Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing

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Standard

Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing. / Tagesson, Håkan Torbern; Smith, Benjamin; Løfgren, Anders; Rammig, Anja; Eklundh, Lars; Lindroth, Anders.

I: Ambio, Bind 6, 2009, s. 316-324.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Tagesson, HT, Smith, B, Løfgren, A, Rammig, A, Eklundh, L & Lindroth, A 2009, 'Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing', Ambio, bind 6, s. 316-324.

APA

Tagesson, H. T., Smith, B., Løfgren, A., Rammig, A., Eklundh, L., & Lindroth, A. (2009). Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing. Ambio, 6, 316-324.

Vancouver

Tagesson HT, Smith B, Løfgren A, Rammig A, Eklundh L, Lindroth A. Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing. Ambio. 2009;6:316-324.

Author

Tagesson, Håkan Torbern ; Smith, Benjamin ; Løfgren, Anders ; Rammig, Anja ; Eklundh, Lars ; Lindroth, Anders. / Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing. I: Ambio. 2009 ; Bind 6. s. 316-324.

Bibtex

@article{46183044336d4e44a94558dd79cffbaa,
title = "Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing",
abstract = "The aim of this study was to investigate a combination of satellite images of leaf area index (LAI) with processbased vegetation modeling for the accurate assessment of the carbon balances of Swedish forest ecosystems at the scale of a landscape. Monthly climatologic data were used as inputs in a dynamic vegetation model, the Lund Potsdam Jena-General Ecosystem Simulator. Model estimates of net primary production (NPP) and the fraction of absorbed photosynthetic active radiation were constrained by combining them with satellite-based LAI images using a general light use efficiency (LUE) model and the Beer-Lambert law. LAI estimates were compared with satellite-extrapolated field estimates of LAI, and the results were generally acceptable. NPP estimates directly from the dynamic vegetation model and estimates obtained by combining the model estimates with remote sensing information were, on average, well simulated but too homogeneous among vegetation types when compared with field estimates using forest inventory data.",
author = "Tagesson, {H{\aa}kan Torbern} and Benjamin Smith and Anders L{\o}fgren and Anja Rammig and Lars Eklundh and Anders Lindroth",
year = "2009",
language = "English",
volume = "6",
pages = "316--324",
journal = "Ambio",
issn = "0044-7447",
publisher = "Springer",

}

RIS

TY - JOUR

T1 - Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing

AU - Tagesson, Håkan Torbern

AU - Smith, Benjamin

AU - Løfgren, Anders

AU - Rammig, Anja

AU - Eklundh, Lars

AU - Lindroth, Anders

PY - 2009

Y1 - 2009

N2 - The aim of this study was to investigate a combination of satellite images of leaf area index (LAI) with processbased vegetation modeling for the accurate assessment of the carbon balances of Swedish forest ecosystems at the scale of a landscape. Monthly climatologic data were used as inputs in a dynamic vegetation model, the Lund Potsdam Jena-General Ecosystem Simulator. Model estimates of net primary production (NPP) and the fraction of absorbed photosynthetic active radiation were constrained by combining them with satellite-based LAI images using a general light use efficiency (LUE) model and the Beer-Lambert law. LAI estimates were compared with satellite-extrapolated field estimates of LAI, and the results were generally acceptable. NPP estimates directly from the dynamic vegetation model and estimates obtained by combining the model estimates with remote sensing information were, on average, well simulated but too homogeneous among vegetation types when compared with field estimates using forest inventory data.

AB - The aim of this study was to investigate a combination of satellite images of leaf area index (LAI) with processbased vegetation modeling for the accurate assessment of the carbon balances of Swedish forest ecosystems at the scale of a landscape. Monthly climatologic data were used as inputs in a dynamic vegetation model, the Lund Potsdam Jena-General Ecosystem Simulator. Model estimates of net primary production (NPP) and the fraction of absorbed photosynthetic active radiation were constrained by combining them with satellite-based LAI images using a general light use efficiency (LUE) model and the Beer-Lambert law. LAI estimates were compared with satellite-extrapolated field estimates of LAI, and the results were generally acceptable. NPP estimates directly from the dynamic vegetation model and estimates obtained by combining the model estimates with remote sensing information were, on average, well simulated but too homogeneous among vegetation types when compared with field estimates using forest inventory data.

M3 - Journal article

VL - 6

SP - 316

EP - 324

JO - Ambio

JF - Ambio

SN - 0044-7447

ER -

ID: 44268663