Environmental factor effects on vegetation coverage using Neural Network Modeling in central Alborz protected area

Document Type : Research Paper


1 Department of Environmental Science, Faculty of Natural Resources, University of Tehran, Karaj, Iran.

2 Department of Assessment and Environment Risks, Research Center of Environment and Sustainable Development, Iran Environmental Protection Organization, Tehran, Iran.

3 Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran.



Vegetation plays an important role in maintaining the balance of ecosystems and is considered as a significant indicator in assessing the environment of terrestrial ecosystems. ‌The coverage of vegetation is considered as one of the important characteristics for the assessment of vegetation. Vegetation changes cause disorder in the ecosystem and act as a stimulus to change the composition of species and habitat conditions. The present research was conducted with the aim of modeling the effect of human activities on the coverage of vegetation with the help of artificial neural network and determining the most effective ecological and human variables on the coverage in the central Alborz protected area under the management of Alborz province. For this purpose, after the characterizing homogeneous ecological units, 101 plant square plots with dimensions of 2 x 2 meters and 101 soil samples were collected in these units. Modeling was done using multi-layer perceptron method, the input data included soil physical and chemical variables, physiographic variables (based on management plan maps) and variables related to human factors (based on the Euclidean distance map of sampling points). According to the values ​​of the coefficient of determination in the three categories of training, validation and test data equal to 0.86, 0.79 and 0.81, the optimal structure of the model for the coverage of vegetation with a structure of 1-19-18 (18 input variables, 19 neurons in the hidden layer and one output variable) was selected. Based on the results of sensitivity analysis, slope variables, percentage of organic matter and height, the most effective variables on the abundance of vegetation in the study area were identified. The model presented in this research is used as a decision support system in assessing the effects of human activities on the coverage of vegetation in protected areas and provides the possibility of predicting the extent of these effects on the coverage of vegetation in protected areas.


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