTER-based qualitative model developed in ALES for physical land evaluation in which presently three land utilization types (LUTs) are distinguished, ie, cultivated banana, coffee and rubber under different input and technological conditions. These LUTs are characterized by 11 landuse requirements and evaluated by matching the land use requirements with the corresponding land qualities. The paper elaborates on the criteria used in SOTAL for land quality assessment and how a final suitability rating is achieved on the basis of the rated land qualities. Results are visualized through G1S-generated maps as products in response to the specific information and data needs of decision and policy makers.
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