基于无人机遥感影像的冬小麦氮素监测

Translated title of the contribution: Nitrogen Monitoring of Winter Wheat Based on Unmanned Aerial Vehicle Remote Sensing Image

Changhua Liu, Zhe Wang, Zhichao Chen, Lan Zhou, Xuezhi Yue, Yuxin Miao

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Accurate nitrogen (N) management is a promising strategy to improve crop N use efficiency. It is important to accurately estimate the state of wheat nitrogen by unmanned aerial vehicle (UAV) remote sensing. The experiment was arranged in science and technology yard base in Laoling City, Shandong Province. The eight-rotor UAV was used to carry a Mini-MCA multispectral camera and collect the wheat canopy spectral data about four key stages (returning green stage, elongation stage, booting stage and flowering stage) of growth and development in 2016. Meanwhile, winter wheat samples of biomass, nitrogen uptake and nitrogen nutrient index were collected and measured synchronously. Grain yield was measured in mature stage. In critical stages and whole stage of different vegetation, indexes and agronomy parameters regression analysis models were established to assess winter wheat nitrogen nutrition diagnostic potential based on UAV remote sensing image. The results showed that it had better estimation of winter wheat nitrogen index (R2 was 0.45~0.96) based on UAV remote sensing image and the decision coefficient was gradually increased with the elapse of growth period. And those in elongation stage, booting stage and flowering stage were similar and had better ability for yield estimation. DATT power function model was the most powerful to explain the wheat nitrogen nutrition index (R2 was 0.95) in flowering stage. Therefore, the platform for multiple UAV rotorcraft synchronization carrying multi-spectral camera had better nitrogen diagnosis potential for winter wheat and it can be used to guide the precise nitrogen fertilizer management.

Translated title of the contributionNitrogen Monitoring of Winter Wheat Based on Unmanned Aerial Vehicle Remote Sensing Image
Original languageChinese (Traditional)
Pages (from-to)207-214
Number of pages8
JournalNongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
Volume49
Issue number6
DOIs
StatePublished - Jun 25 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018, Chinese Society of Agricultural Machinery. All right reserved.

Keywords

  • Nitrogen nutrient index
  • Nitrogen uptake
  • Unmanned aerial vehicle
  • Vegetation indexes
  • Winter wheat
  • Yield

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