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Remote sensing technology is one of the most efficient and innovative technologies for agricultural land use/cover mapping. In this regard, the object-based Image Analysis (OBIA) is known as a new method of satellite image processing which integrates spatial and spectral information for satellite image process. This approach make use of spectral, environmental, physical and geometrical characteristics (e.g. texture, shape) together images contexts for modeling of land use/cover classes. The main objective of this study is to classify micro land use/cover of Meyandoab County by applying appropriate and effective algorithms and parameters in the object based approach. For this goal, Quick Bird and Aster satellite images were used within the integrated approach for processing and land use modeling. Accordingly, the land use map was classified in 9 class based on spectral and spatial characteristics.  In order to perform OBIA, the segmentation was applied in the scale of 10, shape parameter of 0.7 as well as the compactness of 0.3. In terms of the classification task, fuzzy based algorithm and operators (AND, OR) was applied to detriment the membership functionality of segments for each class as well as classifying the related objects.  We also applied textures, geometric, NDVI, GLCM, brightness algorithms based on fuzzy operators and assign class algorithm. In order to applying the validation of results, the accuracy assessment step was performed and the finally overall accuracy of 93.6 was obtained for the derived map. The Kappa coefficient was also detriment to be 0.92. The area under cultivation included respectively for lands of wheat and barley, prunes and plums, apples, vineyards and alfalfa hay2622.42, 4505, 4354.55, 4457.85, 14110.58 hectares.
 

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Quality of life is one of the important issues that was first brought to the attention of scholars by the extensive development of technology and industrialization process in the Western countries, and it is increasingly being studied in this field, and this is important due to the increasing increase in quality of life studies in public policy monitoring. Quality of life can be used as a powerful tool for monitoring community development planning. The existence of spatial and spatial inequalities in the city has caused many problems, including the weakness of resources, inappropriate housing, the problems and damage caused by social inequalities, and undermined the quality of life. In this research, that of terms methodological, descriptive-analytic and in terms of purpose, it is functional used the statistics blocks of Urmia, in the census of 1395, and remote sensing data in combination with GIS have been to understand the quality of life in the 5 regions of Urmia. The criteria defined in this research are in 4 sections: social (including 9 sub-criteria), access to public services (5 sub-criteria), physical (4 sub-criteria), natural (4 sub-criteria), which are based on decision analysis Multi-criteria and integration of layers in the GIS environment. Weights obtained for social dimensions, access to public, natural and physical services derived from network analysis model  are respectively 0.506, 0.323, 0.116 and 0.055. The results show that as far as the southwest is moving along the northeastern part of the city, blocks that have a better quality of life are rising.  In the urban regions of the region 2, quality of life is more favorable than other urban regions. The results of such studies can help urban planners to better understand and prioritize urban issues as a dynamic environment.