ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume IV-2/W5
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W5, 471–477, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W5-471-2019
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W5, 471–477, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W5-471-2019

  29 May 2019

29 May 2019

EVALUATION OF THE LONG-TERM EFFECTS OF EXPOSURE TO GREENSPACE ON TYPE 2 DIABETIC PATIENTS: CASE STUDY – TEHRAN, IRAN

A. Esmaeilzadeh1, M. R. Delavar2, and E. Nasli-Esfahani3 A. Esmaeilzadeh et al.
  • 1GIS Dept., School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
  • 2Center of Excellence in Geomatic Eng. in Disaster Management, School of Surveying and Geospatial Eng., College of Engineering, University of Tehran, Tehran, Iran
  • 3Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

Keywords: Greenspace, Diabetes, GIS, NDVI, Long-term, Epidemiology, Spatial uncertainty assessment

Abstract. Development of information technology and expansion of geospatial information systems have realized the planning managers and urban policy-makers’ wishes in making more informed decisions about urban management. At the same time, population growth and the provision of its health should be considered as one of the most important and remarkable issues for many researchers and medical specialists. So, in recent years there have been an increasing number of researches related to the study of effective factors such as environment parameters on the people’s health. In previous research, the long-term exposure effects of environmental parameters such as greenspace and air pollution on people’s health have been mostly ignored or access to reliable data has not been accomplished. The aim of this research is to study how the long-term exposure to greenspace surrounding the type 2 diabetes mellitus (T2DM) affects the average values of four years glycolized hemoglobin (HbA1c) levels. Moreover, in order to study the effects of the data type on reliability of the results, land-use data base (LDB) and satellite imagery have been employed. Pearson product and regression model have been used in this research for correlation and buffer analyse to calculate the degree of exposure of T2DM persons to greenspace. According to the results, negative correlation between long-term exposure to greenspace and the average values of four years HbA1c levels becomes statistically significant. Pearson correlation coefficients for the LDB (r = −0.366, p = 0.001) and satellite imagery (r = −0.276, p = 0.006) at 250-meter buffer from diabetic patients’ habitat is significant at 99% confidence level.