首页> 外文会议>European Space Agency;Living planet symposium;EUMETSAT;European Commission >COMPARING THE POTENTIAL OF THE SENTINEL-2 MSI AND THE FUTURE EnMAP HIS FOR THE RETRIEVAL OF WINTER WHEAT CROP PARAMETERS IN SOUTHERN GERMANY
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COMPARING THE POTENTIAL OF THE SENTINEL-2 MSI AND THE FUTURE EnMAP HIS FOR THE RETRIEVAL OF WINTER WHEAT CROP PARAMETERS IN SOUTHERN GERMANY

机译:比较SENTINEL-2 MSI和未来Enmap HIS的潜力,以检索德国南部的冬小麦作物参数

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摘要

This study tests the effect of improved spectral resolution on different approaches for the estimation of crop biophysical variables of winter wheat in Southern Germany by comparing the existing Sentinel-2 MSI with the future EnMAP HSI. The experiment is based on simulated sensor data of both Sentinel-2 and EnMAP, with their individual spectral configurations and radiometric properties taken into account. An advanced multispectral setup, such as provided by Sentinel-2, proved to enable reasonable estimation of biophysical variables by applying machine learning algorithms. The augmented information content inherent in hyperspectral signatures, however, marks an advantage for the creation of novel narrow-band indices (RMSE improvement of 10.0%) and for the inversion of canopy reflectance models like PROSAIL independent from in-situ data (RMSE improvement of 18.7%). With the notable advantages of Sentinel-2 – higher revisit rates and better spectral resolution – new synergies are expected to arise, once both instruments will be operating in parallel configuration.
机译:这项研究通过比较现有的Sentinel-2 MSI和未来的EnMAP HSI,测试了光谱分辨率提高对德国南部冬小麦作物生物物理变量估计的不同方法的影响。该实验基于Sentinel-2和EnMAP的模拟传感器数据,并考虑了它们各自的光谱配置和辐射特性。先进的多光谱设置(例如Sentinel-2提供)被证明可以通过应用机器学习算法来合理估计生物物理变量。然而,高光谱信号固有的增强信息内容标志着创建新的窄带指数(RMSE提高了10.0%)和独立于原位数据的PROSAIL之类的冠层反射模型(RMSE改进了20%)的优势。 18.7%)。凭借Sentinel-2的显着优势-更高的重访率和更好的光谱分辨率-一旦两台仪器都将以并行配置运行,就有望产生新的协同效应。

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  • 会议地点 Prague(CZ)
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    Ludwig-Maximilians-University, Department of Geography: Luisenstr. 37, 80333 Munich, Germanymartin.danner@iggf.geo.uni-muenchen.de;

    Ludwig-Maximilians-University, Department of Geography: Luisenstr. 37, 80333 Munich, Germany;

    Ludwig-Maximilians-University, Department of Geography: Luisenstr. 37, 80333 Munich, Germany;

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