Multi-temporal Monitoring of Wheat Growth through Correlation Analysis of Satellite Images, Unmanned Aerial Vehicle Images with Ground Variable

被引:15
|
作者
Du, Mengmeng [1 ]
Noguchi, Noboru [2 ]
机构
[1] Hokkaido Univ, Grad Sch Agr, Lab Vehicle Robot, Kita Ku, Kita 9 Nishi 9, Sapporo, Hokkaido 0658589, Japan
[2] Hokkaido Univ, Res Fac Agr, Lab Vehicle Robot, Kita Ku, Kita 9 Nishi 9, Sapporo, Hokkaido 0658589, Japan
来源
IFAC PAPERSONLINE | 2016年 / 49卷 / 16期
关键词
satellite remote sensing; UAV remote sensing; wheat growth monitoring; wheat canopy; radiometric normalization; wheat protein content;
D O I
10.1016/j.ifacol.2016.10.002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Satellite remote sensing has been proved to be an effective way of monitoring crop growth status and yield prediction Recently near -ground remote sensing using unmanned aerial vehicle (UAV) witnessed wide applications in obtaining field information. In this research, four satellite and eight UAV images were used from early June to the end of July, 2015, which covers two experimental wheat fields; in order to monitor wheat canopy growth status and analyze the correlation among satellite images based normalized difference vegetation index (NDVI) with UAV images based visible-band difference vegetation index (VDVI) and ground variable of grain protein contents. The results of relational analysis of NDVI with sampled wheat grain protein content showed that the NDVI related most to the grain protein content at the later stage of wheat growing season, one week prior to harvesting. And the correlation analysis of NDVI with VDVI showed good consistency at the early stage of wheat growing season, with the coefficient of determination R-2=0.77, in regardless of the wheat varieties. (c) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:5 / 9
页数:5
相关论文
共 50 条
  • [1] Multi-temporal monitoring of wheat growth by using images from satellite and unmanned aerial vehicle
    Du Mengmeng
    Noboru, Noguchi
    Atsushi, Itoh
    Yukinori, Shibuya
    INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING, 2017, 10 (05) : 1 - 13
  • [2] Correlation Analysis of Vegetation Indices Based on Multi-temporal Satellite Images and Unmanned Aerial Vehicle Images with Wheat Protein Contents
    Du M.
    Noguchi N.
    Ito A.
    Shibuya Y.
    Engineering in Agriculture, Environment and Food, 2021, 14 (03) : 86 - 94
  • [3] Multi-temporal imaging using an unmanned aerial vehicle for monitoring a sunflower crop
    Agueera Vega, Francisco
    Carvajal Ramirez, Fernando
    Perez Saiz, Monica
    Orgaz Rosua, Francisco
    BIOSYSTEMS ENGINEERING, 2015, 132 : 19 - 27
  • [4] Detection of Road Surface Changes from Multi-Temporal Unmanned Aerial Vehicle Images Using a Convolutional Siamese Network
    Truong Linh Nguyen
    Han, DongYeob
    SUSTAINABILITY, 2020, 12 (06)
  • [5] Estimation of the Bio-Parameters of Winter Wheat by Combining Feature Selection with Machine Learning Using Multi-Temporal Unmanned Aerial Vehicle Multispectral Images
    Zhang, Changsai
    Yi, Yuan
    Wang, Lijuan
    Zhang, Xuewei
    Chen, Shuo
    Su, Zaixing
    Zhang, Shuxia
    Xue, Yong
    REMOTE SENSING, 2024, 16 (03)
  • [6] Correlation of multi-temporal ground-based optical images for landslide monitoring: Application, potential and limitations
    Travelletti, J.
    Delacourt, C.
    Allemand, P.
    Malet, J. -P.
    Schmittbuhl, J.
    Toussaint, R.
    Bastard, M.
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2012, 70 : 39 - 55
  • [7] Pixel Unmixing for Urban Environment Monitoring Using Multi-Temporal Satellite Images
    Zhao, Yindi
    Du, Huijian
    Du, Peijun
    Cai, Yan
    2010 18TH INTERNATIONAL CONFERENCE ON GEOINFORMATICS, 2010,
  • [8] Combined Use of Multi-Temporal Optical and Radar Satellite Images for Grassland Monitoring
    Dusseux, Pauline
    Corpetti, Thomas
    Hubert-Moy, Laurence
    Corgne, Samuel
    REMOTE SENSING, 2014, 6 (07) : 6163 - 6182
  • [9] Polarimetric analysis of multi-temporal RADARSAT-2 SAR images for wheat monitoring and mapping
    Xu, Juan
    Li, Zhen
    Tian, Bangsen
    Huang, Lei
    Chen, Quan
    Fu, Sitao
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2014, 35 (10) : 3840 - 3858
  • [10] Locating landslides using multi-temporal satellite images
    Cheng, KS
    Wei, C
    Chang, SC
    MONITORING OF CHANGES RELATED TO NATURAL AND MANMADE HAZARDS USING SPACE TECHNOLOGY, 2004, 33 (03): : 296 - 301