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Cropping intensity map of China with 10 m spatial resolution from analyses of time-series Landsat-7/8 and Sentinel-2 images

Luo Liu,Shanggui Kang,Xiliu Xiong,Yuanwei Qin,Jie Wang,Zhenjie Liu,Xiangming Xiao

Published 2023 in International Journal of Applied Earth Observation and Geoinformation

ABSTRACT

Cropping intensity maps at high spatial resolution play a crucial role in guiding agricultural policies and ensuring food security. So far, most of nationwide cropping intensity maps have been developed from satellite images at moderate or coarse resolutions. In this study, we first assembled and integrated time-series dataset with high spatial resolution, specifically Landsat-7, Landsat-8 and Sentinel-2 imagery in 2017. We then used an object-and phenology-based algorithm and integrated images to create a 10-m resolution cropping intensity map over China. The map evaluation results revealed an overall accuracy of 96.68 ± 0.01 % and a Kappa coefficient of 0.90. In 2017, single cropping dominated the agricultural practices in China, with an approximate area of 1.189 × 10 6 km 2 ± 7.90 × 10 3 km 2 , constituted 79.26 % of the entire cropland area. Simultaneously, double and triple cropping covered approximately 0.306 × 10 6 km 2 ± 8.03 × 10 3 km 2 and 5.00 × 10 3 ± 1.75 × 10 3 km 2 , corresponding to 20.41 % and 0.33 % of the entire cropland area, respectively. On average, the national multiple cropping index (MCI) was 1.21. The results in the study prove the reliability of the generated mapping products and high potential of the developed mapping framework (the algorithm and integrated datasets), which can be readily applied to quantify the interannual changes of cropping pattern on a nationwide level with a high spatial resolution.

PUBLICATION RECORD

  • Publication year

    2023

  • Venue

    International Journal of Applied Earth Observation and Geoinformation

  • Publication date

    2023-11-01

  • Fields of study

    Agricultural and Food Sciences, Computer Science, Environmental Science

  • Identifiers
    DOI 10.1016/j.jag.2023.103504
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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