Identification of late rice farmland based on long-term remote sensing phenology information in Dongting Lake Plain

In order to explore the extraction method of late rice planting areas in the Dongting Lake Plain represented by Junshan District, multispectral satellites and synthetic aperture radar satellites were combined to establish continuous remote sensing phenology curves for rice. By establishing multi-dimensional spatial features, based on an unsupervised classification spatial clustering algorithm, and using 2 years of continuous multispectral and SAR images, a complete continuous remote sensing phenology curve of rice was constructed by coupling, and accurate rice field plot information was screened. Therefore, the late rice phenological characteristic plot based on satellite images enables high-precision extraction of complex mountainous rice planting areas. The result shows, the method solved the adverse effects on rice remote sensing classification caused by problems such as broken underlying surface, scattered farmland distribution, and fewer available images in the study area. The overall classification accuracy is 86.49%, which is better than traditional supervised classification methods.

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Publication Details

Published
2024-08-16
DOI
https://doi.org/10.1117/12.3036496
Primary Topic
Remote Sensing and Land Use
Type
article
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Identification of late rice farmland based on long-term remote sensing phenology information in Dongting Lake Plain

Leishi Chen, Xiqiang Shuai, Shuai Jiang, Hao Lin et al.
Remote Sensing and Land Use
article

Identification of late rice farmland based on long-term remote sensing phenology information in Dongting Lake Plain

Leishi Chen, Xiqiang Shuai, Shuai Jiang, Hao Lin, Z. J. Zheng
article en

Abstract

In order to explore the extraction method of late rice planting areas in the Dongting Lake Plain represented by Junshan District, multispectral satellites and synthetic aperture radar satellites were combined to establish continuous remote sensing phenology curves for rice. By establishing multi-dimensional spatial features, based on an unsupervised classification spatial clustering algorithm, and using 2 years of continuous multispectral and SAR images, a complete continuous remote sensing phenology curve of rice was constructed by coupling, and accurate rice field plot information was screened. Therefore, the late rice phenological characteristic plot based on satellite images enables high-precision extraction of complex mountainous rice planting areas. The result shows, the method solved the adverse effects on rice remote sensing classification caused by problems such as broken underlying surface, scattered farmland distribution, and fewer available images in the study area. The overall classification accuracy is 86.49%, which is better than traditional supervised classification methods.

Hunan Provincial Center for Disease Control and Prevention (CN), Beijing Meteorological Bureau (CN)
Zero hunger
Openalex Percentile: Top 83%
Remote Sensing and Land Use
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Identification of late rice farmland based on long-term remote sensing phenology information in Dongting Lake Plain — Leishi Chen, Xiqiang Shuai, et al. · (2024) | TGRS Research Map | TGRS