Satellite data planning for flood mapping activities based on high rainfall events generated using TRMM, GEFS and disaster news

ABSTRACT

Microwave satellite data enable the mapping of flooding over large areas, irrespective of cloud and weather conditions. Efficient planning of microwave data for acquiring satellite images over flood-affected areas for flood assessment and mapping needs prior information about the probable flood areas. Analysis of rainfall trend over a particular region over a time can help in predicting the flood-like situation and probable flood areas. Forecasts from weather forecasts models provide a fair idea about high rainfall events. Integration of global rainfall products (Tropical Rainfall Measuring Mission (TRMM)) and global forecast precipitation products (Global Ensemble Forecast System (GEFS)) can help in identifying the probable areas which may attain high rainfall. This advance information about probable high rainfall areas can be used in planning the remote sensing satellites for acquiring the satellite imagery over the area for flood mapping activities. Temporal satellite images integrated with disaster news available on Internet can help in analysing the ground situation (residing or increasing of flood situation). It can help in resource planning and management. The main purpose of this study is to develop a GIS-based framework coupled with automatic procedures for integrating TRMM, GEFS and disaster news using open-source technologies to identify the probable high rainfall area over Indian region and its application in planning acquisition of microwave satellite data sets for flood mapping activities. The high rainfall events identified using TRMM, GEFS and disaster news have been verified with Indian Metrological Department rainfall data during Chennai floods 2015 and Assam floods 2016. The system has been successfully used to plan and acquired satellite data for flood season 2015 and 2016.

KEYWORDS:

• Flood
• automation
• GIS
• remote sensing images

Acknowledgements

We thank Dr. Y.V.N. Krishna Murthy (Director NRSC) for providing the continues guidance throughout the process. We are grateful to Dr. V.K Dadhwal and Dr. P. G Diwakar for their guidance and support. Special thanks to Dr. M.V. Ravikumar, Dr. Vinod M Bothale, Mr. Arulraj. M and colleagues at the Disaster Management Support Group for support and cooperation; the TRMM and GEFS project team, for real-time and forecasted rainfall products.

Disclosure statement

No potential conflict of interest was reported by the authors.