Agro-ecological evaluation of sustainable area for citrus crop production in Ramsar District, Iran
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Date
2017-07
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Universiti Teknologi Malaysia
Abstract
Citrus growing is regarded as an important cash crop in Ramsar, Iran. Ramsar District has a temperate climate zone, while citrus is a sub-tropical fruit. Few studies on citrus crop in terms of negative environmental factors have been carried out by researchers around the world. This study aims to integrate Geographical Information System (GIS) and Analytical Network Process (ANP) model for determination of citrus suitability zones. This study evaluates the agro-ecological suitability, determine potentials and constraints of the region based on effective criteria using ANP model. ANP model was used to determine suitable, moderate and unsuitable areas based on (i) socio-economic, morphometry and hydro-climate factors using 15 layers based on experts’ opinion; (ii) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite image of the year 2003 with 98.45% overall accuracy, and (iii) developed Multiple Linear Regression (MLR) model for citrus prediction. Thereby, weighted overlay of 15 factors was obtained using GIS. In this study, the citrus orchards map of 2003 and the new map of the citrus areas of 2014 namely Citrus State Development Program (CSDP) of the study area were compared. The results of this study demonstrated: (i) suitable areas (free risk areas) based on negative environmental factors and areas which are susceptible to citrus plantation; (ii) high-risk areas which are unsuitable for citrus plantation, and (iii) the high weights derived by ANP model were assigned to altitude, frost and minimum temperature. The MLR model was successfully developed to predict citrus yield in Ramsar District by 10% error. The MLR model would propose optimum citrus crop production areas. As conclusion, the main outcome of this study could help growers and decision makers to enhance the current citrus management activities for current and future citrus planning
Description
Thesis (Ph.D (Geoinformatics))
Keywords
Geoinformation and real estate