Timely, accurate spatial information on the health of neglected and underutilised crop
species (NUS) is critical for optimising their production and food and nutrition in develo** …

The estimation of aboveground biomass (AGB) in agroforestry systems using remote
sensing has proliferated in the last decades. Similarly, machine learning is also being used …

Reliable crop type maps from satellite data are an essential prerequisite for quantifying crop
growth, health, and yields. However, such maps do not exist for most parts of Africa, where …

As agricultural land expansion is the primary driver of deforestation, agroforestry could be an
optimal land use strategy for climate change mitigation and reducing pressure on forests …

Knowledge of the soil water content (SWC) is important for many aspects of agriculture and
must be monitored to maximize crop yield, efficiently use limited supplies of irrigation water …

Low levels of agricultural productivity are associated with the persistence of food insecurity,
poverty, and other socio-economic stresses. Map** and monitoring agricultural dynamics …

Remote sensing imagery has been a key data source for precision agriculture. However,
high-resolution and/or hyperspectral imagery have typically been favored for their greater …

Multi-source remote sensing-derived information on crops contributes significantly to
agricultural monitoring, assessment, and management. In Africa, some challenges (ie, small …

Maintaining farm sustainability through optimizing the agricultural management practices
helps build more planet-friendly environment. The emerging satellite missions can acquire …

Trees in agroforestry parklands influence crops both through competitive and facilitative
mechanism, but the effects are challenging to disentangle due to the complexity of the …