IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2022)

Multiyear Automated Mapping and Price Analysis of Garlic in Main Planting Areas of China Using Time-Series Remote Sensing Images

  • Hongyan Zhang,
  • Fangfang Xiao,
  • Wei He,
  • Zhaoyang Chai,
  • Hong-Tat Ewe

DOI
https://doi.org/10.1109/JSTARS.2022.3186298
Journal volume & issue
Vol. 15
pp. 5222 – 5233

Abstract

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As one of the major cash crops in China, the accurate area and distribution prediction of garlic is of great significance for the adjustment of the extent under cultivation. In this study, to map garlic in the main planting areas of China, an innovative phenology-based automated classification method was developed. The obtained garlic maps were subsequently used to analyze the relationship between areas under cultivation and garlic prices. The details are summarized as follows. First, we established the normalized difference vegetation index time-series remote sensing images to extract winter crop masks. Second, an improved green chlorophyll vegetation index was designed to distinguish garlic from winter crops using Landsat 8 and Sentinel-2 time-series images. Specifically, we extract the garlic planting areas from 2014 to 2021 in our study areas, located in the main planting areas of east-central China. The quantitative evaluations showed that the proposed method delivered an average overall accuracy varying from 89.89% to 98.68% across the entire study areas. Additionally, we analyzed the relationship between the areas in cultivation and the prices of garlic in multiple years. These results indicate that the price of garlic is highly correlated to the planting behavior of farmers, and the size of the planting areas is one of the main factors to the prices of garlic. The results can guide farmers to adjust their planting areas so as to optimize the garlic market and ensure the maximum benefit to farmers.

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