Challenges and opportunities in remote sensing-based crop monitoring: A review

B Wu, M Zhang, H Zeng, F Tian… - National Science …, 2023 - academic.oup.com
Building a more resilient food system for sustainable development and reducing uncertainty
in global food markets both require concurrent and near-real-time and reliable crop …

Can yield prediction be fully digitilized? A systematic review

N Darra, E Anastasiou, O Kriezi, E Lazarou, D Kalivas… - Agronomy, 2023 - mdpi.com
Going beyond previous work, this paper presents a systematic literature review that explores
the deployment of satellites, drones, and ground-based sensors for yield prediction in …

Complementary use of ground-based proximal sensing and airborne/spaceborne remote sensing techniques in precision agriculture: A systematic review

A Alexopoulos, K Koutras, SB Ali, S Puccio, A Carella… - Agronomy, 2023 - mdpi.com
As the global population continues to increase, projected to reach an estimated 9.7 billion
people by 2050, there will be a growing demand for food production and agricultural …

Seasonal dynamics of fallow and crop** lands in the broadacre crop** region of Australia

Z ** via UAV-based imaging, modelling, and machine learning
Q Chen, B Zheng, K Chenu, P Hu, SC Chapman - Plant Phenomics, 2022 - spj.science.org
High-throughput phenoty** has become the frontier to accelerate breeding through linking
genetics to crop growth estimation, which requires accurate estimation of leaf area index …

Early crop classification via multi-modal satellite data fusion and temporal attention

F Weilandt, R Behling, R Goncalves, A Madadi… - Remote Sensing, 2023 - mdpi.com
In this article, we propose a deep learning-based algorithm for the classification of crop
types from Sentinel-1 and Sentinel-2 time series data which is based on the celebrated …

Comparing machine and deep learning methods for the phenology-based classification of land cover types in the Amazon biome using Sentinel-1 time series

IAL Magalhães, OA de Carvalho Júnior… - Remote Sensing, 2022 - mdpi.com
The state of Amapá within the Amazon biome has a high complexity of ecosystems formed
by forests, savannas, seasonally flooded vegetation, mangroves, and different land uses …

Computer vision and deep learning as tools for leveraging dynamic phenological classification in vegetable crops

L Rodrigues, SA Magalhães, DQ da Silva… - Agronomy, 2023 - mdpi.com
The efficiency of agricultural practices depends on the timing of their execution.
Environmental conditions, such as rainfall, and crop-related traits, such as plant phenology …