Airborne remote-sensing has been identified worldwide as a promising technique for
identifying and map** weeds in crops, and potentially offers a solution to the current …

The timely and accurate quantification of grassland biomass is a prerequisite for sustainable
grazing management. With advances in artificial intelligence, the launch of new satellites …

The total biomass of a tall fescue (Festuca arundinacea var. Fletcher) pasture was assessed
by using a vehicle mounted light detection and ranging (LiDAR) unit to derive canopy height …

Map** crop within-field yield variability provide an essential piece of information for
precision agriculture applications. Leaf Area Index (LAI) is an important parameter that …

Robust quantification of vegetative biomass using satellite imagery using one or more forms
of machine learning (ML) has hitherto been hindered by the extent and quality of training …

Chlorophyll red-edge descriptors have been used to estimate leaf nitrogen concentration in
ryegrass (Lolium spp.) pasture. Two-layer model calculations have been used to predict the …

Three years of summer field studies (2002–2004) were conducted at two sites in the Central
Italian Alps. Field spectroradiometer data were acquired on different vegetation typologies …

Biomass measurements of totora and bofedal Andean wetland grasses in the Bolivian
Northern Altiplano were correlated over a growing season to vegetation indices derived from …

The accurate instance segmentation of individual crop plants is crucial for achieving a high-
throughput phenotypic analysis of seedlings and smart field management in agriculture …

Understanding the temporal and spatial variability in a crop yield is viewed as one of the key
steps in the implementation of precision agriculture practices. Therefore, a study on a center …