Recent advances in crop disease detection using UAV and deep learning techniques

TB Shahi, CY Xu, A Neupane, W Guo - Remote Sensing, 2023 - mdpi.com
Because of the recent advances in drones or Unmanned Aerial Vehicle (UAV) platforms,
sensors and software, UAVs have gained popularity among precision agriculture …

Global open data remote sensing satellite missions for land monitoring and conservation: A review

D Radočaj, J Obhođaš, M Jurišić, M Gašparović - Land, 2020 - mdpi.com
The application of global open data remote sensing satellite missions in land monitoring and
conservation studies is in the state of rapid growth, ensuring an observation with high spatial …

Predicting canopy chlorophyll content in sugarcane crops using machine learning algorithms and spectral vegetation indices derived from UAV multispectral imagery

A Narmilan, F Gonzalez, ASA Salgadoe… - Remote Sensing, 2022 - mdpi.com
The use of satellite-based Remote Sensing (RS) is a well-developed field of research. RS
techniques have been successfully utilized to evaluate the chlorophyll content for the …

Multi-stage corn yield prediction using high-resolution UAV multispectral data and machine learning models

C Kumar, P Mubvumba, Y Huang, J Dhillon, K Reddy - Agronomy, 2023 - mdpi.com
Timely and cost-effective crop yield prediction is vital in crop management decision-making.
This study evaluates the efficacy of Unmanned Aerial Vehicle (UAV)-based Vegetation …

Estimation of maize foliar temperature and stomatal conductance as indicators of water stress based on optical and thermal imagery acquired using an unmanned …

K Brewer, A Clulow, M Sibanda, S Gokool, J Odindi… - Drones, 2022 - mdpi.com
Climatic variability and extreme weather events impact agricultural production, especially in
sub-Saharan smallholder cropping systems, which are commonly rainfed. Hence, the …

Evaluating the sensitivity of water stressed maize chlorophyll and structure based on UAV derived vegetation indices

L Zhang, W Han, Y Niu, JL Chavez, G Shao… - … and Electronics in …, 2021 - Elsevier
To further assess the sensitivity of crop chlorophyll and structure based on UAV vegetation
indices (VIs) to maize water stress, a study was carried out in a maize field located in Inner …

[HTML][HTML] Monitoring maize canopy chlorophyll content throughout the growth stages based on UAV MS and RGB feature fusion

W Li, K Pan, W Liu, W Xiao, S Ni, P Shi, X Chen, T Li - Agriculture, 2024 - mdpi.com
Chlorophyll content is an important physiological indicator reflecting the growth status of
crops. Traditional methods for obtaining crop chlorophyll content are time-consuming and …

[HTML][HTML] The feasibility of hand-held thermal and UAV-based multispectral imaging for canopy water status assessment and yield prediction of irrigated African …

PR Mwinuka, BP Mbilinyi, WB Mbungu… - Agricultural Water …, 2021 - Elsevier
This study was conducted to evaluate the feasibility of a mobile phone-based thermal and
UAV-based multispectral imaging to assess the irrigation performance of African eggplant …

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 …

[HTML][HTML] Timely monitoring of soil water-salt dynamics within cropland by hybrid spectral unmixing and machine learning models

R Du, J Chen, Y Xiang, R Xiang, X Yang… - International Soil and …, 2024 - Elsevier
Soil salinization and water scarcity are main restrictive factors for irrigated agriculture
development in arid regions. Knowing dynamics of soil water and salt content is an …