Near real-time characterisation of urban environments: a holistic approach for monitoring dengue fever risk areas

Despite frequent use of digital devices in everyday life, cost-effective measurement of public health issues in urban areas is still challenging. This study was, therefore, planned to extract land-use types using object-based and spatial metric approaches to explore the dengue incidence in relation to the surrounding environment in near real-time using Google and Advanced Land Observation Satellite images. The characterised image showed useful classification of an urban area with 77% accuracy and 0.68 kappa. Geospatial analysis on public health data indicated that most of the dengue cases were found in densely populated areas surrounded by dense vegetation. People living in independent houses having sparsely vegetated surroundings were found to be less vulnerable. Disease incidence was more prevalent in people of 5–24 years of age (67%); while in terms of occupation, mostly students, the unemployed, labourers and farmers (88%) were affected. In general, males were affected slightly more (10%) than females. Proximity analyses indicated that most of the dengue cases were around institutions (40%), religious places (18%) and markets (15%). Thus, usage of Digital Earth scalable tools for monitoring health issues would open new ways for maintaining a healthy and sustainable society in the years ahead.