A method for aesthetic quality modelling of the form of plants and water in the urban parks landscapes: An artificial neural network approach.

This work presents a simplified method for the application of the Multi-Layer Perceptron (MLP) model that aims to predict the aesthetic quality of the landscape designed by water and plants in different forms and volume. The MLP was prepared by (Rosenblat) in the field of computer science, followed by the application of a MLP in landscape aesthetic quality prediction proposed by (Jahani). In the method of this research, the structure of MLP was structured for aesthetic quality prediction of plants and water in urban park landscapes.

Land use change detection and impact assessment in Anzali international coastal wetland using multi-temporal satellite images.

Anzali is one of the 18 Iranian wetlands of international importance listed in Ramsar Convention. This unique ecosystem in the world with high ecological diversity is highly threatened by various factors such as pollutants, sedimentation, unauthorized development of urban infrastructure, over-harvesting of wetland resources, land use changes, and invasive species. Among which, one of the most challenging destructive factors, land use change, was scrutinized in this study.