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Comparative Study on Crop Recognition of Landsat-OLI and RapidEye Data

机译:土地劳动力奥利和熊民数据作物识别的比较研究

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Remote sensing imagery derived from different sensors has different crop identification capability. due to the different spatial and temporal resolution, availability of certain spectral bands. Landsat OLI and RapidEye provide an important part of data sources for agricultural monitoring with a relative long historic records. As the availability of the data from these two sensors is totally different, an analysis of the crop identification capability using these sensors could provide the stakeholders data source selection for the operational perspectives. This paper took Bei'an city, Heilongjiang province as the study area, where major planted crops are maize and soybean. The authors used maximum likelihood classification methods to try tried to identify best registration phase, best spectral band combination for crop type identification in the study region. Especially, the authors evidenced the identification improvement contributed by the unique short infrared wave band from LANDSAT OLI and red edge band from RapidEye.
机译:源自不同传感器的遥感图像具有不同的作物识别能力。由于不同的空间和时间分辨率,某些光谱带的可用性。 Landsat Oli和Rapideye提供了具有相对悠久的历史记录的农业监测数据来源的重要组成部分。由于来自这两个传感器的数据的可用性完全不同,因此使用这些传感器的作物识别能力的分析可以为操作视角提供利益相关者数据源选择。本文采取了黑龙江省北安市作为研究区,主要种植的作物是玉米和大豆。作者使用了最大的似然分类方法来尝试识别研究区域中的作物类型鉴定的最佳配准阶段,最佳光谱带组合。特别是,作者证明了来自Rapideye的Landsat Oli和红色边缘带的独特短红外波段所贡献的识别改进。

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