Research Papers

Calibration of a biome-biogeochemical cycles model for modeling the net primary production of teak forests through inverse modeling of remotely sensed data

[+] Author Affiliations
Chomchid Imvitthaya

RS and GIS, School of Engineering and Technology, Asian Institute of Technology, Phaholyothin Road, Klong Luang, Pathumthani, 12120 Thailand, chomchid.imvitthaya@ait.ac.th

Kiyoshi Honda

RS and GIS, School of Engineering and Technology, Asian Institute of Technology, Phaholyothin Road, Klong Luang, Pathumthani, 12120 Thailand, chomchid.imvitthaya@ait.ac.th

Surat Lertlum

RS and GIS, School of Engineering and Technology, Asian Institute of Technology, Phaholyothin Road, Klong Luang, Pathumthani, 12120 Thailand, chomchid.imvitthaya@ait.ac.th

Nipon Tangtham

Kasetsart University, Forestry Research Center, Faculty of Forestry, Ngam-Wongwan Road, Chatuchak Bangkok, 10900 Thailand

J. Appl. Remote Sens. 5(1), 053516 (March 31, 2011). doi:10.1117/1.3567194
History: Received February 12, 2010; Revised February 07, 2011; Accepted February 21, 2011; Published March 31, 2011; Online March 31, 2011
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In this paper, we present the results of a net primary production (NPP) modeling of teak (Tectona grandis Lin F.), an important species in tropical deciduous forests. The biome-biogeochemical cycles or Biome-BGC model was calibrated to estimate net NPP through the inverse modeling approach. A genetic algorithm (GA) was linked with Biome-BGC to determine the optimal ecophysiological model parameters. The Biome-BGC was calibrated by adjusting the ecophysiological model parameters to fit the simulated LAI to the satellite LAI (SPOT-Vegetation), and the best fitness confirmed the high accuracy of generated ecophysioligical parameter from GA. The modeled NPP, using optimized parameters from GA as input data, was evaluated using daily NPP derived by the MODIS satellite and the annual field data in northern Thailand. The results showed that NPP obtained using the optimized ecophysiological parameters were more accurate than those obtained using default literature parameterization. This improvement occurred mainly because the model's optimized parameters reduced the bias by reducing systematic underestimation in the model. These Biome-BGC results can be effectively applied in teak forests in tropical areas. The study proposes a more effective method of using GA to determine ecophysiological parameters at the site level and represents a first step toward the analysis of the carbon budget of teak plantations at the regional scale.

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© 2011 Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation

Chomchid Imvitthaya ; Kiyoshi Honda ; Surat Lertlum and Nipon Tangtham
"Calibration of a biome-biogeochemical cycles model for modeling the net primary production of teak forests through inverse modeling of remotely sensed data", J. Appl. Remote Sens. 5(1), 053516 (March 31, 2011). ; http://dx.doi.org/10.1117/1.3567194


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