QUANTITATIVE ASSESSMENT OF RICE CROP DAMAGE POST TITLI CYCLONE IN SRIKAKULAM, ANDHRA PRADESH USING GEO-SPATIAL TECHNIQUES
- 1International Rice Research Institute, Country Office, Lam, Guntur 522034, A.P., India
- 2International Rice Research Institute, Head Quarters, DAPO Box 7777, Metro Manila 1301, Philippines
- 3Sarmap, Cascine di Barico 10, Purasca 6989, Switzerland
- 4Acharya N.G. Ranga Agricultural University, Guntur 522034, A.P., India
Keywords: Synthetic Aperture Radar (SAR), Flood Inundation Mapping, Rice Crop Detection, Damage Assessment, ORYZA
Abstract. Mapping the extent of damage due to natural calamities remains one of the thrust areas in monitoring resource inventory through geo-spatial techniques. The effect of the cyclone ‘Titli’ and heavy rains during first fortnight of October 2018 in Srikakulam district, Andhra Pradesh State has been demonstrated using geo-spatial technology in terms of flood inundated rice area and corresponding yield and production loss. The pre- and post-cyclone (5 and 13 October 2018) flood inundation maps were generated using Sentinel-1A and TerraSAR-X Synthetic Aperture Radar (SAR) data respectively. The pre-cyclone rice area estimates were derived from multi-temporal Sentinel-1A SAR data, while yield forecast is based on the combination of satellite observations and yield simulation using ORYZA crop growth model. An intensive ground truth data collection had been carried out for the validation of satellite-derived rice area estimation of pre-cyclone event. An accuracy assessment has been carried out for district, mandal and village level. An overall accuracy of 96% with kappa coefficient 0.92 has been achieved. With the help map flood inundation and rice area maps, mandal-wise flood affected rice area and corresponding yield loss have been estimated. The post-cyclone ground truth data had been collected for quantitative assessment of crop damaged area. An overall accuracy of the flood affected rice map was 85% with kappa coefficient 0.70. It was estimated that rice crop damage assessment with SAR data indicated 53312 ha out of 205174 ha were affected and corresponding estimated yield as well as production are 0.8 t/ha and 189160 t respectively.