جستجوی مقالات مرتبط با کلیدواژه "statistics" در نشریات گروه "جغرافیا"

Rainfall is counted as the main entrance in hydrologic modeling. Efficient network of the rain gauge stations are the ones having an appropriate density and favorable estimations of rainfall in locations without any station. In order to optimize the position of the rain gauge stations, different methods have been proposed, among which the geo-statistical methods are widely used. The present study aimed to assess the status of the rain gauge stations of Kordestan Province, and to optimize their position based on geo statistical methods. In this study, in order to evaluate the accuracy of various interpolation methods, the Ordinary Kriging method with circular function was detected to be more credible compared to other models and that it was the most suitable interpolation method in the distribution of rainfall in the province. Furthermore, in order to optimize and estimate the errors of the current stations, the precipitation data from 145 meteorological stations were used, and given the sheer size of the study area and great changes to rainfall data, area segmentation or clustering of the stations was done, and the whole area was divided into 8 clusters. The results of the optimization based on the Kriging coefficient of variation indicated that, by the addition of new 17 proposed stations to the rain gauge network in the province, the values ​​of spatial coefficient of variation of annual rainfall has decreased between 0.21 to 6.67 percent, and close to 12% from the central to the south, and in western areas, respectively. The results of this study have a great importance on the use of geo-statistical methods in optimization, and the generated maps are of high practical value for the executive agencies (Ministry of Energy, the National Weather Service, etc.).

The present study was done through Iran to investigate the best method of spatial interpolation to estimate the annual average temperature. Therefore, the data of 180 synoptic stations in Iran were used. Using different interpolation methods (IDW, GPI, LPI and RBF) with different powers of 1, 2, 3, 4 and 5 and models (Completely Regularized Spline, Inverse Multi-quadric, Multi-quadric, Spline with Tension, and Thin Plate Spline), spatial distribution of the average annual precipitation was investigated to recognize the best method of interpolation. The geo-statistical interpolation methods were kriging and co-kriging. Using some evaluation methods and some indices (RMSE, MBE, MAPE and R), the best method for interpolation was selected. Finally, annual temperature map in GIS was provided by the best method. The results showed that the RBF method has the least RMSE and the most correlation relationship than the others for the interpolating the annual average temperature in Iran (Multi-quadric)

One of the most common and important methods for the regulation, presentation and analysis of scientific findings is the use of statistics science. In the science of geography, the use of quantitative statistics and data is considered necessary. It is also evident in various geography disciplines, including urban geography. The purpose of this study was to visualize facts within the data and analyze them on the basis of statistical information. In order to carry out this task, it was attempted to establish a relationship among population, urban utilities and their waste production in SPSS software using statistical analyses. In this regard, two methods of Inter Regression Analysis and Stepwise Regression Analysis were used. The results of the analyzed data showed that the population and urban utilizations in Tehran justify the garbage produced in different regions in terms of volume, size and shape.