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Multi-temporal RADARSAT-2 polarimetric SAR for maize mapping supported by segmentations from high-resolution optical image.
- Source :
- International Journal of Applied Earth Observation & Geoinformation; Feb2019, Vol. 74, p1-15, 15p
- Publication Year :
- 2019
-
Abstract
- Highlights • Integrates advantages of the microwave and optical satellite data. • Optical image is better at representing maize field boundaries than the SAR image. • Both off or in-season optical images are useful to increase the flexibility of our proposed method. • Time-series PolSAR images are able to distinguish maize from other crops. • Random Forest can be used to reduce data redundancy without reducing accuracy. Abstract Due to its ability to penetrate the cloud, Synthetic Aperture Radar (SAR) has been a great resource for crop mapping. Previous research has verified the applicability of SAR imagery in object-oriented crop classification, however, speckle noise limits the generation of optimal segmentation. This paper proposed an innovative SAR-based maize mapping method supported by optical image, Gaofen-1 PMS, based segmentation, named as parcel-based SAR classification assisted by optical imagery-based segmentation (os-PSC). Polarimetric decomposition was applied to extract polarimetric parameters from multi-temporal RADARSAT-2 data. One Gaofen-1 image was then used for parcel extraction, which was the basic unit for SAR image analysis. The final step was a multi-step classification for final maize mapping including: the potential maize mask extraction, pure/mixed maize parcel division and an integrated maize map production. Results showed that the overall accuracy of the os-PSC method was 89.1%, higher than those of pixel-level classification and SAR-based segmentation methods. The comparison between optical- and SAR-based segmentation demonstrated that optical-based segmentation would be better at representing maize field boundaries than the SAR-based segmentation. Moreover, the parcel- and pixel-level integrated classification will be suitable for many agricultural systems with small landownership where inter-cropping is common. Through integrating advantages of the SAR and optical data, os-PSC shows promising potentials for crop mapping. [ABSTRACT FROM AUTHOR]
- Subjects :
- SPECKLE interference
IMAGE segmentation
IMAGE sensors
SYNTHETIC aperture radar
CORN
Subjects
Details
- Language :
- English
- ISSN :
- 15698432
- Volume :
- 74
- Database :
- Supplemental Index
- Journal :
- International Journal of Applied Earth Observation & Geoinformation
- Publication Type :
- Academic Journal
- Accession number :
- 132489856
- Full Text :
- https://doi.org/10.1016/j.jag.2018.08.021