Paper
9 October 2007 Integration of ground and satellite data to simulate forest carbon budget on regional scale
Fabio Maselli, Marta Chiesi, Marco Moriondo, Luca Fibbi, Marco Bindi, Steven W. Running
Author Affiliations +
Abstract
Simulating the main terms of forest carbon budget (GPP, NPP, NEE) is important for both scientific and practical reasons. This operation was performed for a region of Central Italy (Tuscany) by the integrated processing of ground and satellite data. Several data layers (meteorology, forest type, volume, etc.) were first collected in order to characterize the eco-climatic and forest features of the region. FAPAR estimates with 1 km resolution were obtained by processing VGT NDVI data. Relying on these data sets, monthly estimates of forest GPP were produced by means of a simplified, NDVIbased parametric model, C-Fix. These GPP estimates were used to calibrate a well known bio-geochemical model, BIOME-BGC, in order to find its best configurations for simulating all main functions (photosynthesis, respirations, allocations, etc.) of the most widespread Tuscany forest types. The calibrated versions of BIOME-BGC were then applied to produce respiration estimates for all regional forest surfaces during the study period. The obtained GPP and respiration estimates, which were referred to equilibrium conditions, were converted into the values of actual forests by applying a simplified approach which relies on the ratio of actual over potential tree volume as an indicator of forest distance from climax. The C-Fix photosynthesis estimates of actual forests were finally integrated with relevant BIOMEBGC simulated respirations in order to assess net forest carbon fluxes.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fabio Maselli, Marta Chiesi, Marco Moriondo, Luca Fibbi, Marco Bindi, and Steven W. Running "Integration of ground and satellite data to simulate forest carbon budget on regional scale", Proc. SPIE 6742, Remote Sensing for Agriculture, Ecosystems, and Hydrology IX, 674203 (9 October 2007); https://doi.org/10.1117/12.737907
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Cited by 2 scholarly publications.
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KEYWORDS
Ecosystems

Calibration

Biological research

Data modeling

Carbon

Photosynthesis

Atmospheric modeling

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