Fine Classification of County Crops Based on Multi-temporal Images of Sentinel-2A
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    Abstract:

    It is a challenge to acquire accurately regional crop structure information by using remote sensing technology at county scale for the possible reasons of cultivated land fragmentation, scattered distribution and complex planting structure. Jingtai County was taken as the research area, and multitemporal Sentinel-2A remote sensing image was used as the data source to construct the time sequences of five kinds of feature parameters, which were normalized difference vegetation index (NDVI), red edge normalized vegetation index (RENDVI), and their combinations (NDVI+RENDVI, NDVI-RENDVI as well as NDVI&RENDVI). The random forest method was used to classify the crops based on five kinds of feature parameters. The results were as follows: according to the shape, the multitemporal VI (vegetation index) feature curve of crops was divided into three types, which were called highlevel, including corn, rice, flax and potato, lowlevel, including onion, greenhouse crops and sandyfield crops, and openend type, including spring wheat and spring wheatautumn oil sunflowers, respectively. Openend type could be identified by images of May or September, meanwhile, highlevel type and lowlevel type could be distinguished by images of July or August. Among each type, crops could be identified by using images of different times. For highlevel type, four crops showed significant differences in the images of mature period, for lowlevel type, images in September could supply much information to distinguish two crops, and as for as openend type, there were significant differences for three crops all through four growing stages. The sequence of overall accuracy of classification results by five kinds of feature parameters from large to small was NDVI&RENDVI, NDVI, NDVI+RENDVI, RENDVI and NDVI-RENDVI. 

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History
  • Received:June 03,2019
  • Revised:
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  • Online: September 10,2019
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