Integration of artificial neural network and geographical information system for intelligent assessment of land suitability for the cultivation of a selected crop

The main objective of this study is to investigate the potential of artificial neural network (ANN) for integration with geographical information system (GIS) to assess the suitability of land to cultivate a selected crop. For this purpose, requirements of a system for intelligent assessment of land suitably were determined and the architecture of the integrated system was designed according to capabilities of ANN and GIS. For evaluation of the integrated system performance, a case study was carried out in the Mazandaran Province, located in the northern part of Iran. In the system implemented for the case study, four effective parameters in crop cultivation were utilized in the multilayer feed-forward back-propagation neural network analysis. The activation function of the hidden layer was set to log-sigmoid function. Designed ANN was trained using the samples extracted from GIS database, and 4-6-1 (4 input parameters as input layer, 6 neurons in hidden layer and 1 target value representing suitability level) structure shows the best result. Evaluation of the system shows that 83.43 % of ANN's results are acceptable and consistent with the real world.