Semantic segmentation dataset of Land Use/Cover Area frame Survey (LUCAS) rural landscape Street View Images.

Urban focused semantically segmented datasets (e.g. ADE20k or CoCo) have been crucial in boosting research and applications in urban areas by providing rich sources of delineated objects in Street View Images (SVI).

Crop Identification Using Deep Learning on LUCAS Crop Cover Photos.

Massive and high-quality in situ data are essential for Earth-observation-based agricultural monitoring. However, field surveying requires considerable organizational effort and money. Using computer vision to recognize crop types on geo-tagged photos could be a game changer allowing for the provision of timely and accurate crop-specific information.

Cognitive Keys in Psychophysical Estimation of Chemosensory Perception in University Students.

Psychophysical methods allow us to measure the relationship between stimuli and sensory perception. Of these, Detection Threshold (DT) allows us to know the minimum concentration to produce taste identification. Given this, we wonder whether, for example, wine tasting experts are more capable of perceiving their sensory properties than other people, or whether they can distinguish them because they are better able to "describe" them.

Harmonised LUCAS in-situ land cover and use database for field surveys from 2006 to 2018 in the European Union.

Accurately characterizing land surface changes with Earth Observation requires geo-located ground truth. In the European Union (EU), a tri-annual surveyed sample of land cover and land use has been collected since 2006 under the Land Use/Cover Area frame Survey (LUCAS). A total of 1351293 observations at 651780 unique locations for 106 variables along with 5.