Review of synthetic aperture radar with deep learning in agricultural applications

MGZ Hashemi, E Jalilvand, H Alemohammad… - ISPRS Journal of …, 2024 - Elsevier
Abstract Synthetic Aperture Radar (SAR) observations, valued for their consistent acquisition
schedule and not being affected by cloud cover and variations between day and night, have …

Estimation of sugar content in wine grapes via in situ VNIR–SWIR point spectroscopy using explainable artificial intelligence techniques

E Kalopesa, K Karyotis, N Tziolas, N Tsakiridis… - Sensors, 2023 - mdpi.com
Spectroscopy is a widely used technique that can contribute to food quality assessment in a
simple and inexpensive way. Especially in grape production, the visible and near infrared …

Improved prediction of rice yield at field and county levels by synergistic use of SAR, optical and meteorological data

W Yu, G Yang, D Li, H Zheng, X Yao, Y Zhu… - Agricultural and Forest …, 2023 - Elsevier
Timely and accurate rice yield prediction over large regions is imperative to making informed
decisions on precision crop management and ensuring regional food security. Previous …

[HTML][HTML] Multispectral satellite image analysis for computing vegetation indices by R in the Khartoum Region of Sudan, Northeast Africa

P Lemenkova, O Debeir - Journal of imaging, 2023 - mdpi.com
Desertification is one of the most destructive climate-related issues in the Sudan–Sahel
region of Africa. As the assessment of desertification is possible by satellite image analysis …

[HTML][HTML] Combination of Remote Sensing and Artificial Intelligence in Fruit Growing: Progress, Challenges, and Potential Applications

DEG Furuya, ÉL Bolfe, TC Parreiras, JGA Barbedo… - Remote Sensing, 2024 - mdpi.com
Fruit growing is important in the global agricultural economy, contributing significantly to
food security, job creation, and rural development. With the advancement of technologies …

Optimal integration of optical and SAR data for improving alfalfa yield and quality traits prediction: new insights into satellite-based forage crop monitoring

J Chen, T Yu, JH Cherney, Z Zhang - Remote Sensing, 2024 - mdpi.com
Global food security and nutrition is suffering from unprecedented challenges. To reach a
world without hunger and malnutrition by implementing precision agriculture, satellite …

The response of yield, number of clusters, and cluster weight to meteorological factors and irrigation practices in grapevines: A multi-experiment study

N Ohana-Levi, Y Cohen, S Munitz, R Michaelovsky… - Scientia …, 2024 - Elsevier
Abstract Knowledge of the yield components of wine grapevines is essential to achieve
target production and effectively design vineyard management. Therefore, it is necessary to …

[HTML][HTML] Oilseed Rape Yield Prediction from UAVs Using Vegetation Index and Machine Learning: A Case Study in East China

H Hu, Y Ren, H Zhou, W Lou, P Hao, B Lin, G Zhang… - Agriculture, 2024 - mdpi.com
Yield prediction is an important agriculture management for crop policy making. In recent
years, unmanned aerial vehicles (UAVs) and spectral sensor technology have been widely …

Toward understanding land use land cover changes and their effects on land surface temperature in yam production area, Côte d'Ivoire, Gontougo Region, using …

KSR Aka, S Akpavi, NDH Dibi, AT Kabo-Bah… - Frontiers in Remote …, 2023 - frontiersin.org
Land use and land cover (LULC) changes are one of the main factors contributing to
ecosystem degradation and global climate change. This study used the Gontougo Region …

Multispectral indices for wildfire management

A Oliveira, JP Matos-Carvalho, F Moutinho… - arXiv preprint arXiv …, 2023 - arxiv.org
This paper highlights and summarizes the most important multispectral indices and
associated methodologies for fire management. Various fields of study are examined where …