Combined Multi-Time Series SAR Imagery and InSAR Technology for Rice Identification in Cloudy Regions

The use of remote sensing technology to monitor farmland is currently the mainstream method for crop research. However, in cloudy and misty regions, the use of optical remote sensing image is limited. Synthetic aperture radar (SAR) technology has many advantages, including high resolution, multi-mod...

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Bibliographic Details
Published in:Applied sciences 2021-08, Vol.11 (15), p.6923
Main Authors: Zhang, Rui, Tang, Zhanzhong, Luo, Dong, Luo, Hongxia, You, Shucheng, Zhang, Tao
Format: Article
Language:English
Subjects:
Accuracy
Agricultural land
Backscattering
Classification
Clouds
cloudy
Coefficients
Coherence
Crops
Deformation
Flowers & plants
Identification
InSAR
Interferometric synthetic aperture radar
multi-time series SAR
Polarization
Precipitation
Rain
Remote monitoring
Remote sensing
Rice
rice identification
Technology
Time series
Vegetation
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Summary:The use of remote sensing technology to monitor farmland is currently the mainstream method for crop research. However, in cloudy and misty regions, the use of optical remote sensing image is limited. Synthetic aperture radar (SAR) technology has many advantages, including high resolution, multi-mode, and multi-polarization. Moreover, it can penetrate clouds and mists, can be used for all-weather and all-time Earth observation, and is sensitive to the shape of ground objects. Therefore, it is widely used in agricultural monitoring. In this study, the polarization backscattering coefficient on time-series SAR images during the rice-growing period was analyzed. The rice identification results and accuracy of InSAR technology were compared with those of three schemes (single-time-phase SAR, multi-time-phase SAR, and combination of multi-time-phase SAR and InSAR). Results show that VV and VH polarization coherence coefficients can well distinguish artificial buildings. In particular, VV polarization coherence coefficients can well distinguish rice from water and vegetation in August and September, whereas VH polarization coherence coefficients can well distinguish rice from water and vegetation in August and October. The rice identification accuracy of single-time series Sentinel-1 SAR image (78%) is lower than that of multi-time series SAR image combined with InSAR technology (81%). In this study, Guanghan City, a cloudy region, was used as the study site, and a good verification result was obtained.
ISSN:2076-3417
2076-3417
DOI:10.3390/app11156923