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Spatial-temporal analysis of Big Data using Geographic Information System

عنوان مقاله: Spatial-temporal analysis of Big Data using Geographic Information System
شناسه ملی مقاله: NCSAC07_195
منتشر شده در دومین همایش بین المللی و هفتمین همایش ملی معماری و شهر پایدار در سال 1401
مشخصات نویسندگان مقاله:

Saeed Behzadi - Assistant Professor in Surveying Engineering, Department of Civil Engineering, Shahid Rajaee TeacherTraining University, Tehran, Iran
Maryam Abbaspour - BSc. Student in Civil Engineering, Faculty of Civil Engineering, University of Science and Technologyof Iran, Tehran, Iran

خلاصه مقاله:
Today, data is generated and fed in massive amounts from countless sources. In the field of urban services, this can lead to the emergence of many issues and problems in order to provide appropriate relief services with sufficient speed and accuracy. Therefore, data mining and information extraction in order to provide a suitable solution and improve services to citizens is inevitable. In this research, using the general G-statistic and the general Moran's statistic, the clusters were examined and evaluated in terms of frequency. Moran's statistic was also used to identify and reveal the behavior of events in terms of spatial dispersion distribution pattern. By examining the distribution map of events, a comparison and final evaluation was made annually. The evaluation results show that the distribution pattern of spatial dispersion is similar in each year and its similarity percentage reaches ۹۵% on average.

کلمات کلیدی:
GIS,Spatial Analysis, Spatial and temporal clustering,G* and Moran's statistical indices

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1733627/