Využitie UAV snímok na poloautomatickú detekciu výpadkov viniča vo vinohradoch Jelenca a Topoľčianok (Slovensko)

The use of UAV (Unmanned Aerial Vehicles) in precision viticulture leads to a more flexible and efficient approach vineyard management. Images from help determine the condition vineyard. Identification missing roots row by semi-automatic image classification its comparison with manual is goal paper. This study presents new methodology for segmentation vine gaps. RGB (Red-Green-Blue) images, multispectral Near-Infrared (NIR) Normalized Differential Vegetation Index (NDVI) images were tested compared classification. percentage gap accuracy individual determined. Object-oriented gaps buffer zone core our method. Using geostatistical methods, such as zonal logistic regression statistics, data zones was evaluated. Areas interest parts vineyards Jelenec Topoľčianky. Success method detectomg outage (compared classification) achieved spectrum: 96.45% 82.61% Topoľčianky By this method, we quickly gaps/vine which can be used optimize or reduce application fertilizers only on vine. also inspection authorities reveal actual