Adapting a regularized canopy reflectance model (REGFLEC) for the retrieval challenges of dryland agricultural systems
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- 作者：Rasmus Houborg ; rasmus.houborg@kaust.edu.sa" class="auth_mail" title="E-mail the corresponding author ; Matthew F. McCabe
- 关键词：LAI ; Leaf chlorophyll ; REGFLEC ; RapidEye ; Red-edge ; Aerosols ; Foliar dust ; Adjacency effects ; Precision agriculture
- 刊名：Remote Sensing of Environment
- 出版年：2016
- 出版时间：1 December 2016
- 年：2016
- 卷：186
- 期：Complete
- 页码：105-120
- 全文大小：2753 K
文摘
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Drylands present a challenging landscape for LAI and leaf chlorophyll (Chll) estimation.
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LAI and Chll were retrieved with mean absolute errors of 12% and 16%, respectively.
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Correction for adjacency effects reduced reflectances with up to 60%.
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Considering adjacency effects and foliar dust reduced negative biases in LAI.
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Integration of red-edge and empirical LAI helped constrain the inversion process.