Remote sensing retrieval of winter wheat leaf area index and canopy chlorophyll density at different growth stages

IF 4.2 3区 地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Naichen Xing, Wenjiang Huang, H. Ye, Yingying Dong, Weiping Kong, Yu Ren, Qiaoyun Xie
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引用次数: 2

Abstract

ABSTRACT Leaf area index (LAI) and canopy chlorophyll density (CCD) are key indicators of crop growth status. In this study, we compared several vegetation indices and their red-edge modified counterparts to evaluate the optimal red-edge bands and the best vegetation index at different growth stages. The indices were calculated with Sentinel-2 MSI data and hyperspectral data. Their performances were validated against ground measurements using R2, RMSE, and bias. The results suggest that indices computed with hyperspectral data exhibited higher R2 than multispectral data at the late jointing stage, head emergence stage, and filling stage. Furthermore, red-edge modified indices outperformed the traditional indices for both data genres. Inversion models indicated that the indices with short red-edge wavelengths showed better estimation at the early jointing and milk development stage, while indices with long red-edge wavelength estimate the sought variables better at the middle three stages. The results were consistent with the red-edge inflection point shift at different growth stages. The best indices for Sentinel-2 LAI retrieval, Sentinel-2 CCD retrieval, hyperspectral LAI retrieval, and hyperspectral CCD retrieval at five growth stages were determined in the research. These results are beneficial to crop trait monitoring by providing references for crop biophysical and biochemical parameters retrieval.
冬小麦不同生育期叶面积指数和冠层叶绿素密度的遥感反演
叶面积指数(LAI)和冠层叶绿素密度(CCD)是反映作物生长状况的关键指标。本研究通过比较几种植被指数及其红边修正值,评价了不同生长阶段的最佳红边带和最佳植被指数。利用Sentinel-2 MSI数据和高光谱数据计算各指数。使用R2、RMSE和偏差对地面测量结果进行了验证。结果表明,拔节后期、抽穗期和灌浆期,利用高光谱数据计算的指标R2均高于多光谱数据。此外,红边修正指数在两种数据类型上的表现都优于传统指数。反演模型表明,红边波长较短的指标对拔节前期和发乳期的拟合效果较好,而红边波长较长的指标对拔节前期和发乳期的拟合效果较好。结果与不同生长阶段红边拐点的变化一致。研究确定了5个生长阶段Sentinel-2 LAI、Sentinel-2 CCD、高光谱LAI和高光谱CCD的最佳检索指标。这些结果有利于作物性状监测,为作物生物物理生化参数检索提供参考。
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来源期刊
Big Earth Data
Big Earth Data Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
7.40
自引率
10.00%
发文量
60
审稿时长
10 weeks
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