农业大数据学报 ›› 2023, Vol. 5 ›› Issue (1): 40-45.doi: 10.19788/j.issn.2096-6369.230112

• 数据论文 • 上一篇    下一篇

2022年内蒙古无人机马铃薯图像数据集

胡天赐1(), 王瑞利3, 蒋呈祥1, 白涛1, 胡林2,4, 王晓丽2,4,*(), 郭雷风1,2,*()   

  1. 1.新疆农业大学计算机与信息工程学院,乌鲁木齐 830052
    2.中国农业科学院农业信息研究所,北京 100081
    3.内蒙古科学技术研究院,呼和浩特 010010
    4.国家农业科学数据中心,北京 100081
  • 收稿日期:2023-03-06 出版日期:2023-03-26 发布日期:2023-05-16
  • 通讯作者: 王晓丽,女,博士,研究方向:科学数据管理与农业信息化,E-mail: wangxiaoli@caas.cn。郭雷风,男,博士,研究方向:信息技术农业应用相关研究;E-mail: guoleifeng@caas.cn
  • 作者简介:胡天赐,男,在读硕士,研究方向:农业信息化方向;E-mail: 1272341570@qq.com
  • 基金资助:
    内蒙古自治区科技计划项目(2021GG0341);国家科技创新2030重大项目(2021ZD0110901);国家重点研发计划(2022YFF0712100);中国农业科学院院级基本科研业务费(Y2022LM20)

2022 Inner Mongolia UAV Potato Image Dataset

HU Tianci1(), WANG Ruili3, JIANG Chengxiang1, BAI Tao1, HU Lin2,4, WANG Xiaoli2,4,*(), GUO Leifeng1,2,*()   

  1. 1. College of Computer and Information Engineering, Xinjiang Agricultural University, Urumqi 830052, China
    2. Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081, China
    3. Inner Mongolia Academy of Science and Technology, Hohhot 010010, China
    4. National Agriculture Science Data Center, Beijing 100081, China
  • Received:2023-03-06 Online:2023-03-26 Published:2023-05-16

摘要:

马铃薯是世界第四大粮食作物,规模化种植是其高产量的基础性保障。随着数字农业的发展,马铃薯的规模化种植方式也日益趋向自动化与智能化。无人机是作物植保和生长监测的重要工具,无人机光谱数据在作物识别、作物生长状况分析等方面发挥重要的作用。为探究光谱数据及图像数据在马铃薯生长中所发挥的作用,文章利用无人机遥感获取不同高度的多光谱影像,并对地面的马铃薯叶片数据进行采集,经过人工检查和整理构建了论文数据集。数据采集地点位于内蒙古呼伦贝尔两块成熟期种薯试验田,采集时间为2022年8月13日、16日和18日,期间共完成了3次不同空间分辨率的光谱数据及图像数据采集。本文数据集的光谱数据完整,叶片数据清晰,可为马铃薯作物识别、种植面积估测以及成熟期期间不同日期的马铃薯相关植被指数变化等研究提供数据支撑。

关键词: 无人机, 马铃薯, 多光谱, 可见光图像, 内蒙古

Abstract:

Potatoes are the fourth largest food crop in the world, and large-scale planting of potatoes is an important basis for ensuring high yields of potatoes. With the development of digital agriculture, the large-scale planting of potatoes also tends to be automated and intelligent. UAVs are an important tool in crop plant protection and growth monitoring. UAV spectral data play an important role in crop identification and crop growth status analysis. important. In order to explore the role of spectral data and image data in potato growth, this study conducted three different spatial resolution images on two mature seed potato experimental fields in Hulunbeier, Inner Mongolia, on August 13, 16 and 18, 2022. Spectral data and image data are collected. UAV remote sensing was used to obtain multi- spectral images at different heights, and the data of potato leaves on the ground were collected. After manual in- spection and sorting, this dataset was constructed. The spectral data of this dataset is complete and the leaf data is clear, which can provide data support for research on potato crop identification, planting area estimation, and potato-related vegetation index changes on different dates during the maturity period.

Key words: drone, potatoes, multispectral, visible light images, Inner Mongolia