Automated rainfall data extraction from satellite imagery for crop index insurance

Abstract

Crop insurance uses rainfall as one of the indeces on which farmers can be insured. The rainfall data can be obtained locally from the weather stations but it is limited to only 30 kilometres radius from a station. Though there are many sources of rainfall data, satellite data has not been explored in depth within the Kenyan context and by any insurance firm as a reference point.This project presents an automation prototype that extracts rainfall data from satellite imagery for crop index insurance. The prototype is implemented using python, .NET, PHP, HTML and PostGres/PostGIS. The prototype encompasses download module, data extraction and database storage modules. Mosaic algorithm is implementedusing the pixel traversal algorithm. The output product is created using the supplied reprojection information and output parameters such as pixel size and easting and northing. The input products being satellite image products, the processing parameter used is a shape file to map out the desired regions and rain gauge stations. Once an output product has been written it can be updated with an unlimited number of new input products. The "filling" of the final product follows the principle of fetching pixels from source products. The Mosaic Processor loops over all cells in the target grid and determines whether a pixel from a source product may be suitable to read into it. The pixel RGB value is referenced to an accompanying CLR file to determine the rainfall value the pixel holds. Rainfall data was extracted from bil images of April 2006 for each day. The rainfall data extracted from the satellite imagery was compared to the recorded meteorological data for the same period (mean monthly rainfall) for April 2006. The research concludes that rainfall can be extracted from satellite imagery and used for rainfall index insurance. The .bil images provide rainfall information for a radius of 8kms which can be improved with higher resolution images. With this, the crop insurers can have a larger pool of farmers to insure as there will be no need of being 30km radius from a rain gauge sation. This research presents altenative source of rainfall data from the traditional rain gauges to be provided to farmers and insurance companies. The research concludes by recommending furtherwork to be done with level 0 imageryto be used as input and higher resolution images to reduce the 8km by 8km to even a shorter distance