Abstract
Farmer suicidal hotspot detection proposed in this paper aims to reduce the death of the farmers. Using geographical information system is vital in predicting potential hotspots for farmer suicide. This study has collected and analyzed data on farmer suicide in India, using state-wise information from the National Crime Records Bureau and has determined the recent higher rate of farmer suicide. Spatial statistics analysis tools that address average nearest neighbor analysis has been used. Global analysis through Moran's Index, analyzed that the farmer suicides have a clustered pattern and plotted a farmer suicidal hotspot map using Getis-Ord (Gi*) analysis. The results show the highest farmer suicide index is in Maharashtra and hence, farmer suicidal hotspot has been found district wise. There are four farmer suicidal factors such as, number of farmer suicide, the population density of farmers, climate, and income. This hotspot geographical region helps to identify future suicidal risk by studying the hotspot map. Moreover, government policy may suggest a hotspot zone to help the overall development of the country’s growth.
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