Cycling is a phenomenon in urban transportation that has the ability to allocate a specific location at any moment in time. Accordingly, spatial analysis of bicycle trips can be accompanied by temporal analysis. The use of a GIS environment is commonly recommended to display the extent of the phenomenon's spatial changes. However, in order to apply and display changes over time, it will requir...

Professor Pirnia classified house space in three spatial system, large, small and breack Peymoon which the basis of these categories include spatial scale, number and arrangement of different spaces in them. Despite the nominal researches, there is not specific research about the introduction of spatial features and patterns ruling over them. The present study follows the concept of privacy and...

Spatial planning approaches along with complication of societies are being changed. These changes and transformations have reflected themselves in increasing diversification of economic patterns, people, group, organization, and institution’s mobility. While in less developed network societies some of the concepts including “distance” and “movement “are relatively losing their importance , some...

An important issue in survival data analysis is the identification of risk factors. Some of these factors are identifiable and explainable by presence of some covariates in the Cox proportional hazard model, while the others are unidentifiable or even immeasurable. Spatial correlation of censored survival data is one of these sources that are rarely considered in the literatures. In this paper,...

Obtaining of an image with high spectral and spatial resolution is the goal of image fusion. The PCA is a well-known pan-sharpening approach widely used for its efficiency and high spatial resolution. However, it can distort the spectral characteristics of the multispectral images. To avoid the weak points of the standard PCA technique, Spatial PCA transform has been proposed and the reasons of...

Spatial autocorrelation statistics provide summary information about the spatial arrangement of data in a map. In fact, these statistics compare neighboring area values in order to assess the level of large scale clustering. Whenever a large number of neighboring areas have either relatively large or relatively small values, large scale clustering may be detected. Detecting such clustering is a...

Many researches have demonstrated that the spatial information can play an important role in the classification of hyperspectral imagery. This study proposes a modified spectral–spatial classification approach for improving the spectral–spatial classification of hyperspectral images. In the proposed method ten spatial/texture features, using mean, standard deviation, contrast, homogeneity, corr...