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Table 5: Final models used to predict canopy attributes from Landsat spectral reflectance data and derived spectral and texture indices based on N = 109 data points.

机译：表5：最终模型用于预测来自Landsat光谱反射数据和基于n = 109个数据点的源极谱和纹理指数的顶篷属性。

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1. Assessment of several spectral indices derived from multi-temporal Landsat data for fire occurrence probability modelling [J] . F. Javier Lozano, Susana Suarez-Seoane, Estanislao de Luis Remote Sensing of Environment: An Interdisciplinary Journal . 2007,第4期

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3. New Reflectance Spectral Vegetation Indices for Estimating Rice Nitrogen Nutrition III: Development of a New Vegetation Index Based on Canopy Red-Edge Reflectance Spectra to Monitor Rice Canopy Leaf Nitrogen Concentration [J] . Jinheng Zhang, Yongliang Lv, Chao Han, Sensor Letters: A Journal Dedicated to all Aspects of Sensors in Science, Engineering, and Medicine . 2011,第3期

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4. Canopy optical indices from infinite reflectance and canopy reflectance models for forest condition monitoring: application to hyperspectral CASI data [C] . Zarco-Tejada, P.J., Miller, Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International . 1999

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5. Evaluation of Landsat Data Pre-Processing Effects on Spectral Indices and Water Surface Area Estimation [D] . Gettinger, Abigail L. 2021

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6. Predicting grain yield using canopy hyperspectral reflectance in wheat breeding data [O] . Osval A. Montesinos-López, Abelardo Montesinos-López, José Crossa, 2017

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Table 5: Final models used to predict canopy attributes from Landsat spectral reflectance data and derived spectral and texture indices based on N = 109 data points.

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