Remote sensing for agricultural applications: A meta-review

M Weiss, F Jacob, G Duveiller - Remote sensing of environment, 2020 - Elsevier
Agriculture provides humanity with food, fibers, fuel, and raw materials that are paramount
for human livelihood. Today, this role must be satisfied within a context of environmental …

Quantitative remote sensing at ultra-high resolution with UAV spectroscopy: a review of sensor technology, measurement procedures, and data correction workflows

H Aasen, E Honkavaara, A Lucieer, PJ Zarco-Tejada - Remote Sensing, 2018 - mdpi.com
In the last 10 years, development in robotics, computer vision, and sensor technology has
provided new spectral remote sensing tools to capture unprecedented ultra-high spatial and …

A systematic review on advancements in remote sensing for assessing and monitoring land use and land cover changes impacts on surface water resources in semi …

MJ Mashala, T Dube, BT Mudereri, KK Ayisi… - Remote Sensing, 2023 - mdpi.com
This study aimed to provide a systematic overview of the progress made in utilizing remote
sensing for assessing the impacts of land use and land cover (LULC) changes on water …

Estimation of winter wheat above-ground biomass using unmanned aerial vehicle-based snapshot hyperspectral sensor and crop height improved models

J Yue, G Yang, C Li, Z Li, Y Wang, H Feng, B Xu - Remote Sensing, 2017 - mdpi.com
Correct estimation of above-ground biomass (AGB) is necessary for accurate crop growth
monitoring and yield prediction. We estimated AGB based on images obtained with a …

Improving unmanned aerial vehicle remote sensing-based rice nitrogen nutrition index prediction with machine learning

H Zha, Y Miao, T Wang, Y Li, J Zhang, W Sun, Z Feng… - Remote Sensing, 2020 - mdpi.com
Optimizing nitrogen (N) management in rice is crucial for China's food security and
sustainable agricultural development. Nondestructive crop growth monitoring based on …

Object-based mangrove species classification using unmanned aerial vehicle hyperspectral images and digital surface models

J Cao, W Leng, K Liu, L Liu, Z He, Y Zhu - Remote Sensing, 2018 - mdpi.com
Mangroves are one of the most important coastal wetland ecosystems, and the compositions
and distributions of mangrove species are essential for conservation and restoration efforts …

Combining color indices and textures of UAV-based digital imagery for rice LAI estimation

S Li, F Yuan, ST Ata-UI-Karim, H Zheng, T Cheng… - Remote Sensing, 2019 - mdpi.com
Leaf area index (LAI) is a fundamental indicator of plant growth status in agronomic and
environmental studies. Due to rapid advances in unmanned aerial vehicle (UAV) and sensor …

Machine learning to estimate surface soil moisture from remote sensing data

H Adab, R Morbidelli, C Saltalippi, M Moradian… - Water, 2020 - mdpi.com
Soil moisture is an integral quantity parameter in hydrology and agriculture practices.
Satellite remote sensing has been widely applied to estimate surface soil moisture …

Estimating leaf area index using unmanned aerial vehicle data: shallow vs. deep machine learning algorithms

S Liu, X Jin, C Nie, S Wang, X Yu, M Cheng… - Plant …, 2021 - academic.oup.com
Measuring leaf area index (LAI) is essential for evaluating crop growth and estimating yield,
thereby facilitating high-throughput phenotyping of maize (Zea mays). LAI estimation models …

Monitoring within-field variability of corn yield using Sentinel-2 and machine learning techniques

A Kayad, M Sozzi, S Gatto, F Marinello, F Pirotti - Remote Sensing, 2019 - mdpi.com
Monitoring and prediction of within-field crop variability can support farmers to make the right
decisions in different situations. The current advances in remote sensing and the availability …