the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
High-resolution distribution maps of single-season rice in China from 2017 to 2022
Ruoque Shen
Baihong Pan
Qiongyan Peng
Jie Dong
Xuebing Chen
Xi Zhang
Jianxi Huang
Wenping Yuan
Abstract. Paddy rice is the second-largest grain crop in China and plays an important role in ensuring global food security. However, there is no high-resolution map of rice covering all of China. This study developed a new rice mapping method by combining optical and synthetic aperture radar (SAR) images in cloudy areas based on the time-weighted dynamic time warping (TWDTW) method and produced distribution maps of single-season rice in 21 provincial administrative regions of China from 2017 to 2022 at 10 or 20-m resolution. The accuracy was examined by using 108195 survey samples and county-level statistical data. On average, the user’s, producer’s, and overall accuracy over all investigated provincial administrative regions were 73.08 %, 82.81 %, and 85.23 %, respectively. Compared with the statistical data from 2017 to 2019, the distribution map explained 83 % of the spatial variation of county-level planting areas on average. The distribution maps can be obtained at https://doi.org/10.57760/sciencedb.06963 (Shen et al., 2023).
Ruoque Shen et al.
Status: open (extended)
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RC1: 'Comment on essd-2023-9', Anonymous Referee #1, 23 Feb 2023
reply
Food security is crucial to human survival, and this article's proposed large-scale fine-resolution single-season rice mapping method is meaningful. However, there are some questions or problems:
- This article uses SAR data in multi-cloud pixels, which is indeed not affected by clouds and mist. However, SAR images are affected by salt-and-pepper noise, can filtering or homogeneous sample point selection method be considered for denoising?
- The compatibility issue between the SAR VH band and the optical image's SWIR1 band needs to be solved, and a clearer explanation is needed. How do you prove that your processing method regarding this is feasible?
- How does this article handle data of different resolutions (such as 10m and 20m)?
- Are formulas 3 and 4 referenced? The explanation of formula 3 and its parameters should be more specific.
- In line 217, figure 8a and 8c is not exist, this issue needs to be thoroughly checked.
- The distribution of statistical data in 2017 is different from that in other years. Is it a problem of data processing?
Citation: https://doi.org/10.5194/essd-2023-9-RC1
Ruoque Shen et al.
Data sets
High-resolution distribution maps of single-season rice in China from 2017 to 2022 Ruoque Shen, Baihong Pan, Qiongyan Peng, Jie Dong, Xuebing Chen, Xi Zhang, Tao Ye, Jianxi Huang, Wenping Yuan https://doi.org/10.57760/sciencedb.06963
Ruoque Shen et al.
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