地球空间信息科学学报（英文版）2025，Vol.28Issue(3)：封2,815-830,17.DOI:10.1080/10095020.2024.2341748
Crop classification in Google Earth Engine:leveraging Sentinel-1,Sentinel-2,European CAP data,and object-based machine-learning approaches
Crop classification in Google Earth Engine:leveraging Sentinel-1,Sentinel-2,European CAP data,and object-based machine-learning approaches
Marco Vizzari 1Giacomo Lesti 1Siham Acharki2
作者信息
- 1. Department of Agricultural,Food,and Environmental Sciences,University of Perugia,Perugia,Italy
- 2. Department of Earth Sciences,Faculty of Sciences and Technologies of Tangier(FSTT),Abdelmalek Essaadi University,Tetouan City,Morocco
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摘要
关键词
Machine learning/random forest/IACS/CAP/winter cereals/summer crops/SNIC/GLCM/Radar vegetation index(RVI)/NDVI/precision agricultureKey words
Machine learning/random forest/IACS/CAP/winter cereals/summer crops/SNIC/GLCM/Radar vegetation index(RVI)/NDVI/precision agriculture引用本文复制引用
Marco Vizzari,Giacomo Lesti,Siham Acharki..Crop classification in Google Earth Engine:leveraging Sentinel-1,Sentinel-2,European CAP data,and object-based machine-learning approaches[J].地球空间信息科学学报（英文版）,2025,28(3):封2,815-830,17.
