Information Processing in Agriculture2025，Vol.12Issue(2)：P.195-208,14.DOI:10.1016/j.inpa.2024.06.001
Vine yield estimation from block to regional scale employing remote sensing,weather,and management data
Pedro C.Towers 1Sean E.Roulet 2Carlos Poblete-Echeverría3
作者信息
- 1. South African Grape and Wine Research Institute(SAGWRI),Department of Viticulture and Oenology,Faculty of AgriSciences,Stellenbosch University,Matieland 7602,South Africa AgriSat SA—Remote Sensing for Agriculture,Pasaje La Loma 983,(5178)La Cumbre,Córdoba,Argentina
- 2. AgriSat SA—Remote Sensing for Agriculture,Pasaje La Loma 983,(5178)La Cumbre,Córdoba,Argentina
- 3. South African Grape and Wine Research Institute(SAGWRI),Department of Viticulture and Oenology,Faculty of AgriSciences,Stellenbosch University,Matieland 7602,South Africa
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摘要
关键词
Precision viticulture/Remote sensing/Spatial variability/Machine learning/Random Forest/Partial least square regression/Landsat分类
农业科技引用本文复制引用
Pedro C.Towers,Sean E.Roulet,Carlos Poblete-Echeverría..Vine yield estimation from block to regional scale employing remote sensing,weather,and management data[J].Information Processing in Agriculture,2025,12(2):P.195-208,14.
