Wheat Growth Monitoring and Yield Estimation based on Multi-Rotor Unmanned Aerial Vehicle
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Wheat Growth Monitoring and Yield Estimation based on Multi-Rotor Unmanned Aerial Vehicle
Authors
Keywords
-
Journal
Remote Sensing
Volume 12, Issue 3, Pages 508
Publisher
MDPI AG
Online
2020-02-06
DOI
10.3390/rs12030508
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Using a Portable Active Sensor to Monitor Growth Parameters and Predict Grain Yield of Winter Wheat
- (2019) Jiayi Zhang et al. SENSORS
- Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data
- (2019) Liang Han et al. Plant Methods
- Estimation of Rice Growth Parameters Based on Linear Mixed-Effect Model Using Multispectral Images from Fixed-Wing Unmanned Aerial Vehicles
- (2019) Yanyu Wang et al. Remote Sensing
- Evaluation and Comparison of Random Forest and A-LSTM Networks for Large-scale Winter Wheat Identification
- (2019) Tianle He et al. Remote Sensing
- Combining Color Indices and Textures of UAV-Based Digital Imagery for Rice LAI Estimation
- (2019) Songyang Li et al. Remote Sensing
- Remote estimation of rice LAI based on Fourier spectrum texture from UAV image
- (2019) Bo Duan et al. Plant Methods
- Improving Field-Scale Wheat LAI Retrieval Based on UAV Remote-Sensing Observations and Optimized VI-LUTs
- (2019) Wanxue Zhu et al. Remote Sensing
- Spectral vegetation indices of wetland greenness: Responses to vegetation structure, composition, and spatial distribution
- (2019) Sophie Taddeo et al. REMOTE SENSING OF ENVIRONMENT
- Remote estimation of rapeseed yield with unmanned aerial vehicle (UAV) imaging and spectral mixture analysis
- (2018) Yan Gong et al. Plant Methods
- Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery
- (2017) X. Zhou et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Modelling the passive microwave signature from land surfaces: A review of recent results and application to the L-band SMOS & SMAP soil moisture retrieval algorithms
- (2017) J.-P. Wigneron et al. REMOTE SENSING OF ENVIRONMENT
- Evaluation of MLSR and PLSR for estimating soil element contents using visible/near-infrared spectroscopy in apple orchards on the Jiaodong peninsula
- (2016) Xiang Yu et al. CATENA
- Development of methods to improve soybean yield estimation and predict plant maturity with an unmanned aerial vehicle based platform
- (2016) Neil Yu et al. REMOTE SENSING OF ENVIRONMENT
- A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape
- (2015) Kennedy Were et al. ECOLOGICAL INDICATORS
- Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: From camera calibration to quality assurance
- (2015) Helge Aasen et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods
- (2014) P.J. Zarco-Tejada et al. EUROPEAN JOURNAL OF AGRONOMY
- Determination of critical nitrogen dilution curve based on leaf area index in rice
- (2014) Syed Tahir Ata-Ul-Karim et al. FIELD CROPS RESEARCH
- Estimating Biomass of Barley Using Crop Surface Models (CSMs) Derived from UAV-Based RGB Imaging
- (2014) Juliane Bendig et al. Remote Sensing
- Estimation of leaf area index in onion (Allium cepa L.) using an unmanned aerial vehicle
- (2013) Juan I. Córcoles et al. BIOSYSTEMS ENGINEERING
- Remotely estimating aerial N status of phenologically differing winter wheat cultivars grown in contrasting climatic and geographic zones in China and Germany
- (2012) Fei Li et al. FIELD CROPS RESEARCH
- Using data mining to model and interpret soil diffuse reflectance spectra
- (2010) R.A. Viscarra Rossel et al. GEODERMA
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started