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Integration of RS, GIS and AHP for Hanoi Peri-Urban Agriculture Planning  Rajesh B. THAPA, MSc. Specialization: Geography Remote Sensing and Geographic Information System. Research Assistant STAR Program School of Advanced Technologies Asian Institute of Technology, Thailand Tel: +66-2-524-6406 Fax: +66-2-524-5597 Email: rajesh@ait.ac.th  Frederic BORNE, PhD Specialization: Image Analysis Image Processing, Texture Analysis 3D Landscape Modeling, Linkage between plant growth modeling and RS/GIS applications Assistant Professor CIRAD-France Centre de Coopération Internationale en Recherche Agronomique pour le Développement Département AMIS, Amélioration des Méthodes pour l’Innovation Scientifique Programme AMAP, Modélisation de l’Architecture des Plantes  Michiro, KUSANAGI, PhD Specialization: Aerospace System Engineering Space System Engineering Visiting Professor/Coordinator STAR Program School of Advanced Technologies Asian Institute of Technology, Thailand Tel: +66-2-524-5577 Fax: +66-2-524-5597 Email: kusanagi@ait.ac.th  Pham Van CU, PhD Specialization: Geomorphology GIS and Remote Sensing Professor/Director Institute of Geology National Center for Sciences and Technology, Vietnam Tel: +84-4-83-51493 Fax: +84-4-83-59335 Email: phamvancu@hn.vnn.vn Abstract An integration of GIS and AHP for peri-urban agriculture planning prevails a very interesting decision scenario to Hanoi provincial agriculture planners. The research was carried out on Hanoi peri-urban area, which is a result of integrated techniques of RS, GIS and AHP. Hanoi province has 46% of arable land that can be managed in getting optimum benefits from available resources giving environmental security to the people. In this study, five parameters namely land use, soil, road linkage, water resource linkage and market linkage have been chosen for peri-urban agriculture planning. The 30-meter resolution Landsat ETM+ image, topographic map, soil map, market baseline survey data and GPS ground truth data were used. These five parameters were scaled as Very Good, Good, Fair and Unarable as per their strengths. The AHP method was applied for judging the parameters and computing the priority index to each parameter. The baseline survey claims, the peri-urban districts of the province served 59% of vegetables to city center. The 30-meter grid based spatial analysis was worked out. Using linear combination method, the province has Unarable (56%) and the arable land as Very Good (32%), Good (12%) and Fair (2%) for the peri-urban agriculture. The arable land and unarable land further analyzed at commune level. This scenario might help the peri-urban planners and decision-makers for taking action on various decisions at different levels. |