%0 Journal Article %A Ahangarcani, Mehrdad %A Farnaghi, Mahdi %A Shirzadi, Mohammad Reza %T Exploring the Impact of Topographical and Climate Factors on Generation of the Vulnerability-map of Leptospirosis %J Journal of Geospatial Information Technology %V 6 %N 4 %U http://jgit.kntu.ac.ir/article-1-643-en.html %R 10.29252/jgit.6.4.31 %D 2019 %K Pearson’s analysis, geographic information system, support vector machine, ROC curve, Leptospirosis, %X Leptospirosis is one of the most widespread zoonotic disease caused by Leptospira bacteria. It is found wherever human is in direct or indirect contact with Leptospira bacteria thorough infected animals as well as contaminated soil or water. The disease is mostly found in tropical, subtropical, hot, and humid areas. The main objectives of this study are to investigate the seasonality relations between the topographical and climate factors, including altitude, slope, vegetation, average temperature, average humidity, precipitation and number of freezing days and incidence of Leptospirosis as well as modelling of Leptospirosis using support vector machine at the district level in Northern provinces of Iran. Pearson’s correlation analysis was conducted to examine the type and strength of relationships between the topographical and climate variables and Leptospirosis incidence. Results of Pearson’s correlation analysis indicate that average humidity, average temperature and rainfall were the most influential environmental factors which as effect on prevalence of Leptospirosis in the study area. Statistical analysis showed that most cases of the Leptospirosis prevalence have been recorded in the late spring and summer. On the other hand, the lowest incidences have occurred in winter. Also, high distribution of leptospirosis mainly located in the central areas of Guilan province, the eastern parts of Mazandaran province and western regions of Golestan province with a mild and humid climate and abundant rainfall. Eventually, performance of support vector machine (SVM) model evaluated by area under the ROC curve. The output maps showed that SVM model has excellent performance in the vulnerability mapping of Leptospirosis. %> http://jgit.kntu.ac.ir/article-1-643-en.pdf %P 31-50 %& 31 %! %9 Research %L A-11-100-3 %+ K. N. Toosi University of Technology %G eng %@ 2008-9635 %[ 2019