基于Sentinel-1反向散射的小麦和大麦田分类

I. Pfeil, F. Reuß, M. Vreugdenhil, C. Navacchi, W. Wagner
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引用次数: 2

摘要

作物类型分布的知识对于从区域到全球范围的许多应用都非常重要。包括微波遥感在内的不同技术已经发展到自动化、精确的作物制图,然而,具有相似形态和物候特征的作物的识别仍然是一个挑战。本文采用统计方法和长短期记忆网络对Sentinel-1卫星c波段SAR仪器观测到的后向散射进行区分,研究了小麦田和大麦田的区别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of Wheat and Barley Fields Using Sentinel-1 Backscatter
The knowledge of the distribution of crop types is of great importance to numerous applications at regional to global scales. Different techniques, including microwave remote sensing methods, have been developed for automatized, accurate crop mapping, however, the discrimination of crops with similar morphology and phenology remains a challenge. In this study, we investigate how to distinguish wheat and barley fields by applying statistical methods and a long-short term memory network to backscatter observed by the C-band SAR instrument onboard the Sentinel-1 satellite.
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