基于Sentinel-2的葡萄牙年度作物分类试验

P. Benevides, H. Costa, Francisco D. Moreira, Daniel Moraes, M. Caetano
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引用次数: 5

摘要

本文采用位于阿连特茹地区的研究区,对葡萄牙最丰富的10种一年生作物类型进行了试验分类。这个地区的土地用途非常多样化,作物类型也多种多样。实验中考虑了Sentinel-2 2018年年内时间序列图像。使用葡萄牙土地包裹识别系统(LPIS)提取自动训练样本。LPIS信息在辅助数据集的帮助下自动处理,以过滤掉更可能被错误标记的作物区域。使用随机森林进行分类。使用同样基于LPIS的独立数据集执行验证。得到了76%的全局精度。该方法的新颖性表明,LPIS可以与辅助数据一起用于作物类型制图,有助于描绘葡萄牙农业土地多样性的特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Annual Crop Classification Experiments in Portugal Using Sentinel-2
This paper presents an experimental crop classification of the 10 most abundant annual crop types in Portugal, using a study area located in Alentejo region. This region has great diversity of land uses as well as multiple crop types. Sentinel-2 2018 intra-annual time-series imagery is considered in the experiment. The Portuguese Land Parcel Identification System (LPIS) is used to extract automatic training samples. LPIS information is automatically processed with the help of auxiliary datasets to filter out crop areas more likely to have been mislabeled. Classification is obtained using random forest. Validation is performed using an independent dataset also based on LPIS. A global accuracy of 76% is obtained. The novelty of the methodology here presented shows that LPIS can be used together with auxiliary data for crop type mapping, helping to characterize the agriculture land diversity in Portugal.
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