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 …

This paper aims to provide a comprehensive review of the current state of drone technology
and its applications in the mining industry. The mining industry has shown increased interest …

Traditional imagery—provided, for example, by RGB and/or NIR sensors—has proven to be
useful in many agroforestry applications. However, it lacks the spectral range and precision …

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 …

The development and uptake of field deployable hyperspectral imaging systems within
environmental monitoring represents an exciting and innovative development that could …

Towards the need for sustainable development, remote sensing (RS) techniques in the
Visible-Near Infrared–Shortwave Infrared (VNIR–SWIR, 400–2500 nm) region could assist …

The study of grasslands using machine learning (ML) methods combined with
proximal/remote sensing data (RS) has been steadily increasing in the last decades …

In recent years, with the rapid development of unmanned aerial vehicles (UAVs) and
lightweight hyperspectral imaging (HSI) sensors, mini-UAV-borne hyperspectral remote …

Over the past decade, unmanned aerial vehicles (UAVs) have been used in the mining
industry for various applications from mineral exploration to mine reclamation. This study …

Accurate and efficient estimation of crop biophysical traits, such as leaf chlorophyll
concentrations (LCC) and average leaf angle (ALA), is an important bridge between …