Imaging spectroscopy- and lidar- derived estimates of canopy composition and structure to improve predictions of forest carbon fluxes and ecosystem dynamics

Antonarakis, A S, Munger, J W and Moorcroft, P R (2014) Imaging spectroscopy- and lidar- derived estimates of canopy composition and structure to improve predictions of forest carbon fluxes and ecosystem dynamics. Geophysical Research Letters, 41 (7). pp. 2535-2542. ISSN 0094-8276

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Abstract

The composition and structure of vegetation are key attributes of ecosystems, affecting their current and future carbon, water, and energy fluxes. Information on these attributes has traditionally come from ground-based inventories of the plant canopy within small sample plots. Here we show how imaging spectrometry and waveform lidar can be used to provide spatially-comprehensive estimates of forest canopy composition and structure that can improve the accuracy of the carbon flux predictions of a size-structured terrestrial biosphere model, reducing its RMSEs from 85%-104% to 37%-57%. The improvements are qualitatively and quantitatively similar to those obtained from simulations initialized with ground measurements, and approximately doubles the estimated rate of ecosystem carbon uptake as compared to a potential vegetation simulation. These results suggest that terrestrial biosphere model simulations can utilize modern-remote sensing data on vegetation composition and structure to improve their predictions of the current and near-term future functioning of the terrestrial biosphere.

Item Type: Article
Schools and Departments: School of Global Studies > Geography
Subjects: G Geography. Anthropology. Recreation > G Geography (General) > G0001 Geography (General) > G0142 Aerial geography
G Geography. Anthropology. Recreation > GB Physical geography
H Social Sciences > HD Industries. Land use. Labour > HD0101 Land use
Q Science > QH Natural history > QH0301 Biology > QH0540 Ecology
Q Science > QK Botany > QK0900 Plant ecology
Depositing User: Alexander Antonarakis
Date Deposited: 06 Jun 2014 11:50
Last Modified: 08 Mar 2017 08:45
URI: http://sro.sussex.ac.uk/id/eprint/48347

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