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Grain yield prediction of rice using multi-temporal UAV-based RGB and multispectral images and model transfer – a case study of small farmlands in the South of China

Grain yield prediction of rice using multi-temporal UAV-based RGB and multispectral images and... http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Agricultural and Forest Meteorology CrossRef

Grain yield prediction of rice using multi-temporal UAV-based RGB and multispectral images and model transfer – a case study of small farmlands in the South of China

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Publisher
CrossRef
Copyright
© 2020 Elsevier B.V. All rights reserved.
ISSN
0168-1923
DOI
10.1016/j.agrformet.2020.108096
Publisher site
See Article on Publisher Site

Abstract

Journal

Agricultural and Forest Meteorology – CrossRef

Published: Sep 1, 2020

References

  • A novel framework to detect conventional tillage and no-tillage cropping system effect on cotton growth and development using multi-temporal UAS data
    Ashapure
  • Empirical proof of the empirical line
    Baugh
  • Estimating biomass of barley using crop surface models (csms) derived from uav-based rgb imaging
    Bendig
  • Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley
    Bendig
  • Quantifying chlorophylls and caroteniods at leaf and canopy scales: an evaluation of some hyperspectral approaches
    Blackburn
  • The rice genome - The cereal of the world’s poor takes center stage
    Cantrell
  • Dynamic monitoring of biomass of rice under different nitrogen treatments using a lightweight UAV with dual image-frame snapshot cameras
    Cen
  • Predicting rice yield using canopy reflectance measured at booting stage
    Chang
  • The use of near-infrared reflectance spectroscopy (NIRS) to predict the composition of whole maize plants
    Cozzolino
  • The MERIS terrestrial chlorophyll index. Int. J
    Dash
  • Monitoring of wheat growth status and mapping of wheat yield’s within-field spatial variations using color images acquired from uav-camera system
    Du
  • Remote estimation of rice yield with unmanned aerial vehicle (uav) data and spectral mixture analysis
    Duan
  • Dynamic monitoring of NDVI in wheat agronomy and breeding trials using an unmanned aerial vehicle
    Duan
  • Remote estimation of vegetation fraction and flower fraction in oilseed rape with unmanned aerial vehicle data
    Fang
  • A multi-environment trial analysis shows slight grain yield improvement in Texas commercial maize
    Farfan
  • Transfer of multivariate calibration models: a review
    Feudale
  • Winter wheat biomass estimation based on spectral indices, band depth analysis and partial least squares regression using hyperspectral measurements
    Fu
  • Combined spectral and spatial modeling of corn yield based on aerial images and crop surface models acquired with an unmanned aircraft system
    Geipel
  • Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves
    Gitelson
  • Novel algorithms for remote estimation of vegetation fraction
    Gitelson
  • Remote estimation of rapeseed yield with unmanned aerial vehicle (UAV) imaging and spectral mixture analysis
    Gong
  • A CMOS-compatible, monolithically integrated snapshot-mosaic multispectral imager
    Gonzalez
  • Assessing correlation of high-resolution NDVI with fertilizer application level and yield of rice and wheat crops using small UAVs
    Guan
  • Automatic segmentation of relevant textures in agricultural images
    Guijarro
  • A rapid monitoring of NDVI across the wheat growth cycle for grain yield prediction using a multi-spectral UAV platform
    Hassan
  • Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight uav spectral camera for precision agriculture
    Honkavaara
  • Mapping leaf chlorophyll and leaf area index using inverse and forward canopy reflectance modeling and SPOT reflectance data
    Houborg
  • Improving winter wheat yield estimation by assimilation of the leaf area index from Landsat TM and MODIS data into the WOFOST model
    Huang
  • Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation
    Huang
  • Cotton yield estimation using very high-resolution digital images acquired with a low-cost small unmanned aerial vehicle
    Huang
  • Application of an unmanned aerial system for monitoring paddy productivity using the GRAMI-rice model
    Jeong
  • Development of a two-band enhanced vegetation index without a blue band
    Jiang
  • Estimation of winter wheat biomass and yield by combining the aquacrop model and field hyperspectral data
    Jin
  • Winter wheat yield estimation based on multi-source medium resolution optical and radar imaging data and the AquaCrop model using the particle swarm optimization algorithm
    Jin
  • Estimates of plant density of wheat crops at emergence from very low altitude UAV imagery
    Jin
  • Predicting temperature induced sterility of rice spikelets requires simulation of crop-generated microclimate
    Julia
  • Comparative uav and field phenotyping to assess yield and nitrogen use efficiency in hybrid and conventional barley
    Kefauver
  • WREP: a wavelet-based technique for extracting the red edge position from reflectance spectra for estimating leaf and canopy chlorophyll contents of cereal crops
    Li
  • Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression
    Li
  • Principal variable selection to explain grain yield variation in winter wheat from features extracted from UAV imagery
    Li
  • Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system
    Li
  • Assimilating remote sensing information into a coupled hydrology-crop growth model to estimate regional maize yield in arid regions
    Li
  • Classification and regression by randomForest
    Liaw
  • Estimates of rice lodging using indices derived from UAV visible and thermal infrared images
    Liu
  • Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine
    Maimaitijiang
  • Vegetation index weighted canopy volume model (CVMVI) for soybean biomass estimation from Unmanned Aerial System-based RGB imagery
    Maimaitijiang
  • Analysis of vegetation indices to determine nitrogen application and yield prediction in maize (Zea mays L.) from a standard uav service
    Maresma
  • Spatial variability of chlorophyll and nitrogen content of rice from hyperspectral imagery
    Moharana
  • Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras
    Naito
  • Remote prediction of yield based on LAI estimation in oilseed rape under different planting methods and nitrogen fertilizer applications
    Peng
  • Are vegetation indices derived from consumer-grade cameras mounted on UAVs sufficiently reliable for assessing experimental plots?
    Rasmussen
  • Rice yield estimation based on K-means clustering with graph-cut segmentation using low-altitude UAV images
    Reza
  • Optimization of soil-adjusted vegetation indices
    Rondeaux