Paper Title
Getis-Ord Gi* based Farmer Suicidal Hotspot Detection

Abstract
Farmer suicidal hotspot detection in India aims to reduce the risk of farmer death. To control the risk of farmer suicide, Using the geographical information system is vital in predicting potential hotspots for farmer suicide. This study collected and analyzed data on farmer suicide in India State wise information from the National Crime Records Bureau determine the higher rate of farmer suicide. We have used Spatial statistics analysis tools that help address Average nearest neighbor analysis. Global analysis through Moron I analyzed where farmer suicidal has a clustered pattern and plotted a farmer suicidal hotspot map using Getis-ord Gi* analysis. The results show the highest farmer suicide index in Maharashtra. There is four farmer suicide factors Number of farmer suicide, the population density of farmers, climate, and income. In Maharashtra, there is a highest farmer suicidal rate than we have find farmer suicidal hotspot district wise. This Hotspot geographical region help to identify future suicidal risk through studying the hotspot map. Moreover, Government policy may suggest a hotspot zone that will help in overall development incountry growth. Keywords - Hotspot Analysis, Population pattern, Autocorrelation, Moron I.