Field scale wheat LAI retrieval from multispectral Sentinel 2A-MSI and LandSat 8-OLI imagery: effect of atmospheric correction, image resolutions and inversion techniques

被引：21

作者：

Dhakar, Rajkumar ^{[1
]}

Sehgal, Vinay Kumar ^{[1
]}

Chakraborty, Debasish ^{[1
]}

Sahoo, Rabi Narayan ^{[1
]}

Mukherjee, Joydeep ^{[1
]}

机构：

[1] ICAR Indian Agr Res Inst, Div Agr Phys, New Delhi, India

来源：

GEOCARTO INTERNATIONAL | 2021年 / 36卷 / 18期

关键词：

Crop; PROSAIL; inversion; spatial resolution; spectral resolution; LEAF-AREA INDEX; RADIATIVE-TRANSFER MODEL; VEGETATION INDEXES; DATA ASSIMILATION; CANOPY VARIABLES; REFLECTANCE DATA; CHLOROPHYLL; FAPAR; SPECTROSCOPY; VALIDATION;

D O I：

10.1080/10106049.2019.1687591

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

This study assessed the effect of atmospheric correction algorithms, inversion techniques and image spatial and spectral resolution on wheat crop LAI retrieval using Sentinel-2 MSI and Landsat-8 OLI imagery. The LAI retrievals were validated with in-situ measurements collected in farmers' fields. The MSI-based LAI retrievals improved significantly when images were atmospherically corrected using MODTRAN than using the libRadtran code. Among the two PROSAIL inversion approaches, look-up table outperforms artificial neural network for LAI retrievals. Using the best strategy of atmospheric correction and inversion, the effect of spatial resolution from 20 m (MSI) to 30 m (OLI) while using common six bands, showed non-significant improvement in LAI retrievals. The inclusion of additional two red-edge bands as available in MSI significantly reduced the uncertainly in LAI retrievals over that obtained by using six bands, while inclusion of only additional VNIR band did not show any significant effect on LAI retrievals.

引用

页码：2044 / 2064

页数：21

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