[Inventory and Study of Fruit Trees With Remote Sensing Techniques in the Eastern Ghouta]

This research carried out in the General Authority for Remote Sensing during the period 2009, 2010, 2011, the eastern region Ghouta census of fruit trees in order to increase the number of statistical accuracy, and at the lowest cost of material and time as possible. Visualization has been used with a high discrimination ability of current sources, and using geographic information system, which helps regulate and control the results of the automated count of trees. The traditional methodologies used in the statistical institutions give statistical figures are weak accuracy, which the research is to use new methodologies to count the fruit trees adapted to local conditions in Syria. Which is characterized by a variety of ways that cultivation of trees within a variety of terrain, geographical areas, and the use of several methods of tree breeding. Thus, the census trees using remote sensing techniques to avoid the errors that occurred with traditional methodologies and be more representative of the local realities. Used in this research program IVOTE (Image Visualization for Orchard Trees Enumeration) designer in the General Authority for Remote Sensing (by Dr. Alaa Shaalan) during the implementation of the project Syrian Tunisian Joint design methodologies recent census of Olives, and geographic information system Arc view GIS 3.2 and the program corrected count fruit trees is the Arc Ivote designer in the body (by Dr. Yunus Idris), who works within the geographic information system environment. Where the study was conducted on the satellite image Q bird with a capacity of discrimination of 60 cm captured in 2009 compared to images of other space taken from the of the artificial Indian and photos taken from Google Earth in 2009.2011 has been traced and corrected has shown the figures resulting from the statistics that the degree of precision and reached to 81 % as a result the program of automated counting and IVOTE to 94% due to the patch in a visual interpretation, after field verification of the results of tests on the desktop some farms in the study area. The results of statistical analysis, the application of equations of the correlation coefficient has positive values in the value of the correlation coefficient in the case of automated counting R2 = 0.997 and the value of the correlation coefficient in the case of visual interpretation R2 = 0.992. Taking into account that the method of counting trees using remote sensing techniques save time and effort is very large when compared to the costs of the traditional way. Because these results confirm the possibility of automated statistics for the trees, and the possibility of application of modern methodologies to different types of fruit trees of strategic importance in the national economy.