النمذجة الخرائطية للطلب على المنتجات الزراعية في محافظة بغداد باستخدام التقانات الجغرافية الحديثة

Abstract

This research aims to model the cartographic factors affecting the demand for agricultural products in Baghdad Governorate through the use of data analysis techniques. The research seeks to identify geographical, social and economic factors that directly and indirectly affect consumer behaviour towards local agricultural products. Data collected from multiple sources, including agricultural production data, population data, and satellite imagery These data were processed using specialized geographic analysis programs to identify the spatial patterns of the influencing factors, and to develop a statistical model that links these factors to the demand for agricultural products. Cartographic modeling is a powerful tool for analyzing geospatial data and modeling complex spatial phenomena, as it is used to link spatial data with other characteristics, allowing a better understanding of spatial relationships and spatial distributions of phenomena. There are wide applications of cartographic modeling in fields as diverse as urban planning, disaster management, and environmental geography. The importance of the study was the need to identify areas of demand (consumption) in the province of Baghdad with a large population weight, as well as in order to plan for production, marketing and supply of agricultural products and adapt to future changes in agricultural land and distance from supply centres.   Arc map10.8.1 has been based on many models provided by the GIS environment One of the tools that have been relied on is the tool for calculating point and linear density kernel density line density. The density of the areas of high and low demand was calculated based on a number of criteria, namely population numbers (consumption), prices, supply centers (Alawi selling vegetables and fruits), land uses, transportation routes. One of the tools that have been relied on to calculate cartographic modeling is also  the tool  of cluster and quilter analysis, which indicates whether the apparent similarity (spatial aggregation of high and low values) or variation (extreme place value) is more pronounced than one would expect in the randomization and for each of the above variables. Aggregation tools and outliers are powerful tools that help analyze agricultural data and understand the factors affecting the demand for agricultural products, contributing to better decision-making and improving efficiency in the agricultural sector. The study found that cartographic modeling methods contribute to drawing a picture of geographical analysis to study the factors affecting the demand for agricultural products in Baghdad Governorate and identify areas with high and low demand can identify areas that witness high demand for certain agricultural products, which helps in better production and marketing planning. Detection of spatial relationships between influencing factors and demand shows strong spatial relationships between different factors, such as the relationship between high income and demand for organic products, can be detected.