1Department of Agronomy, Faculty of Agriculture, University of Zabol, Zabol, Iran
2Department of Remote Sensing and GIS, University of Tabriz, Tabriz, Iran
Lack of awareness of the critical factors involved in production of plants and sometimes, the cultivation of plants in areas unsusceptible to plant, can increase the amount of chemical fertilizer consumption in order to compensate the subsequent reduction of plant yield. This would increase environmental pollution. Thus, identifying of suitable areas where could supply plants initial needs of the environment is critical. For this goal, several criteria including soil conditions, climatologically indicators, topography situation and agro-climatology criteria were taken into account of modeling processing. Doing so, standardization process was performed on criteria and weighting process was performed by using of analytic hierarchy process approach. Geographical information system based on multi-criteria decision analysis was employed for weighted overlapping of indicators. Initial results indicated that East-Azerbaijan Province in the northern part of Iran has high potential for cultivating of Damask Rose. Results indicate that about 34.4% of East Azerbaijan Province has classified to be high suitability for cultivating this plant, while about 65.5 and 0.1 % of this area classified to be in the moderate and low suitability category respectively. In comparison of Damask Rose production during the 2014 and resulted analytic hierarchy process map results showed that areas with high suitability are not more under cultivation of this plant. Then, the findings of this study are great of importance for the purpose of regional planning in East-Azerbaijan Province.
Comprehensively assessment of effective factors in the growth of the Damask Rose
Using GIS- Multicriteria Decision Analysis (MCDA) approach
Importance of results for the purpose of regional planning in East-Azerbaijan province
Using large number of weather stations in compare to similar studies, for accurate inverse distance weighting
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