Land cover maps are regarded one of the main inputs for land use planning and environmental modeling. One of the main reasons of unsuitable spatial array of the urban areas can be related to the rural communities' emigration, which in turn cause complete degradation of the farmlands and rural structures. Such event can be regards as a factor which is responsible for demolishing of the Haft Barm area an important recreational and touristic areas in the vicinity of Shiraz metropolis. Therefore, recognizing the natural conditions of the area, preparing resource maps like land use and land cover, and monitoring their changes during the time is critical issue in the environmental planning and management. To this aim, WorldView 2 images with eight bands were used and mentioned maps were produced. The mapping analysis way was relied on an Object-Based classification methodology and using a decision tree which was applied in the WorldView 2 images categorization. The process shall be as the following: a) segmentation, b) terrain selecting, c) creating a decision tree for images' classification, and d) ultimate classification and evaluation of the accuracy. The area was divided into 10 user classes. The results indicated successful classes categorization with overall accuracy of 87. 45%. The highest accuracy of classification was obtained for water, forest, product, building classes respectively. Planted forests patches as well as natural forests were identified and classified using OBC approach (objectbased method) while additional coastal bands were used to distinguishing among barren and covered lands. Distance to tree and shadow play an important role in identifying buildings.

Determination of the spatial pattern of trees is one of the important structural parameters of the forest for identifying changes in forest communities and it's monitoring in recent years. On the one hand, extracting this structural parameter using satellite data has a significant impact on reducing cost of inventory and makes it easy to evaluate forests of forest managers. In this study, the spatial pattern of trees in the natural forest of Farim of Mazandaran province was determined by using SPOT7 satellite data. Thus, some tree`s characteristics such as species, diameter at breast height, the diameter of canopies, gaps and the position of each tree were measured in 12 plot with area about one ha (100 m x 100 m). On the other hand, after radiometric and geometric corrections of satellite data, the tree`s canopy and gaps were classified, using the Object-Based method, and tree position per plot also was determined by canopy gravity center. Then, the spatial distribution pattern of the trees and structure, distinguished and extracted by field inventory and satellite data was compared by O-ring function. The results showed that the overall accuracy of canopy and gaps extracted from satellite data by objectbased classification was about 91% and kappa coefficient equaled 0. 7. The spatial pattern of trees were random except of the small radius and similar to the pattern of trees in-ground inventory. In total, results showed that SPOT-7 data and the Object-Based classification have an acceptable potential for determining the spatial pattern of forest stands.