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Research Article

Mapping paddy rice using Landsat time series data in the Ganfu Plain irrigation system, Southern China, from 1988−2017

, , , , , , & ORCID Icon show all
Pages 1556-1576 | Received 13 Sep 2019, Accepted 11 Sep 2020, Published online: 07 Dec 2020
 

ABSTRACT

The spatial pattern and temporal variation of paddy rice fields based on remote sensing have strong effects on the allocation of agricultural water resources on a regional scale. Free Land Remote-Sensing Satellite (Landsat) data have been successfully used to map paddy rice. However, due to frequent clouds and a temporal gap of 16 days, the shortage of Landsat data availability poses a great challenge to long-term paddy rice mapping. This study proposed a decision tree algorithm based on the Enhanced Vegetation Index (EVI) to map multi-season paddy rice in southern China. The study area is located in the Ganfu Plain Irrigation System (GFPIS), where double-cropping rice (early and late rice) and single-cropping rice (middle rice) are mixed. First, we explored the effects of the number and temporal distribution of Landsat images on the classification accuracy. With available cloud-free images in 2017, ten image combinations were set up to map rice fields using the proposed algorithm separately. Then, the algorithm was applied to map historical paddy rice planting in this study area. The results indicated that with a cropland mask, a single-date image in early rice growing season can map the total early rice with an overall accuracy varying from 82.02% to 93.26%, and the accuracy was mainly influenced by the temporal distribution of the images. In addition, through post-processing, multi-temporal images could be used to recognize early rice only, late rice only, double-cropping rice and middle rice with an overall accuracy ranging from 71.83% to 85.81%. In contrast, images in the early or late growing season without obvious vegetation characteristics may result in confusion. Two peak growing season images with obvious differences in the vegetation index played a key role in detecting different rice cropping types. In addition, when the EVI of rice was within a certain range, one or more images could achieve a similar overall accuracy. The total area of middle rice and late rice remained constant before 2001, but it changed from 10.72 × 104 ha in 2001 to 7.55 × 104 ha in 2017. Additionally, there was a twofold increase in the mapped middle rice area.

Acknowledgements

We would like to thank Tongyuan Luo, Jinxin Ran and Meng Liu for their help in the field surveys. And we gratefully acknowledge the United States Geological Survey (USGS) provides the Landsat images.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was financially supported by Department of Science and Technology of Hubei Province under S&T Cooperation with Foreign Country Project (No. 2019AHB076) and Technological Innovation Project (No. 2018ABA079), Open Research Fund Program of State Key Laboratory of Water Resources and Hydropower Engineering Science (No. 2016NSK01), and Water Resources Department of Jiangxi Province under Science and Technology Project (No. KT201736);Water Resources Department of Jiangxi Province [KT201736];Department of Science and Technology of Hubei Province [2018ABA079,2019AHB076];

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