Next Article in Journal
Untangling the Incoherent and Coherent Scattering Components in GNSS-R and Novel Applications
Next Article in Special Issue
GRID: A Python Package for Field Plot Phenotyping Using Aerial Images
Previous Article in Journal
Hyperspectral Estimation of Soil Organic Matter Content using Different Spectral Preprocessing Techniques and PLSR Method
Previous Article in Special Issue
Combination of Linear Regression Lines to Understand the Response of Sentinel-1 Dual Polarization SAR Data with Crop Phenology—Case Study in Miyazaki, Japan
Article

Assessing the Effect of Real Spatial Resolution of In Situ UAV Multispectral Images on Seedling Rapeseed Growth Monitoring

by 1,2,†, 1,2,†, 3, 1,2, 1,2, 1,2, 1,2, 4 and 5,*
1
Macro Agriculture Research Institute, College of Resource and Environment, Huazhong Agricultural University, 1 Shizishan Street, Wuhan 430070, China
2
Key Laboratory of Farmland Conservation in the Middle and Lower Reaches of the Ministry of Agriculture, Wuhan 430070, China
3
Aerial Application Technology Research Unit, USDA-Agricultural Research Service, College Station, TX 77845, USA
4
College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
5
College of Science, Huazhong Agricultural University, Wuhan 430070, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Received: 13 March 2020 / Revised: 2 April 2020 / Accepted: 7 April 2020 / Published: 8 April 2020
(This article belongs to the Special Issue Remote Sensing for Precision Agriculture)
The spatial resolution of in situ unmanned aerial vehicle (UAV) multispectral images has a crucial effect on crop growth monitoring and image acquisition efficiency. However, existing studies about optimal spatial resolution for crop monitoring are mainly based on resampled images. Therefore, the resampled spatial resolution in these studies might not be applicable to in situ UAV images. In order to obtain optimal spatial resolution of in situ UAV multispectral images for crop growth monitoring, a RedEdge Micasense 3 camera was installed onto a DJI M600 UAV flying at different heights of 22, 29, 44, 88, and 176m to capture images of seedling rapeseed with ground sampling distances (GSD) of 1.35, 1.69, 2.61, 5.73, and 11.61 cm, respectively. Meanwhile, the normalized difference vegetation index (NDVI) measured by a GreenSeeker (GS-NDVI) and leaf area index (LAI) were collected to evaluate the performance of nine vegetation indices (VIs) and VI*plant height (PH) at different GSDs for rapeseed growth monitoring. The results showed that the normalized difference red edge index (NDRE) had a better performance for estimating GS-NDVI (R2 = 0.812) and LAI (R2 = 0.717), compared with other VIs. Moreover, when GSD was less than 2.61 cm, the NDRE*PH derived from in situ UAV images outperformed the NDRE for LAI estimation (R2 = 0.757). At oversized GSD (≥5.73 cm), imprecise PH information and a large heterogeneity within the pixel (revealed by semi-variogram analysis) resulted in a large random error for LAI estimation by NDRE*PH. Furthermore, the image collection and processing time at 1.35 cm GSD was about three times as long as that at 2.61 cm. The result of this study suggested that NDRE*PH from UAV multispectral images with a spatial resolution around 2.61 cm could be a preferential selection for seedling rapeseed growth monitoring, while NDRE alone might have a better performance for low spatial resolution images. View Full-Text
Keywords: multispectral camera; ground sampling distance (GSD); unmanned aerial vehicle (UAV) remote sensing; growth monitoring; plant height (PH) multispectral camera; ground sampling distance (GSD); unmanned aerial vehicle (UAV) remote sensing; growth monitoring; plant height (PH)
Show Figures

Graphical abstract

MDPI and ACS Style

Zhang, J.; Wang, C.; Yang, C.; Xie, T.; Jiang, Z.; Hu, T.; Luo, Z.; Zhou, G.; Xie, J. Assessing the Effect of Real Spatial Resolution of In Situ UAV Multispectral Images on Seedling Rapeseed Growth Monitoring. Remote Sens. 2020, 12, 1207. https://0-doi-org.brum.beds.ac.uk/10.3390/rs12071207

AMA Style

Zhang J, Wang C, Yang C, Xie T, Jiang Z, Hu T, Luo Z, Zhou G, Xie J. Assessing the Effect of Real Spatial Resolution of In Situ UAV Multispectral Images on Seedling Rapeseed Growth Monitoring. Remote Sensing. 2020; 12(7):1207. https://0-doi-org.brum.beds.ac.uk/10.3390/rs12071207

Chicago/Turabian Style

Zhang, Jian, Chufeng Wang, Chenghai Yang, Tianjin Xie, Zhao Jiang, Tao Hu, Zhibang Luo, Guangsheng Zhou, and Jing Xie. 2020. "Assessing the Effect of Real Spatial Resolution of In Situ UAV Multispectral Images on Seedling Rapeseed Growth Monitoring" Remote Sensing 12, no. 7: 1207. https://0-doi-org.brum.beds.ac.uk/10.3390/rs12071207

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop