High-throughput estimation of crop traits: A review of ground and aerial phenoty** platforms
Crop yields need to be improved in a sustainable manner to meet the expected worldwide
increase in population over the coming decades as well as the effects of anticipated climate …
increase in population over the coming decades as well as the effects of anticipated climate …
Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks
Big Data (BD), Machine Learning (ML) and Internet of Things (IoT) are expected to have a
large impact on Smart Farming and involve the whole supply chain, particularly for rice …
large impact on Smart Farming and involve the whole supply chain, particularly for rice …
Satellite remote sensing of vegetation phenology: Progress, challenges, and opportunities
Z Gong, W Ge, J Guo, J Liu - ISPRS Journal of Photogrammetry and …, 2024 - Elsevier
Vegetation phenology serves as a crucial indicator of ecosystem dynamics and its response
to environmental cues. Against the backdrop of global climate warming, it plays a pivotal role …
to environmental cues. Against the backdrop of global climate warming, it plays a pivotal role …
Forecasting vegetation indices from spatio-temporal remotely sensed data using deep learning-based approaches: A systematic literature review
Over the last few years, Deep learning (DL) approaches have been shown to outperform
state-of-the-art machine learning (ML) techniques in many applications such as vegetation …
state-of-the-art machine learning (ML) techniques in many applications such as vegetation …
Soil organic carbon prediction using phenological parameters and remote sensing variables generated from Sentinel-2 images
It is important to predict the spatial distribution of SOC accurately for migrating carbon
emission and sustainable soil management. Environmental variables influence the accuracy …
emission and sustainable soil management. Environmental variables influence the accuracy …
An intelligent system for crop identification and classification from UAV images using conjugated dense convolutional neural network
Crop identification and classification is an important aspect for modern agricultural sector.
With development of unmanned aerial vehicle (UAV) systems, crop identification from RGB …
With development of unmanned aerial vehicle (UAV) systems, crop identification from RGB …
[HTML][HTML] An architectural multi-agent system for a pavement monitoring system with pothole recognition in UAV images
In recent years, maintenance work on public transport routes has drastically decreased in
many countries due to difficult economic situations. The various studies that have been …
many countries due to difficult economic situations. The various studies that have been …
Develo** an operational algorithm for near-real-time monitoring of crop progress at field scales by fusing harmonized Landsat and Sentinel-2 time series with …
Crop phenology has been widely detected from multiple historical satellite observations.
Conversely, Near-Real-Time (NRT) monitoring of crop progress from timely available remote …
Conversely, Near-Real-Time (NRT) monitoring of crop progress from timely available remote …
UAV time-series imagery with novel machine learning to estimate heading dates of rice accessions for breeding
Timely monitoring of rice heading dates is essential for estimating growth status and grain
yield in rice breeding. This study aims to develop a machine learning method to classify …
yield in rice breeding. This study aims to develop a machine learning method to classify …
Remote estimation of grain yield based on UAV data in different rice cultivars under contrasting climatic zone
B Duan, S Fang, Y Gong, Y Peng, X Wu, R Zhu - Field Crops Research, 2021 - Elsevier
Timely and accurate estimation of grain yield is valuable for crop monitoring and breeding,
and plays an important role in precision agriculture. In this study, we developed a method to …
and plays an important role in precision agriculture. In this study, we developed a method to …