Estimating leaf area index in coniferous and deciduous forests in Sweden using landsat optical sensor data
Eklundh, Lars LU
(2003)
Remote Sensing for Agriculture Ecosystems, and Hydrology IV
4879.
p.379-390
- Abstract
- This paper reports on research to estimate leaf area index (LAI) in Swedish forests with satellite sensor data. The study is part of a research programme that aims at generating input data for process-oriented forest carbon models. Field-work was carried out in two areas in Sweden about 530 km apart, in the nemoral and boreo-nemoral forest regions. Various ways of estimating LAI in the field were tested, including litter-traps, allometric equations, and light transmission measurements. The capability of Landsat TM and ETM+ for LAI-mapping was investigated with the Nilson and Kuusk forest reflectance model. Results point to channel 3 and the mid-IR channels as particularly important for LAI estimation in coniferous stands, however, modelled... (More)
- This paper reports on research to estimate leaf area index (LAI) in Swedish forests with satellite sensor data. The study is part of a research programme that aims at generating input data for process-oriented forest carbon models. Field-work was carried out in two areas in Sweden about 530 km apart, in the nemoral and boreo-nemoral forest regions. Various ways of estimating LAI in the field were tested, including litter-traps, allometric equations, and light transmission measurements. The capability of Landsat TM and ETM+ for LAI-mapping was investigated with the Nilson and Kuusk forest reflectance model. Results point to channel 3 and the mid-IR channels as particularly important for LAI estimation in coniferous stands, however, modelled reflectances were strongly influenced by background reflectances (particularly at low densities) and leaf optical properties. Top-of-canopy reflectances were derived from Landsat TM and ETM+, and their relationships with field-estimated LAI analysed. Among several vegetation indices .tested, the Moisture Stress Index (TM5 / TM4) was one of the best indices for LAI in coniferous stands. In deciduous stands relationships based on the Simple Ratio were superior, however, the explanatory power in deciduous stands was lower than in coniferous stands. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/611303
- author
- Eklundh, Lars
LU
- organization
- publishing date
- 2003
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Canopy reflectance modelling, Thematic mapper, Light transmission measurement, Leaf area index, Landsat optical sensor
- host publication
- Proceedings of SPIE - The International Society for Optical Engineering
- volume
- 4879
- pages
- 379 - 390
- publisher
- SPIE
- conference name
- Remote Sensing for Agriculture Ecosystems, and Hydrology IV
- conference location
- Agia Pelagia, Greece
- conference dates
- 2002-09-22 - 2002-09-25
- external identifiers
-
- wos:000182227200040
- other:CODEN: PSISDG
- scopus:0038193863
- ISSN
- 0277-786X
- 1996-756X
- DOI
- 10.1117/12.462467
- language
- English
- LU publication?
- yes
- id
- e542f0bf-e884-4af2-afe1-5afee7c168b1 (old id 611303)
- date added to LUP
- 2016-04-01 12:12:12
- date last changed
- 2024-04-23 07:33:51
@inproceedings{e542f0bf-e884-4af2-afe1-5afee7c168b1,
abstract = {{This paper reports on research to estimate leaf area index (LAI) in Swedish forests with satellite sensor data. The study is part of a research programme that aims at generating input data for process-oriented forest carbon models. Field-work was carried out in two areas in Sweden about 530 km apart, in the nemoral and boreo-nemoral forest regions. Various ways of estimating LAI in the field were tested, including litter-traps, allometric equations, and light transmission measurements. The capability of Landsat TM and ETM+ for LAI-mapping was investigated with the Nilson and Kuusk forest reflectance model. Results point to channel 3 and the mid-IR channels as particularly important for LAI estimation in coniferous stands, however, modelled reflectances were strongly influenced by background reflectances (particularly at low densities) and leaf optical properties. Top-of-canopy reflectances were derived from Landsat TM and ETM+, and their relationships with field-estimated LAI analysed. Among several vegetation indices .tested, the Moisture Stress Index (TM5 / TM4) was one of the best indices for LAI in coniferous stands. In deciduous stands relationships based on the Simple Ratio were superior, however, the explanatory power in deciduous stands was lower than in coniferous stands.}},
author = {{Eklundh, Lars}},
booktitle = {{Proceedings of SPIE - The International Society for Optical Engineering}},
issn = {{0277-786X}},
keywords = {{Canopy reflectance modelling; Thematic mapper; Light transmission measurement; Leaf area index; Landsat optical sensor}},
language = {{eng}},
pages = {{379--390}},
publisher = {{SPIE}},
title = {{Estimating leaf area index in coniferous and deciduous forests in Sweden using landsat optical sensor data}},
url = {{http://dx.doi.org/10.1117/12.462467}},
doi = {{10.1117/12.462467}},
volume = {{4879}},
year = {{2003}},
}