Flooded Rice Paddy Detection Using Sentinel-1 and PlanetScope Data: A Case Study of the 2018 Spring Flood in West Java, Indonesia
- Resource Type
- article
- Authors
- Hiroyuki Wakabayashi; Chiharu Hongo; Takahiro Igarashi; Yoshihiro Asaoka; Boedi Tjahjono; Intan Permata
- Source
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 6291-6301 (2021)
- Subject
- Agricultural insurance
flood
gamma naught
linear discriminant analysis (LDA)
normalized difference water index (NDWI)
Ocean engineering
TC1501-1800
Geophysics. Cosmic physics
QC801-809
- Language
- English
- ISSN
- 2151-1535
This study aims to detect flooded rice paddies in Indonesia using remotely sensed data from a relatively extensive flood that occurred in the Tegalluar area of Bojongsoang in the spring of 2018, which was observed by the Sentinel-1 and PlanetScope satellites. We propose an automatic thresholding method for the detection of flooded areas in rice paddy fields using Sentinel-1 C-band synthetic aperture radar (SAR) data acquisitions from before and during flooding. The flood-detection accuracy was verified using visible and near-infrared images acquired by the PlanetScope satellites. The proposed method showed that the VV (transmit V and receive V polarizations) data outperformed the VH (transmit V and receive H polarizations) data in terms of correlation ratio and discriminant accuracy. The overall classification accuracy of the nonflooded and flooded areas reached 84.7% with the VV data and 80.6% with the VH data, including the error that resulted from the time difference in the data acquired by Sentinel-1 and PlanetScope. Utilizing speckle-reducing filters with SAR data was found to improve the overall classification accuracy by 5%.