Estimating forest canopy cover using Landsat7 ETM+ data

The remotely sensed data is one of the most rapid methods for providing thematic maps in natural resources, especially forest. By combining ETM+ data and ground observation data, we can have access to thematic maps of forest such as canopy cover map, that it can be used in forest ecological studies and forest management and improvement.      The research was conducted to evaluate and investigate the possibility of using Landsat7 ETM+ data for developing forest canopy cover density map at four classes in four sites of Caspian Forests of Iran. Based on OIF index and statistical analysis of the ETM+ data, Color composite 3, 4, 5 were selected for unsupervised and supervised classifications. Ground observation information was collected from 282 plots (150*150m), using unsupervised map as a primary map.      Finally, combining the ETM+ data and the ground information, using supervised classification method, canopy cover map was achieved at four classes (5-30%, 31-50%, 51-80%, 81-100%). Evaluation of the canopy cover density percentage showed that the overall accuracy of the canopy cover percentage map developed by the Landsat7 ETM+ data and average accuracy, producer's and user's accuracy were: 85.43, 84.7 and 82.68 percent, respectively

Investigation on boundary changes of northern forests of Iran using remotely sensed data

We compared land use maps of 1988 and 2004 of northern mountainous forests of Iran that have been extracted from landsat images in 15 years period and investigated on boundary changes and calculated deforestation areas as well. This information is essential for afforestation and forest extension in the deforestation areas of upper border of the mountainous forests. For this reason, we used landsat TM and ETM+ images in 1988 and 2004 for providing land use maps and also collected information from 2960 sample plot (90×90m) using systematic random sampling. Based on extracted maps, 121528 ha of northern mountainous forests of Iran has been deforested in 15 years period. The deforestation area were estimated 8101 ha per year.  It is 0.45 percent of the northern forests. The percentage of deforestation area in terms of provinces (Guilan, Mazandran and Golestan) were estimated 1182, 4647 and 2272 ha per year or annually 0.21%, 0.49% and 0.69%, respectively. The results showed that the maximum deforestation percentage occurred in the Golestan and the minimum in the Guilan province

Geostatistically estimation and mapping of forest stock in a natural unmanaged forest in the Caspian region of Iran (Case study: Keyroud forest, Nowshahr)

Estimation and mapping of forest resources is a prerequisite for research, management, and planning. In this study, we applied kriging geostatistical interpolation for estimation and mapping of forest stock attributes in a natural, uneven-aged and unmanaged forest in the Caspian region of northern Iran. The elevation across the 516-ha study area ranged from 1100 to 1450 m a.s.l. Field sampling was performed using 1000 m2 circular sample plots in a 75 m × 200 m systematic grid. Total numbers of 309 plots were sampled. Experimental variograms were fitted for stem basal area (BA), volume stock (V) and stem density (N) using geo-referenced plots. The variograms of BA and V exhibited no spatial autocorrelation, except for the stratified data based on diameter classes and tree species. The N showed yet a medium spatial structure which was fitted by a spherical model. The stem density was estimated by ordinary block kriging. The cross-validated results showed high estimation accuracy. The applied geostatistical methods were concluded to be advantageous for accurately capture the spatial variability of stem density which was reflected in the stem density maps. The methods can be applied to similar unmanaged, uneven-aged stands in the north of Iran, and thereby support the estimation of forest growing stock