Soil available nutrients are crucial for promoting crop growth, and controlling their content is
essential for increasing yield, promoting smart agriculture, and protecting the environment …

Support vector machines (SVMs) are well-established classifiers that are effectively
deployed in an array of classification tasks. In this article, we consider extending classical …

Cloud detection is a pivotal satellite image pre-processing step that can be performed on
board a satellite to tag useful images. It can reduce the amount of data to downlink by …

Soil organic matter (SOM) is the main source of soil nutrients. Rapid determination of SOM
content is of great significance for guiding field management. The change of SOM content …

Remote sensing data has been widely used for various Earth Observation (EO) missions
such as land use and cover classification, weather forecasting, agricultural management …

This paper takes a look at the state-of-the-art solutions in the field of spectral imaging
systems by way of application examples. It is based on a comparison of currently used …

Remote sensing (RS) applications in the space domain demand machine learning (ML)
models that are reliable, robust, and quality-assured, making red teaming a vital approach …

The objective of this work is to propose the use of FarmO'Cart, a cutting-edge online
marketing platform, as an effective solution to modernize conventional agricultural trading …

Enhancing agricultural methods through the utilization of Earth observation and artificial
intelligence (AI) has emerged as a significant concern. The ability to quantify soil parameters …

In this paper, the problem of generating (hallucinating) a high-resolution hyperspectral
image from a single low-resolution raw-RGB image is considered. To solve this problem, a …