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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Remote Estimation of Crop Chlorophyll Content Using Spectral Indices Derived From Hyperspectral Data
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Remote Estimation of Crop Chlorophyll Content Using Spectral Indices Derived From Hyperspectral Data

机译：利用从高光谱数据中得出的光谱指数远程估算作物叶绿素含量

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摘要

This paper examines the use of simulated and measured canopy reflectance for chlorophyll estimation over crop canopies. Field spectral measurements were collected over corn and wheat canopies in different intensive field campaigns organized during the growing seasons of 2004 and 2005. They were used to test and evaluate several combined indices for chlorophyll determination using hyperspectral imagery (Compact Airborne Spectrographic Imager). Several index combinations were investigated using both PROSPECT–SAILH canopy simulated spectra and field-measured reflectances. The relationships between leaf chlorophyll content and combined optical indices have shown similar trends for both PROSPECT–SAILH simulated data and ground-measured data sets, which indicates that both spectral measurements and radiative transfer models hold comparable potential for the quantitative retrieval of crop foliar pigments. The data set used has shown that crop type had a clear influence on the establishment of predictive equations as well as on their validation. In addition to generating different predictive equations, corn and wheat data yielded contrasting agreement between estimated and measured chlorophyll contents even for the same predictive algorithm. Among the set of indices tested in this paper, index combinations like Modified Chlorophyll Absorption Ratio Index/Optimized Soil-Adjusted Vegetation Index (OSAVI), Triangular Chlorophyll Index/OSAVI, Moderate Resolution Imaging Spectrometer Terrestrial Chlorophyll Index/Improved Soil-Adjusted Vegetation Index (MSAVI), and Red-Edge Model/MSAVI seem to be relatively consistent and more stable as estimators of crop chlorophyll content.
机译：本文研究了使用模拟和测量的冠层反射率估算作物冠层的叶绿素含量。在2004年和2005年生长季节组织的不同密集田间运动中，收集了玉米和小麦冠层的现场光谱测量结果。它们用于测试和评估使用高光谱图像（紧凑型机载光谱成像仪）测定叶绿素的多个综合指标。使用PROSPECT-SAILH冠层模拟光谱和现场测量的反射率研究了几种指数组合。对于PROSPECT-SAILH模拟数据和地面测量数据集，叶绿素含量与组合光学指数之间的关系显示出相似的趋势，这表明光谱测量和辐射转移模型在作物叶色素的定量检索中具有可比的潜力。所使用的数据集表明，农作物类型对预测方程的建立及其验证有着明显的影响。除了生成不同的预测方程式之外，即使对于相同的预测算法，玉米和小麦数据在估计和测量的叶绿素含量之间也产生了相反的一致性。在本文测试的一组指标中，指标组合包括改良的叶绿素吸收率指数/优化的土壤调整植被指数（OSAVI），三角叶绿素指数/ OSAVI，中等分辨率成像光谱仪陆地叶绿素指数/改良的土壤调整植被指数（ MSAVI）和Red-Edge Model / MSAVI作为作物叶绿素含量的估计值似乎相对一致且更稳定。

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