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Land Suitability Analysis for Orange &Pineapple: A Multi Criteria Decision Making Approach Using Geo Spatial Technology

Land Suitability Analysis for Orange &Pineapple: A Multi Criteria Decision Making Approach Using Geo Spatial Technology
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摘要 Land evaluation procedure given by FAO for soil site suitability for various land utilization types for rainfed agriculture has been used to assess the land suitability for khasi mandarin orange and pineapple in East Khasi Hills District of Meghalaya. The database on soil and land use/land cover was generated from IRS-P6 remote sensing satellite data, soil survey and laboratory analysis of soil samples to perform an integrated analysis in the Geographic Information System environment. Different soil chemical parameters and physical parameters were considered to evaluate soil site suitability for orange & pineapple. Different thematic layers were derived from soil map by using ArcGIS software. Subsequently all of them were overlaid and integrated in GIS environment and suitability criteria was applied to the resulted composite map and generated land suitability map for orange and pineapple. The result indicated that the soil sites of the study area are highly to marginally suitable for mandarin orange whereas it is marginally suitable for pineapple. The study reveals that highly suitable areas for orange are found in the Cherapunjee and Mawsynram area that covers 34.5 Sq.Km areas. Moderately suitable (37% of TGA) and marginally suitable (24% of TGA) areas are found only because of slope constraint (8%-30% slope). The hills with deep gorges and ravines on the southern portion of the district is found not suitable for orange plantation because of steep slopes (>30%) and stoniness. Land suitability analysis for pineapple showed that 81% area of total geographical area of the district is marginally suitable and 19% area is not suitable to support the crop. The district is marginally suitable because of topography (slope and erosion), soil fertility (base saturation and CEC) and climate. Land evaluation procedure given by FAO for soil site suitability for various land utilization types for rainfed agriculture has been used to assess the land suitability for khasi mandarin orange and pineapple in East Khasi Hills District of Meghalaya. The database on soil and land use/land cover was generated from IRS-P6 remote sensing satellite data, soil survey and laboratory analysis of soil samples to perform an integrated analysis in the Geographic Information System environment. Different soil chemical parameters and physical parameters were considered to evaluate soil site suitability for orange & pineapple. Different thematic layers were derived from soil map by using ArcGIS software. Subsequently all of them were overlaid and integrated in GIS environment and suitability criteria was applied to the resulted composite map and generated land suitability map for orange and pineapple. The result indicated that the soil sites of the study area are highly to marginally suitable for mandarin orange whereas it is marginally suitable for pineapple. The study reveals that highly suitable areas for orange are found in the Cherapunjee and Mawsynram area that covers 34.5 Sq.Km areas. Moderately suitable (37% of TGA) and marginally suitable (24% of TGA) areas are found only because of slope constraint (8%-30% slope). The hills with deep gorges and ravines on the southern portion of the district is found not suitable for orange plantation because of steep slopes (>30%) and stoniness. Land suitability analysis for pineapple showed that 81% area of total geographical area of the district is marginally suitable and 19% area is not suitable to support the crop. The district is marginally suitable because of topography (slope and erosion), soil fertility (base saturation and CEC) and climate.
出处 《Journal of Geographic Information System》 2014年第1期40-44,共5页 地理信息系统(英文)
关键词 Khasi MANDARIN ORANGE PINEAPPLE Site SUITABILITY ANALYSIS Soil SLOPE Remote Sensing GIS Khasi Mandarin Orange Pineapple Site Suitability Analysis Soil Slope Remote Sensing GIS
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