A tool for mapping and monitoring landslides emergency management and disaster response: case study Murang’a County
Kimani, Michael Ngugi
MetadataShow full item record
Murang’a County is considered the county which is more prone to landslides than any other part in Kenya. This is mainly due its mountainous terrain that has rugged a landscape composed of steep valleys punctuated by numerous hills. The terrain is dissected therefore creating the menace of landslides that come often during the rainy season. According to Kenya Red Cross, they have reported that Murang’a County has recorded the highest number of loss of life as well as property destruction as a result of landslides. The magnitude of the landslide often stretch to about three kilometres making it difficult to reach the affected villages. There has been a big challenge in identifying the impact of the landslides and infrastructures affected, hampering the coordination of emergency response efforts mainly because the data is not integrated spatially. Most of infrastructure damaged are people’s houses, roads, tea factories, tea buying centres, schools, hospitals, the tea farms not mention loss of human life and animals. To address this challenge, a tool that utilizes location intelligence as a spatial analytic technique to map and monitor landslide emergencies as well as respond to disasters in a more informed manner was developed. Spatial analysis lends new perspectives to a decision-maker as they study landslide occurrence, households destroyed, infrastructure affected and the relationships among them in an easily understandable manner. The tool was used to record & monitor landslide events, using an interactive operation dashboard that spatially showed where the landslides occurred, location of affected households and damaged infrastructure so as to coordinate the response services deployed. The tool was anchored on location intelligence, a spatial analysis technique, which provided various ways of analysing landslides events geographically and integrated infrastructure data to determine the likely impact. The findings of the research showed that users found the application informative and easy to use. The users were able to locate the areas where landslides often occur and were satisfied with the useful information that assisted them in identifying the infrastructure that was at risk.