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Efficiency of crop identification based on optical and SAR image time series

机译:基于光学和SAR图像时间序列的农作物识别效率

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This paper assessed the use of optical and SAR imagery for crop identification in an operational context with a particular emphasis on actual crop diversity and information delivery time. Fifteen ERS and Radarsat and 3 optical images were used to discriminate agricultural crop types based on dedicated per-parcel classification and photo interpretation schemes. For crop area control, the efficiency concept was introduced as a complementary indicator of classification performance. A set of 6571 parcels were classified into 39 crop types from various combinations of images. The efficiency computed from an independent set of 899 parcels peaked based on a combination of optical images and 3 to 5 SAR images. Moreover, the delivery time of the relevant information was improved when SAR data was included. The hierarchical classification strategy based on nested classifications also improved the operational crop control system for all image combinations. Finally, this research documented the respective contributions of optical and SAR time series for any control system of agricultural land. (c) 2005 Elsevier Inc. All rights reserved.
机译:本文评估了在操作环境中使用光学和SAR图像进行作物鉴定的方法,并特别强调了实际的作物多样性和信息传递时间。基于专用的每件包裹分类和照片解释方案,使用了15个ERS和Radarsat以及3个光学图像来区分农作物类型。对于作物面积控制,引入了效率概念作为分类性能的补充指标。从各种图像组合中将一组6571个包裹分类为39种农作物类型。根据光学图像和3至5个SAR图像的组合,从一组独立的899个包裹中计算出的效率达到峰值。此外,当包含SAR数据时,相关信息的传递时间得以缩短。基于嵌套分类的分层分类策略还针对所有图像组合改进了操作性作物控制系统。最后,本研究记录了光学和SAR时间序列对任何农用土地控制系统的各自贡献。 (c)2005 Elsevier Inc.保留所有权利。

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