Identifying and characterizing vascular plants in time and space is required in various
disciplines, eg in forestry, conservation and agriculture. Remote sensing emerged as a key …

The coffee sector is working towards sector-wide commitments for sustainable production.
Yet, knowledge of where coffee is cultivated and its environmental impact remains limited, in …

Invasion of the Polygraphus proximus Blandford bark beetle causes catastrophic damage to
forests with firs (Abies sibirica Ledeb) in Russia, especially in Central Siberia. Determining …

Unmanned aerial vehicles (UAVs) coupled with machine learning approaches have
attracted considerable interest from academicians and industrialists. UAVs provide the …

Soil degradation processes are widespread on agricultural land. Ground-based methods for
detecting degradation require a lot of labor and time. Remote methods based on the …

In the production process from green beans to coffee bean packages, the defective bean
removal (or in short, defect removal) is one of most labor-consuming stages, and many …

This research proposed novel technique in crop monitoring system using machine learning-
based classification using UAV. To monitor and operate activities from remote locations …

In the context of agribusiness, the task of tree detection and counting is fundamental for
updating the forest inventory and the management plan of a farm. Because it constitutes an …

Accurate information on the spatial distribution of plant species and communities is in high
demand for various fields of application, such as nature conservation, forestry, and …

The detection of degraded soil distribution areas is an urgent task. It is difficult and very time
consuming to solve this problem using ground methods. The modeling of degradation …