Preprints
https://doi.org/10.5194/essd-2024-402
https://doi.org/10.5194/essd-2024-402
30 Sep 2024
 | 30 Sep 2024
Status: this preprint is currently under review for the journal ESSD.

20 m Africa Rice Distribution Map of 2023

Jingling Jiang, Hong Zhang, Ji Ge, Lijun Zuo, Lu Xu, Minyang Song, Yinhaibin Ding, Yazhe Xie, and Wenjiang Huang

Abstract. In recent years, the demand for rice in Africa has been growing rapidly, and in order to meet this demand, the rice cultivation area is also expanding rapidly, thus it is of great significance to monitor the rice cultivation in Africa. The spatial and temporal distribution of rice cultivation in Africa is complex, making it difficult to use a climate-based rice identification method, and the existing rice distribution products are all grid based statistical data with low resolution, unable to obtain accurate rice field location and available labels. To address these two difficulties, based on time-series optical and dual-polarisation SAR data, this study proposes a sample set construction method by fast coarse positioning assisted visual interpretation, and a feature importance guided supervised classification combining multiple temporal optical and SAR features to reduce the impact of rice diversity in Africa. Firstly, we use the time-series statistical features of VH data for fast coarse positioning and screening of possible rice areas, and combine multiple auxiliary data for visual interpretation to make sample set; secondly, based on the complementary information in SAR data and optical data, the 20 meter Africa rice distribution map of 2023 was completed by combining the object-oriented segmentation results of temporal optical images and the pixel based classification results of temporal SAR data features after feature selection. The average classification accuracy of the proposed method on the validation set is more than 85 %, and the R2 of the linear fit to various existing statistical data is more than 0.9, which proves that the proposed method can achieve the spatial distribution mapping of rice under the complex climatic conditions in a large region, providing crucial data support for rice monitoring and agricultural policy development. The dataset is available at https://doi.org/10.5281/zenodo.13729353 (Jiang, Zhang et al. 2024).

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Jingling Jiang, Hong Zhang, Ji Ge, Lijun Zuo, Lu Xu, Minyang Song, Yinhaibin Ding, Yazhe Xie, and Wenjiang Huang

Status: open (until 06 Nov 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Jingling Jiang, Hong Zhang, Ji Ge, Lijun Zuo, Lu Xu, Minyang Song, Yinhaibin Ding, Yazhe Xie, and Wenjiang Huang

Data sets

20m Africa rice distribution map in 2023 Jiang Jingling et al. https://doi.org/10.5281/zenodo.13729353

Jingling Jiang, Hong Zhang, Ji Ge, Lijun Zuo, Lu Xu, Minyang Song, Yinhaibin Ding, Yazhe Xie, and Wenjiang Huang

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Short summary
This study employs temporal SAR data and optical imagery to conduct rice extraction experiments in 34 African countries with annual rice planting areas exceeding 5,000 hectares, achieving 20-meter resolution spatial distribution mapping of rice in Africa for 2023. The average classification accuracy on the validation set exceeded 85 %, and the R² values for linear fitting with existing statistical data all surpassed 0.9, demonstrating the effectiveness of the proposed mapping method.
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