Winter wheat mapping combining variations before and after estimated heading dates

Bingwen Qiu, Yuhan Luo, Zhenghong Tang, Chongcheng Chen, Difei Lu, Hongyu Huang, Yunzhi Chen, Nan Chen, Weiming Xu

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

Accurate and updated information on winter wheat distribution is vital for food security. The intra-class variability of the temporal profiles of vegetation indices presents substantial challenges to current time series-based approaches. This study developed a new method to identify winter wheat over large regions through a transformation and metric-based approach. First, the trend surfaces were established to identify key phenological parameters of winter wheat based on altitude and latitude with references to crop calendar data from the agro-meteorological stations. Second, two phenology-based indicators were developed based on the EVI2 differences between estimated heading and seedling/harvesting dates and the change amplitudes. These two phenology-based indicators revealed variations during the estimated early and late growth stages. Finally, winter wheat data were extracted based on these two metrics. The winter wheat mapping method was applied to China based on the 250 m 8-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) 2-band Enhanced Vegetation Index (EVI2) time series datasets. Accuracy was validated with field survey data, agricultural census data, and Landsat-interpreted results in test regions. When evaluated with 653 field survey sites and Landsat image interpreted data, the overall accuracy of MODIS-derived images in 2012–2013 was 92.19% and 88.86%, respectively. The MODIS-derived winter wheat areas accounted for over 82% of the variability at the municipal level when compared with agricultural census data. The winter wheat mapping method developed in this study demonstrates great adaptability to intra-class variability of the vegetation temporal profiles and has great potential for further applications to broader regions and other types of agricultural crop mapping.

Original languageEnglish (US)
Pages (from-to)35-46
Number of pages12
JournalISPRS Journal of Photogrammetry and Remote Sensing
Volume123
DOIs
StatePublished - Jan 1 2017

Keywords

  • Intra-class variability
  • MODIS EVI2
  • Phenological stages
  • Time series analysis
  • Winter wheat

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Computer Science Applications
  • Computers in Earth Sciences

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