The novel method for LAI inversion using Lidar and hyperspectral data

For inversion of Leaf area index (LAI) in large scale, it is of great significance to integrate space-borne Lidar and optical remote sensing data effectively. In order to improve the estimation precision of leaf area index, an analyzing method based on Lidar and hyperspectral data was proposed. Thro...

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Veröffentlicht in:Functional Materials
Datum:2017
Hauptverfasser: Zuowei Huang, Feng Liu, Guangwei Hu
Format: Artikel
Sprache:English
Veröffentlicht: НТК «Інститут монокристалів» НАН України 2017
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Online Zugang:https://nasplib.isofts.kiev.ua/handle/123456789/136804
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Назва журналу:Digital Library of Periodicals of National Academy of Sciences of Ukraine
Zitieren:The novel method for LAI inversion using Lidar and hyperspectral data / Zuowei Huang, Feng Liu, Guangwei Hu // Functional Materials. — 2017. — Т. 24, № 3. — С. 442-450. — Бібліогр.: 23 назв. — англ.

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Digital Library of Periodicals of National Academy of Sciences of Ukraine
id nasplib_isofts_kiev_ua-123456789-136804
record_format dspace
spelling Zuowei Huang
Feng Liu
Guangwei Hu
2018-06-16T16:34:18Z
2018-06-16T16:34:18Z
2017
The novel method for LAI inversion using Lidar and hyperspectral data / Zuowei Huang, Feng Liu, Guangwei Hu // Functional Materials. — 2017. — Т. 24, № 3. — С. 442-450. — Бібліогр.: 23 назв. — англ.
1027-5495
DOI: https://doi.org/10.15407/fm24.03.442
https://nasplib.isofts.kiev.ua/handle/123456789/136804
For inversion of Leaf area index (LAI) in large scale, it is of great significance to integrate space-borne Lidar and optical remote sensing data effectively. In order to improve the estimation precision of leaf area index, an analyzing method based on Lidar and hyperspectral data was proposed. Through the processing of Lidar (Light Identification Detection and Ranging) and hyperspectral data, the LAI estimation model was established based on statistic analysis method in the study area. The results showed that the Lidar and hyperspectral data joint inversion model which considers the optical remote sensing of biophysical parameters can provide good estimates of LAI inversion, shows high accuracy (R2=0.8948, RMSE=0.2120),which reveals the great potential to enhance the accuracy of LAI estimation by using Lidar and hyperspectral data.
en
НТК «Інститут монокристалів» НАН України
Functional Materials
Modeling and simulation
The novel method for LAI inversion using Lidar and hyperspectral data
Article
published earlier
institution Digital Library of Periodicals of National Academy of Sciences of Ukraine
collection DSpace DC
title The novel method for LAI inversion using Lidar and hyperspectral data
spellingShingle The novel method for LAI inversion using Lidar and hyperspectral data
Zuowei Huang
Feng Liu
Guangwei Hu
Modeling and simulation
title_short The novel method for LAI inversion using Lidar and hyperspectral data
title_full The novel method for LAI inversion using Lidar and hyperspectral data
title_fullStr The novel method for LAI inversion using Lidar and hyperspectral data
title_full_unstemmed The novel method for LAI inversion using Lidar and hyperspectral data
title_sort novel method for lai inversion using lidar and hyperspectral data
author Zuowei Huang
Feng Liu
Guangwei Hu
author_facet Zuowei Huang
Feng Liu
Guangwei Hu
topic Modeling and simulation
topic_facet Modeling and simulation
publishDate 2017
language English
container_title Functional Materials
publisher НТК «Інститут монокристалів» НАН України
format Article
description For inversion of Leaf area index (LAI) in large scale, it is of great significance to integrate space-borne Lidar and optical remote sensing data effectively. In order to improve the estimation precision of leaf area index, an analyzing method based on Lidar and hyperspectral data was proposed. Through the processing of Lidar (Light Identification Detection and Ranging) and hyperspectral data, the LAI estimation model was established based on statistic analysis method in the study area. The results showed that the Lidar and hyperspectral data joint inversion model which considers the optical remote sensing of biophysical parameters can provide good estimates of LAI inversion, shows high accuracy (R2=0.8948, RMSE=0.2120),which reveals the great potential to enhance the accuracy of LAI estimation by using Lidar and hyperspectral data.
issn 1027-5495
url https://nasplib.isofts.kiev.ua/handle/123456789/136804
citation_txt The novel method for LAI inversion using Lidar and hyperspectral data / Zuowei Huang, Feng Liu, Guangwei Hu // Functional Materials. — 2017. — Т. 24, № 3. — С. 442-450. — Бібліогр.: 23 назв. — англ.
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first_indexed 2025-12-07T16:42:46Z
last_indexed 2025-12-07T16:42:46Z
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