基于LISS-III的三角洲植被叶面积指数估算与反验证

Q3 Agricultural and Biological Sciences
A. Santra, S. S. Mitra, Suman Sinha
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引用次数: 1

摘要

叶面积指数(LAI)是一个无量纲的生物物理变量,是表征冠层结构的重要因子之一。它估计每单位地面面积的树叶面积,并有助于间接评估生态系统中的生物量和能量平衡。遥感技术建立了植被在红、近红外波段的反射率特征与LAI之间的强相关性。目前已有大量影像衍生植被指数成功应用于LAI估算。本文将印度西孟加拉邦Sagar岛三角洲生态系统野外采集的LAI与IRS-LISS-III数据反演的3个土壤调整植被指数(SAVI、MSAVI和OSAVI)建立相关性。利用OSAVI估算全岛LAI, OSAVI结果最好(R2= 0.92)。采用高档验证方法,对LISS-III衍生LAI图像进行粗分辨率MODIS LAI (MOD 15A3)产品反验证。在应用的六个最佳拟合模型中,逻辑回归显示两个产品之间有很强的正对应关系(R2 = 0.71)。还评估了模型的不确定性,并确定了可能的原因。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation and counter- validation of LISS-III derived leaf area index in Deltaic vegetation
Leaf area index (LAI), a dimensionless biophysical variable is considered as one of the most important factors in characterizing canopy structure. It estimates the amount of foliage area per unit of ground area and helps indirectly to assess biomass and energy balance in an ecosystem. Remote sensing techniques established a strong correlation between the vegetation reflectance characteristics in red and near infra-red bands and LAI. Good number of image derived vegetation indices has been applied so far to estimate LAI successfully. In this paper correlation is established between field-collected LAI and three soil adjusted vegetation indices, i.e., SAVI, MSAVI and OSAVI derived from IRS-LISS-III data in deltaic ecosystem in Sagar Island of West Bengal, India. LAI was estimated from OSAVI for the whole island as OSAVI yielded best result (R2= 0.92). Coarse resolution MODIS LAI (MOD 15A3) product was counter-validated with respect to the LISS-III derived LAI image following the upscale validation approach. Out of the six best-fit models applied, the logistic regression showed strong positive correspondence between the two products (R2 = 0.71). Uncertainty of the model was also assessed and probable reasons were identified.
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来源期刊
caspian journal of environmental sciences
caspian journal of environmental sciences Environmental Science-Environmental Science (all)
CiteScore
2.30
自引率
0.00%
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审稿时长
5 weeks
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