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Abstract. Forest canopy density (FCD) of seventeen protected areas of the Caspian Hyrcanian mixed forest are studied here. A modified version of FCD mapper based on spectral band fusion and customized threshold calibration that is optimized for Hyrcanian forests is used for this purpose. In this project, the results of applying the FCD model on three time series of satellite images have been analysed. This classification is based on the FAO standard and consist of four categories such as no-forest, thin, semi-dense and dense. These images, taken with TM and ETM sensors, belong to three-time series between 1987 and 2002. The results of this study indicate that the rate of growth or destruction of forests has been investigated in the regions. Then, using tables and diagrams of variations, the rate of growth or destruction of forest lands in the corresponding period in each class is determined. The FCD model has the ability to study the canopy loading classes in the annual time series.

Mapping of forest extent is a prerequisite to acquire quantitative and qualitative information about forests and to formulate management and conservation strategies. forest canopy density (FCD) model is one of the useful RS methods for forest mapping using satellite images. One of the most serious challenges in FCD model is the weakness in the calculation of canopy density in low density forests as well as plain forests. Due to the existence of chlorophyll in croplands, shrubs, pastures, etc., FCD model has difficulty to determinate the forests areas from the other mentioned land cover. Hence, this paper is focused on improving the performance of FCD model to overcome this limitation. This improvement yield by adding a new forest color composite index (FCCI) and removing non-forest vegetation using the average kernel and DEM regard to standard forest definition. In this study, in order to implement and evaluate the performance of the improved model, time series of Landsat images acquired from USGS Landsat standard level-2 products archive. In this study, Landsat time series images acquired from USGS Landsat standard level-2 products were used to estimate forest canopy density in Hyrcanian forests of northern Iran. The results indicated the higher accuracy of the proposed model. Moreover, overall accuracy and kappa index of the model were 10% and 24% superior to initial model, respectively. As a second objective, in order to implement and evaluate the performance of the improved model, canopy changes of the Hyrcanian forests were also examined. In general, the results of this study showed that