Spatial Mapping of the Flood-Affected Regions of Northern Kerala: A Case Study of 2018 Kerala Floods

• Published in: Journal of the Indian Society of Remote Sensing 2022, Vol.50 (4), p.677-688
• Main Authors: Chithra, K., Binoy, B. V., Bimal, P.
• Format: Article
• Language: English
• Subjects: Cloud cover; Disaster management; Earth and Environmental Science; Earth Sciences; Emergency preparedness; Flood mapping; Flooding; Floods; Image resolution; Radar; Radar imaging; Remote sensing; Remote Sensing/Photogrammetry; Research Article; Satellite imagery; Scientific papers; Synthetic aperture radar; Villages; Visible spectrum; Weather
• ISSN: 0255-660X; 0974-3006
• DOI: 10.1007/s12524-021-01485-5

Flood mapping studies gained popularity in recent years with the availability of high-resolution SAR imagery. Satellite images in the visible spectrum cannot be used for disaster management applications due to inherent cloud cover during adverse weather conditions. The cloud penetrating capabilities and all-weather operation make radar images more suitable for flood mapping applications than optical images. The Kerala floods of 2018 were the worst disaster the state experienced in a century after the 1924 floods. It has resulted in widespread destruction and damages all around the state. Even though few flood inundation studies are based on the Kerala floods, they all concentrate on Central Kerala. Previous studies have not investigated detailed flood mapping of Northern Kerala using remote sensing techniques. This research paper explores the extent of flooding in Kozhikode, Malappuram and Wayanad districts of Northern Kerala by applying the thresholding method on radar images. The inundation extent of August 2018 is compared with the water-covered area of 2017 August to determine the extent of flooding. The current research also analyses the level of flood influence at the village level by using a spatial approach. The study reveals that the low-lying regions of the Malappuram district are the worse affected in the study area, with a few villages being severely flooded, with more than 10% of the geographical area inundated during the peak time. The flood inundation maps can be used to study the causative factors by applying modeling approaches.