Applications of remote sensing in precision agriculture: A review

RP Sishodia, RL Ray, SK Singh - Remote sensing, 2020 - mdpi.com
Agriculture provides for the most basic needs of humankind: food and fiber. The introduction
of new farming techniques in the past century (eg, during the Green Revolution) has helped …

A review of advanced technologies and development for hyperspectral-based plant disease detection in the past three decades

N Zhang, G Yang, Y Pan, X Yang, L Chen, C Zhao - Remote Sensing, 2020 - mdpi.com
The detection, quantification, diagnosis, and identification of plant diseases is particularly
crucial for precision agriculture. Recently, traditional visual assessment technology has not …

Hyperspectral sensing of plant diseases: Principle and methods

L Wan, H Li, C Li, A Wang, Y Yang, P Wang - Agronomy, 2022 - mdpi.com
Pathogen infection has greatly reduced crop production. As the symptoms of diseases
usually appear when the plants are infected severely, rapid identification approaches are …

Identification of crop diseases and insect pests based on deep learning

B Wang - Scientific Programming, 2022 - Wiley Online Library
In order to solve the problems of many kinds of crop diseases and pests, fast diffusion
speed, and long time of manual identification of diseases and pests, a crop disease and pest …

Monitoring wheat fusarium head blight using unmanned aerial vehicle hyperspectral imagery

L Liu, Y Dong, W Huang, X Du, H Ma - Remote Sensing, 2020 - mdpi.com
The monitoring of winter wheat Fusarium head blight via rapid and non-destructive
measures is important for agricultural production and disease control. Images of unmanned …

Detection of cotton verticillium wilt disease severity based on hyperspectrum and GWO-SVM

N Zhang, X Zhang, P Shang, R Ma, X Yuan, L Li, T Bai - Remote Sensing, 2023 - mdpi.com
In order to address the challenge of early detection of cotton verticillium wilt disease,
naturally infected cotton plants in the field, which were divided into five categories based on …

Dual-branch collaborative learning network for crop disease identification

W Zhang, X Sun, L Zhou, X Xie, W Zhao… - Frontiers in Plant …, 2023 - frontiersin.org
Crop diseases seriously affect the quality, yield, and food security of crops. redBesides,
traditional manual monitoring methods can no longer meet intelligent agriculture's efficiency …

A fast Fourier convolutional deep neural network for accurate and explainable discrimination of wheat yellow rust and nitrogen deficiency from Sentinel-2 time series …

Y Shi, L Han, P González-Moreno, D Dancey… - Frontiers in Plant …, 2023 - frontiersin.org
Introduction Accurate and timely detection of plant stress is essential for yield protection,
allowing better-targeted intervention strategies. Recent advances in remote sensing and …

Using UAV-based hyperspectral imagery to detect winter wheat fusarium head blight

H Ma, W Huang, Y Dong, L Liu, A Guo - Remote Sensing, 2021 - mdpi.com
Fusarium head blight (FHB) is a major winter wheat disease in China. The accurate and
timely detection of wheat FHB is vital to scientific field management. By combining three …

A review of hybrid approaches for quantitative assessment of crop traits using optical remote sensing: research trends and future directions

A Abdelbaki, T Udelhoven - Remote Sensing, 2022 - mdpi.com
Remote sensing technology allows to provide information about biochemical and
biophysical crop traits and monitor their spatiotemporal dynamics of agriculture ecosystems …