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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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/15/6923 |
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| author | Rui Zhang Zhanzhong Tang Dong Luo Hongxia Luo Shucheng You Tao Zhang |
| author_facet | Rui Zhang Zhanzhong Tang Dong Luo Hongxia Luo Shucheng You Tao Zhang |
| author_sort | Rui Zhang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T09:18:59Z |
| format | Article |
| id | doaj.art-947f044faf5d4990ada1e06abe004458 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T09:18:59Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-947f044faf5d4990ada1e06abe0044582023-11-22T05:21:42ZengMDPI AGApplied Sciences2076-34172021-07-011115692310.3390/app11156923Combined Multi-Time Series SAR Imagery and InSAR Technology for Rice Identification in Cloudy RegionsRui Zhang0Zhanzhong Tang1Dong Luo2Hongxia Luo3Shucheng You4Tao Zhang5Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, ChinaCollege of Resources and Environment, Xingtai University, Xingtai 054001, ChinaChongqing Institute of Geology and Mineral Resources, Chongqing 401120, ChinaCollege of Geographical Science, Southwest University, Chongqing 400715, ChinaLand Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, ChinaLand Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, ChinaThe 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.https://www.mdpi.com/2076-3417/11/15/6923multi-time series SARInSARcloudyrice identificationremote sensing |
| spellingShingle | Rui Zhang Zhanzhong Tang Dong Luo Hongxia Luo Shucheng You Tao Zhang Combined Multi-Time Series SAR Imagery and InSAR Technology for Rice Identification in Cloudy Regions Applied Sciences multi-time series SAR InSAR cloudy rice identification remote sensing |
| title | Combined Multi-Time Series SAR Imagery and InSAR Technology for Rice Identification in Cloudy Regions |
| title_full | Combined Multi-Time Series SAR Imagery and InSAR Technology for Rice Identification in Cloudy Regions |
| title_fullStr | Combined Multi-Time Series SAR Imagery and InSAR Technology for Rice Identification in Cloudy Regions |
| title_full_unstemmed | Combined Multi-Time Series SAR Imagery and InSAR Technology for Rice Identification in Cloudy Regions |
| title_short | Combined Multi-Time Series SAR Imagery and InSAR Technology for Rice Identification in Cloudy Regions |
| title_sort | combined multi time series sar imagery and insar technology for rice identification in cloudy regions |
| topic | multi-time series SAR InSAR cloudy rice identification remote sensing |
| url | https://www.mdpi.com/2076-3417/11/15/6923 |
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