Jinya_water_RGB.pdf (422.85 kB)
Wheat drought assessment by remote sensing imagery using unmanned aerial vehicle
conference contribution
posted on 2019-06-07, 10:07 authored by Jinya Su, Matthew CoombesMatthew Coombes, Cunjia LiuCunjia Liu, Lei Guo, Wen-Hua ChenWen-Hua ChenThis work aims at evaluating the usability of remote sensing RGB imagery by an Unmanned Aerial Vehicle (UAV) in
assessing wheat drought status. A UAV survey is conducted to collect high-resolution RGB imageries by using DJI S1000 for
the experimental wheat fields of Gucheng town, Heibei Province, China. The soil moisture for different plots of the experimental
filed is kept at an approximately constant level for the whole growing season in a well controlled environment, where field
measurements are performed just after the UAV survey to obtain the soil water content for each plot. A machine learning based
wheat drought assessment framework is proposed in this work. In the proposed framework, wheat pixels are first segmented
from the soil background using the classical normalized excess green index (NExG). Rather than using pixel-wise classification,
a pixel square of appropriate dimension is defined as the samples, based on which various features are extracted for the wheat
pixels including statistical features and spectral index features. Different classification algorithms are experimented to identify a
suitable one in terms of classification accuracy and computation time. It is discovered that Support Vector Machine with Gaussian
kernel can obtain an accuracy over 90%, which demonstrates the usefulness of RGB imagery in wheat drought assessment.
Funding
This work was supported by Science and Technology Facilities Council (STFC) under Newton fund with grant number ST/N006852/1 and the Newton Network+ NeWMap project.
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
2018 37th Chinese Control Conference (CCC) 2018 37th Chinese Control Conference (CCC)Citation
SU, J. .... et al., 2018. Wheat drought assessment by remote sensing imagery using unmanned aerial vehicle. Presented at the 2018 37th Chinese Control Conference (CCC), Wuhan, China, 25-27 July 2018.Publisher
IEEEVersion
- AM (Accepted Manuscript)
Acceptance date
2018-05-21Publication date
2018Notes
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.ISBN
9789881563958Publisher version
Language
- en