Tehran University of Medical Sciences Iranian Journal of Public Health 2251-6085 47 9 2018 08 29 1280 1290 Muhammad Haris MAZHER Institute of Geographic Information Systems, School of Civil and Environmental Engineering, National University of Sciences and Technology, Islamabad, Pakistan Javed IQBAL Institute of Geographic Information Systems, School of Civil and Environmental Engineering, National University of Sciences and Technology, Islamabad, Pakistan Muhammad Ahsan MAHBOOB Institute of Geographic Information Systems, School of Civil and Environmental Engineering, National University of Sciences and Technology, Islamabad, Pakistan Iqra ATIF Institute of Geographic Information Systems, School of Civil and Environmental Engineering, National University of Sciences and Technology, Islamabad, Pakistan 2018 08 29 2018 08 29 Background: Remote sensing have been intensively used across many disciplines, however, such information was limited in spatial epidemiology. Methods: Two years (2009 & 2010) Landsat TM satellite data was used to develop vegetation, water bodies, air temperature and humidity criterion maps to model malaria risk and its spatiotemporal seasonal variation. The criterion maps were used in weighted overlay analysis to generate final categorized malaria risk map. Results: Overall, 25%, 68%, 18% and 16% of the total area of Rawalpindi region was categorized as danger zone for Jun 2009, Oct 2009, Jan 2010 and Jun 2010, respectively. The malaria risk reached at its peak during the monsoon season whereas air temperature and relative humidity were the main contributing factors in seasonal variation. Conclusion: Malaria risk maps could be used for prioritizing areas for malaria control measures.     https://ijph.tums.ac.ir/index.php/ijph/article/view/14580 https://ijph.tums.ac.ir/index.php/ijph/article/download/14580/6109