Abstract
Jianghan Plain is a traditional paddy rice cropping area in southern China, consisting of single-cropping rice (SCR) and double-cropping rice (DCR). In recent years, the integrated farming of rice and crayfish (IRC) has developed rapidly in the area. The purpose of this study was to employ multiple vegetation indices derived from Moderate Resolution Imaging Spectroradiometer (MODIS) time-series data to update the rice cropping pattern map of the Jianghan Plain. The Enhanced Vegetation Index combined with Normalized Difference Vegetation Index and Land Surface Water Index was applied to extract the phenological stages of paddy fields based on their spectral signatures. Then, the spatial distribution of SCR, DCR, and IRC was mapped by the phenology-based algorithm. The spatial comparison between MODIS-based mapping results and high spatial-resolution data showed that the overall classification accuracy (CA) was 91.69%. The CA of SCR, DCR, and IRC was 91.25%, 92.00%, and 92.50%, respectively. The total MODIS-derived rice area had a good quantitative consistency with statistical data (R2 = 0.86, P < 0.01) and land-use data (R2 = 0.63, P < 0.01). The research demonstrated the promise of the MODIS dataset in mapping croplands mixed with paddy fields and rice-crayfish fields over large areas.
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Acknowledgements
We thank the editors of the Paddy and Water Environment, the anonymous reviewers for their valuable suggestions, and the data providers (USGS) that supplied the remote sensing data in AρρEEARS.
Funding
This research was supported by a Grant from the State Key Laboratory of Resources and Environmental Information System [Grant No. 202026] and the National Natural Science Foundation of China under Grant [Grant No. 62071457].
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Conceptualization, QS, RL, and HC; methodology, QS, RL, and HC; validation, QS and HC; formal analysis, QS and HC; investigation, QS, JQ, YH, DH, and MC; data curation, QS, JQ, and DH; writing-original draft preparation, QS and HC; writing-review and editing, QS, HC, and YH; supervision, QS and HC; project administration, QS and HC. All authors have read and agreed to the published version of the manuscript.
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Shao, Q., Li, R., Qiu, J. et al. Large-scale mapping of new mixed rice cropping patterns in southern China with phenology-based algorithm and MODIS dataset. Paddy Water Environ 21, 243–261 (2023). https://doi.org/10.1007/s10333-023-00926-w
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DOI: https://doi.org/10.1007/s10333-023-00926-w