Abstract:
Information technology and computers in agriculture for the sustainable use and management of agricultural land in decision-making facilities reduce time consumption and accuracy. The goal of this research is to investigate the importance of integrating soil-type details into decision-making procedures to achieve sustainability and efficient utilization of agricultural lands; therefore, the AGLA was designed to achieve the aforementioned aim. The AGLA design adopts a toolkit methodology; that incorporates software components such as models, and geographic information system (GIS) applications. Microsoft Visual Studio was used to construct an algorithm developed using C# programming language to analyse the data. This algorithm facilitates the assessment of environmental conditions and determination of evaluation classes for various crops based on specific criteria. The key steps in the data analysis process included data preparation and evaluation class assignment. The results of the models can be obtained as PDF reports and an Excel spreadsheet in (CSV) format with coordinates linked to a shapefile in the ArcGIS map program that helps to extract evaluation maps. The models were tested in a previous PhD study and compared to the MicroLEIS web version. AGAL can be improved by adding more features to existing models and by designing additional models.A case study have been selected to evaluated the land suitability using the AGLA application, The study focus on Akre district plane in Iraq covering approximately 714.87 Km2considered as a food basket for wide ranges areas. The aim of this study was to classify the land suitability of the study area and identify the most suitable crops for this area. Land suitability was determined based on the interaction of various topological, physical, chemical and climate analyses from twenty profiles collected from different landscapes. These analyses were processed using the AGLA model. The results were compiled into Excel sheet file (.csv.MS_DOS) that can be integrated to ArcGIS as a points. Suitability classes were determined for wheat, barley, rice, beans, tomato, lentil, nuts, almond and olive. In total the mean of suitability classes for the study area were class S1: the suitable lands were 98.51 Km2about 13.76 %, Class S2: the moderate suitable lands were 491.31 Km 2about 68.63
%, Class S3: the low suitable lands were 111.68 Km2about 15.6 % and Class N: non suitable or marginal lands were 14.37 Km2 about 2.01 %.
