Forecasting crop yields, or providing an expectation of ex-ante harvest amounts, is highly
relevant to the whole agricultural production chain. Farmers can adapt their management …

Unmanned Aerial Vehicles (UAVs) are an alternative to costly and time-consuming
traditional methods to improve agricultural water management and crop productivity through …

In this paper, we provide a review of the research dedicated to applications of data science
techniques, and especially machine learning techniques, in relevant agricultural systems …

Accurate spatial information of agricultural fields in smallholder farms is important for
providing actionable information to farmers, managers, and policymakers. Very High …

New Earth observation missions and technologies are delivering large amounts of data.
Processing this data requires develo** and evaluating novel dimensionality reduction …

The aim of this study was to use small unmanned aerial vehicles (UAVs) for determining
high-resolution normalized difference vegetation index (NDVI) values. Subsequently, these …

Crop type information is essential for many practical applications, yet its map** is often
constrained by inherent characteristics of most farming areas, such as fragmentation and …

Smallholder farmers cultivate more than 80% of the cropland area available in Africa. The
intrinsic characteristics of such farms include complex crop-planting patterns, and small …

The production of land cover maps through satellite image classification is a frequent task in
remote sensing. Random Forest (RF) and Support Vector Machine (SVM) are the two most …

Workflow engines are commonly used to orchestrate large-scale scientific computations
such as, but not limited to weather, climate, natural disasters, food safety, and territorial …