Abstract
Modelling the spatial distribution of plants is one of the indirect methods for predicting the properties of plants and can be defined based on the relationship between the spatial distribution of vegetation and environmental variables. In this article, we introduce a new method for the spatial prediction of the dominant trees and species, through a combination of environmental and satellite data. Based on the basal area factor (BAF) frequency for each tree species in a total of 518 sample plots, the dominant tree species were determined for each plot. Also, topographical maps of primary and secondary properties were prepared using the digital elevation model (DEM). Categories of soil and the climate maps database of the Doctor Bahramnia Forestry Plan were extracted as well. After pre-processing and processing of spectral data, the pixel values at the sample locations in all the independent factors such as spectral and non-spectral data, were extracted. The modelling rates of tree and shrub species diversity using data mining algorithms of 80% of the sampling plots were taken. Assessment of model accuracy was conducted using 20% of samples and evaluation criteria. Random forest (RF), support vector machine (SVM) and k-nearest neighbor (k-NN) algorithms were used for spatial distribution modelling of dominant species groups using environmental and spectral variables from 80% of the sample plots. Results showed physiographic factors, especially altitude in combination with soil and climate factors as the most important variables in the distribution of species, while the best model was created by the integration of physiographic factors (in combination with soil and climate) with an overall accuracy of 63.85%. In addition, the results of the comparison between the algorithms, showed that the RF algorithm was the most accurate in modelling the diversity.
Highlights
The forests of Iran cover an area of about 12.4 million ha, comprising 7.4% of the country’s area [1].Of the five vegetation regions, the most important according to forest density, canopy cover and diversity, is the Hyrcanian (Caspian) region [2]
The Random forest (RF) algorithm had a slightly higher performance
The best overall accuracy was obtained using a combination of topography, soil and climate factors
Summary
The forests of Iran cover an area of about 12.4 million ha, comprising 7.4% of the country’s area [1]. Of the five vegetation regions, the most important according to forest density, canopy cover and diversity, is the Hyrcanian (Caspian) region [2]. In forest ecosystems, trees and shrubs are living either independently (individually) or in association with each other, where some species are dominant over other species based on different biotic and non-biotic factors, comprising a stand with an area larger than 0.5 hectare or group species with an area smaller than 0.5 hectare. Forest stand types or dominant trees and shrubs species mapping is one of the most important ways to manage and protect plant communities. Information about dominant tree species is required to assess forest resilience and vulnerability to any threat, for instance, drought and pathogens [3].
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