Optical vegetation indices for monitoring terrestrial ecosystems globally

Y Zeng, D Hao, A Huete, B Dechant, J Berry… - Nature Reviews Earth & …, 2022 - nature.com
Vegetation indices (VIs), which describe remotely sensed vegetation properties such as
photosynthetic activity and canopy structure, are widely used to study vegetation dynamics …

[HTML][HTML] Drones in agriculture: A review and bibliometric analysis

A Rejeb, A Abdollahi, K Rejeb, H Treiblmaier - Computers and electronics …, 2022 - Elsevier
Abstract Drones, also called Unmanned Aerial Vehicles (UAV), have witnessed a
remarkable development in recent decades. In agriculture, they have changed farming …

[HTML][HTML] Remote sensing of soil degradation: Progress and perspective

J Wang, J Zhen, W Hu, S Chen, I Lizaga… - International Soil and …, 2023 - Elsevier
Soils constitute one of the most critical natural resources and maintaining their health is vital
for agricultural development and ecological sustainability, providing many essential …

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 …

Remote sensing in agriculture—accomplishments, limitations, and opportunities

S Khanal, K Kc, JP Fulton, S Shearer, E Ozkan - Remote Sensing, 2020 - mdpi.com
Remote sensing (RS) technologies provide a diagnostic tool that can serve as an early
warning system, allowing the agricultural community to intervene early on to counter …

Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: A review

A Chlingaryan, S Sukkarieh, B Whelan - Computers and electronics in …, 2018 - Elsevier
Accurate yield estimation and optimised nitrogen management is essential in agriculture.
Remote sensing (RS) systems are being more widely used in building decision support tools …

A review of machine learning in processing remote sensing data for mineral exploration

H Shirmard, E Farahbakhsh, RD Müller… - Remote Sensing of …, 2022 - Elsevier
The decline of the number of newly discovered mineral deposits and increase in demand for
different minerals in recent years has led exploration geologists to look for more efficient and …

A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction

M Rashid, BS Bari, Y Yusup, MA Kamaruddin… - IEEE …, 2021 - ieeexplore.ieee.org
An early and reliable estimation of crop yield is essential in quantitative and financial
evaluation at the field level for determining strategic plans in agricultural commodities for …

Multi-sensor remote sensing for drought characterization: current status, opportunities and a roadmap for the future

W Jiao, L Wang, MF McCabe - Remote Sensing of Environment, 2021 - Elsevier
Satellite based remote sensing offers one of the few approaches able to monitor the spatial
and temporal development of regional to continental scale droughts. A unique element of …

Forest aboveground biomass estimation using Landsat 8 and Sentinel-1A data with machine learning algorithms

Y Li, M Li, C Li, Z Liu - Scientific reports, 2020 - nature.com
Forest aboveground biomass (AGB) plays an important role in the study of the carbon cycle
and climate change in the global terrestrial ecosystem. AGB estimation based on remote …