Direct measurement of aboveground biomass of trees is considered as one of the labor-intensive, expensive, time consuming and destructive tasks. The objective of this study was to estimate the biomass of four coniferous and deciduous trees species (Pinus eldarica, Cupressus arizonica, Robinia pseudoacacia and Morus alba) by means of high resolution Quickbird remotely-sensed data of over a plantation are established around the industrial domain of Isfahan’s Mobarakeh Steel Company. To this aim, three approaches based on vegetation indices, texture analysis and Principal Component Analysis (PCA) were applied to extract required information from satellite imagery. The correlation analysis between field-assessed biomass and the image-based information and regression models were built. The results using vegetation indices (DVI and NDVI) for coniferous species as well as athose from texture analysis and PCA for deciduous species showed significant corelations. As depicted by the species-specific regression of biomass revealed the amount of RMSE ​​ for P. eldarica, C. arizonica, R. pseudoacacia and M. alba to be 53, 20, 30 and 50, respectively. Moreover, species-specific biases for P. eldarica, C. arizonica, R. pseudoacacia and M. alba was shown to be 30, 10, -30 and 44 respectively. The results of this study supports the use of the applied Quickbird data for model-based estimation of aboveground biomass across the study site.