Literature DB >> 21491677

Assessment of forest net primary production through the elaboration of multisource ground and remote sensing data.

Fabio Maselli1, Marta Chiesi, Anna Barbati, Piermaria Corona.   

Abstract

This paper builds on previous work by our research group which demonstrated the applicability of a parametric model, Modified C-Fix, for the monitoring of Mediterranean forests. Specifically, the model is capable of combining ground and remote sensing data to estimate forest gross primary production (GPP) on various spatial and temporal scales. Modified C-Fix is currently applied to all Italian forest areas using a previously produced data set of meteorological data and NDVI imagery descriptive of a ten-year period (1999-2008). The obtained GPP estimates are further elaborated to derive forest net primary production (NPP) averages for 20 Italian Regions. Such estimates, converted into current annual increment of standing volume (CAI) through the use of specific coefficients, are compared to the data of a recent national forest inventory (INFC). The results obtained indicate that the modelling approach tends to overestimate the ground CAI values for all forest types. The correction of a drawback in the current model implementation leads to reduce this overestimation to about 9% of the INFC increments. The possible origins of this overestimation are investigated by examining the results of previous studies and of older forest inventories. The implications of using different NPP estimation methods are finally discussed in view of assessing the forest carbon budget on a national basis.

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Year:  2010        PMID: 21491677     DOI: 10.1039/b924629k

Source DB:  PubMed          Journal:  J Environ Monit        ISSN: 1464-0325


  2 in total

1.  Temporal variations of NDVI and correlations between NDVI and hydro-climatological variables at Lake Baiyangdian, China.

Authors:  Fei Wang; Xuan Wang; Ying Zhao; Zhifeng Yang
Journal:  Int J Biometeorol       Date:  2013-10-31       Impact factor: 3.787

2.  Assessment of global carbon dioxide concentration using MODIS and GOSAT data.

Authors:  Meng Guo; Xiufeng Wang; Jing Li; Kunpeng Yi; Guosheng Zhong; Hiroshi Tani
Journal:  Sensors (Basel)       Date:  2012-11-26       Impact factor: 3.576

  2 in total

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