GPS, LiDAR and VNIR data to monitor the spatial behavior of grazing sheep

Traditional knowledge about the behavior of grazing livestock is to disappear. Shepherds well know that sheep follows non-random patterns. As a novel alternative seeking behavioral patterns, this study quantified activities two flocks Churra breed (both in same area but separated by 10 years) based on Global Position System (GPS) monitoring and remote sensing techniques. In first period (2009-10), geolocations were recorded every 5 min (4,240 records), while second one (2018-20), records taken 30 (7,636 records). The data clustered day/night activity (resting, moving, or grazing). An airborne LiDAR dataset was used slope, aspect, vegetation height. Four visible-infrared orthophotographs mosaicked classified obtain land use/land cover (LU/LC) map. Then, GPS locations overlain terrain features, Chi-square test evaluated relationships between features. Three spatial statistics (directional distribution, Kernel density, Hot Spot analysis) also calculated. Results both periods suggested distribution free-grazing ewes non-random. showed strong preferences for areas with gentle north-facing slopes, where herbaceous layer formed pasture predominates. geostatistical analyses corroborated those preferences. Geotechnologies have emerged as potent tool demonstrate influence environmental attributes sheep.