During the last few years, Unmanned Aerial Vehicles (UAVs) technologies are widely used
to improve agriculture productivity while reducing drudgery, inspection time, and crop …

In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …

Vegetation phenology is the study of recurring plant life cycle stages, seasonality which is
linked to many ecosystem processes and is an important proxy of climate and environmental …

Climate change represents one of the most critical threats to biodiversity with far-reaching
consequences for species interactions, the functioning of ecosystems, or the assembly of …

This work explores the combination of free cloud computing, free open-source software, and
deep learning methods to analyze a real, large-scale problem: the automatic country-wide …

The major part of the population lives in urban areas, and this is expected to increase in the
future. The main challenges faced by cities currently and towards the future are the rapid …

Deep learning is a powerful tool for automating the process of recognizing and classifying
objects in images. In this study, we used ML. NET, a popular open-source machine learning …

Conservation practitioners require cost-effective and repeatable remotely sensed data for
assistive monitoring. This paper tests the ability of standard remotely piloted aircraft (DJI …

Remote sensing images are crucial for finding spatial and temporal patterns in vegetation.
The Guadiana river (located in South West Spain) has been invaded since the early 2000s …

When doctors are fatigued, they often make diagnostic errors. Similarly, pharmacists may
also make mistakes in dispensing medication. Therefore, object segmentation plays a vital …