Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System
Authors
Keywords
-
Journal
SENSORS
Volume 17, Issue 3, Pages 502
Publisher
MDPI AG
Online
2017-03-04
DOI
10.3390/s17030502
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Conceptual design of a hybrid solar MALE UAV
- (2016) P. Panagiotou et al. AEROSPACE SCIENCE AND TECHNOLOGY
- Are vegetation indices derived from consumer-grade cameras mounted on UAVs sufficiently reliable for assessing experimental plots?
- (2016) Jesper Rasmussen et al. EUROPEAN JOURNAL OF AGRONOMY
- Detection of rice phenology through time series analysis of ground-based spectral index data
- (2016) Hengbiao Zheng et al. FIELD CROPS RESEARCH
- Unmanned Aerial Vehicle to Estimate Nitrogen Status of Turfgrasses
- (2016) Lisa Caturegli et al. PLoS One
- The spectral calibration method for a crop nitrogen sensor
- (2016) Jun Ni et al. Sensor Review
- Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley
- (2015) Juliane Bendig et al. International Journal of Applied Earth Observation and Geoinformation
- Winglet design and optimization for a MALE UAV using CFD
- (2014) P. Panagiotou et al. AEROSPACE SCIENCE AND TECHNOLOGY
- Prediction of dry direct-seeded rice yields using chlorophyll meter, leaf color chart and GreenSeeker optical sensor in northwestern India
- (2014) A.M. Ali et al. FIELD CROPS RESEARCH
- Optimising three-band spectral indices to assess aerial N concentration, N uptake and aboveground biomass of winter wheat remotely in China and Germany
- (2014) Fei Li et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- The applicability of empirical vegetation indices for determining leaf chlorophyll content over different leaf and canopy structures
- (2013) H. Croft et al. Ecological Complexity
- Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression
- (2013) Fei Li et al. EUROPEAN JOURNAL OF AGRONOMY
- Hyperspectral canopy sensing of paddy rice aboveground biomass at different growth stages
- (2013) Martin L. Gnyp et al. FIELD CROPS RESEARCH
- Use of a virtual-reference concept to interpret active crop canopy sensor data
- (2012) Kyle H. Holland et al. PRECISION AGRICULTURE
- Use of soil moisture data for refined GreenSeeker sensor based nitrogen recommendations in winter wheat (Triticum aestivum L.)
- (2012) Olga S. Walsh et al. PRECISION AGRICULTURE
- Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivars
- (2011) Klaus Erdle et al. FIELD CROPS RESEARCH
- Carbon, nitrogen and Greenhouse gases budgets over a four years crop rotation in northern France
- (2011) Benjamin Loubet et al. PLANT AND SOIL
- Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera
- (2011) P.J. Zarco-Tejada et al. REMOTE SENSING OF ENVIRONMENT
- Variable nitrogen rate determination from plant spectral reflectance in soft red winter wheat
- (2010) W. E. Thomason et al. PRECISION AGRICULTURE
- Canopy gap fraction estimation from digital hemispherical images using sky radiance models and a linear conversion method
- (2009) Mait Lang et al. AGRICULTURAL AND FOREST METEOROLOGY
- Ultra low-level airborne (ULLA) sensing of crop canopy reflectance: A case study using a CropCircle™ sensor
- (2009) David W. Lamb et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Grain yield and protein responses in wheat using the N-Sensor for variable rate N application
- (2009) A. H. Mayfield et al. Crop & Pasture Science
- Analysis of common canopy vegetation indices for indicating leaf nitrogen accumulations in wheat and rice
- (2007) Yan Zhu et al. International Journal of Applied Earth Observation and Geoinformation
Become a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get StartedAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started