To investigate the SPATIAL error CORRELATION in panel regression models, various statistical hypothesizes and testings have been proposed. This paper, within introduction to SPATIAL panel data regression model, existence of SPATIAL error CORRELATION and random effects is investigated by a joint Lagrange Multiplier test, which simultaneously tests their existence. For this purpose, joint Lagrange Multiplier test statistic and its asymptotic distribution is introduced. A simulation study is performed for considering the size and power of the test this test for joint hypothesizes. Then the application of this test is shown with investigating SPATIAL errors CORRELATION and random effects in data of agricultural product exports of ECO member states. Finally, discussion and conclusion are given.

In recent decades, Mashhad has experienced increasing SPATIAL changes in its public services development. Unbalanced distribution of Mashhad public services has created various issues for tourists and residents. The research pursues two main goals. One goal is to investigate the SPATIAL CORRELATION between public services and tourism attractions and tourism destination of Mashhad city. Another goal is to investigate the SPATIAL inequality between urban areas in access to public services. One goal is to examine the SPATIAL CORRELATION between public services and urban tourism services on the one hand and the SPATIAL CORRELATION between public services and urban tourist attractions on the other. Another goal is to investigate the SPATIAL inequality between urban areas in access to public services. For this purpose, it is attempted to calculate the indicators of access to public services, tourism services and tourism attractions of Mashhad city by a descriptive approach. These indicators are calculated using the inverse distance weighted interpolation (IDW) technique based on Mashhad urban database data. Then, using factor analysis and cluster analysis techniques, SPATIAL CORRELATIONs between indicators are tested. The results of the research indicate a significant SPATIAL CORRELATION between access to public services and access to tourism services and tourist attractions of Mashhad city. There are also SPATIAL inequalities between the central areas of Mashhad city compared with the marginal areas in access to public services. These results show the significant SPATIAL effects of urban tourism on the SPATIAL development of public services, especially in the central areas of Mashhad city.

In this paper, a supervised hyperspectral unmixing solution that integrate the SPATIAL information in the abundance estimation procedure is presented. The proposed method is applied on a nonlinear model based on Polynomial Postnonlinear Mixing Model (PPNMM) where characterizes each pixel reflections composed of nonlinear function of pure spectral signatures corrupted by noise. The image is iteratively classified to classes where contains similar spectral reflectance so share the same abundance vector. Then the abundance vector is estimated for all pixels belong to each class. To make classification, the SPATIAL CORRELATION between pixels belonging to each class is modelled by Markov Random Field (MRF). A Bayesian framework is proposed to estimate the classes and corresponding abundance vectors alternatively. Due to complexity of derived likelihood function, a Markov Chain Monte-Carlo (MCMC) algorithm is used to estimate the abundance vector based on generated samples. The result of implementation on simulated data shows around 20% prominence of proposed approach in comparison to nonlinear unmixing and MRF-based linear unmixing algorithms in the sense of estimation and reconstruction error.

Establishing a balance between natural resources and the environment and population growth, followed by increasing human needs, is an issue that should be the focus of policy makers and population planners to ensure sustainable development in the country. Human population is both affected by climate changes, so it is important to identify the relationship between population and the environment primarily because of the extent of the effects of population on the environment. Therefore, the present study intends to use the discovery of the relationship between population movements and environmental indicators while explaining the prevailing conditions in the country, to provide solutions to implement these strategies, to achieve greater stability in Iran. The research method of this research is descriptive-analytical based on secondary data. In line with the purpose of the research, 5 components (climate, water, soil, air, natural hazards) and 9 indicators have been used. In the data entry and sorting stage, Microsoft Excel software and in the data analysis stage, SPSS software and Pearson CORRELATION coefficient were used to consider the CORRELATION between environmental data and demographic movements. GIS is used and the data output is displayed in the form of maps, tables and graphs. The results of the present study that population movements in Iran have no environmental origin, but these movements and migration of some provinces during the study period (1986-2016) have caused several environmental crises. Among the effects of population displacement on the environment can be mentioned the uncontrolled abstraction of groundwater and the water crisis, as well as the occurrence of subsidence in the continuation of this issue. Also, human activities due to population increase and destruction of vegetation in and around cities have intensified natural hazards.

Non-narrative study and determination of the CORRELATION between living space and society is a subject that has been neglected in the studies by space creators (architects, city and landscape designers, and theorists of this field) and social specialists (sociologists, anthropologists, etc. ). While environmental sciences have not been able to provide a convincing theoretical framework for the role of society, in social sciences, also the acceptable understanding of the concepts of space and environment has not been reached. Trying to overcome this shortcoming is as a missing loop that is difficult to achieve and will undoubtedly answer many common environmental issues. The present study aims to examine the CORRELATION between SPATIAL configuration and development status of Isfahan's neighborhoods to help to eliminate this shortcoming in some way. For this purpose, this CORRELATION is tested in 188 neighborhoods of Isfahan at three level, global, mean and local, using CORRELATION analysis. In this process, the SPATIAL configuration of the neighborhoods is analyzed using space syntax method and their level of development is determined using TOPSIS method. The results of this study show that although there is a significant relationship at the two scales, global and mean, but this CORRELATION is weak. At local scale, also there is basically no significant CORRELATION. Accordingly, if it is supposed to improve the structural integrity of Isfahan City and the development status of its neighborhoods by making changes in its SPATIAL configuration, the priority should be given to changing the streets connecting the neighborhoods as well as the main street of the city, instead of interfering in and changing the neighborhood access network, taking into account that these changes should not be expected to necessarily have a positive effect on the development status of neighborhoods.

Rain-gauge networks are often installed to provide measurements that characterize the temporal and SPATIAL variations of rainfall, thus accurate and efficient design of them are necessary. The main objective of this research is to evaluate the rain gauge network installed and administered by the Ministry of Energy in the Golestan province (39 rain gauge stations during 12 years), using SPATIAL CORRELATION technique. Considering the effects of topography on precipitation pattern, the Golestan province has been divided into two homogeneous areas. In each area the CORRELATION functions based on CORRELATION between monthly rainfall data and distances of stations have been determined and the accuracy of SPATIAL rainfall estimation with the running rain gauges have been evaluated using two accuracy criteria (Ac1 and Ac2). Then, depending on the desired level of accuracy, the required number of rain gauges and their distances and SPATIAL pattern were estimated in both homogeneous areas. Results showed that the present network of rain gauges in the mountainous area has more suitable SPATIAL pattern than the flat area. Also it has been concluded that the existing network of rain gauges would suffice the objectives of management and research studies that require data with 10 to 15% accuracy level. However, in case of need for more accurate estimation of spatio-temporal variations of rainfall, the number of rain gauges in the mountainous area should be increased. While, in the flat area relocation of existing rain gauges is necessary.