Use of lidar data to simulate forest net primary production

Maselli, Fabio; Mari, Riccardo; Chiesi, Marta

doi:10.1080/01431161.2012.745019

Cited by 6 publications

(12 citation statements)

References 29 publications

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“…For relatively small areas an alternative could be provided by tree height estimates obtained from LiDAR data, which can be used as a proxy of tree age (Maselli et al 2013), though old small individuals and, vice-versa, trees with huge biomass accumulated in few decades, can be found in forest ecosystems (Marziliano et al 2012). Finally, as regards the last step, its application on regional to national scales is virtually unfeasible, since the dendrochronological measurements needed to characterize specific site history can be obtained only for small areas.…”

Section: Discussionmentioning

confidence: 99%

Assessing most relevant factors to simulate current annual increments of beech forests in Italy

Chiesi¹,

Maselli²,

Chirici³

et al. 2014

iForest

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Section: Discussionmentioning

confidence: 99%

Assessing most relevant factors to simulate current annual increments of beech forests in Italy

Chiesi¹,

Maselli²,

Chirici³

et al. 2014

iForest

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“…The actual status of the two stands was instead accounted for by modifying the model combination strategy on the basis of the previously exposed considerations. The scalars describing vegetation status required by equation 3 (FC and NV) were derived from the analysis of the LiDAR dataset of 2015 using the allometric relationships described in [21]. These scalars were kept constant during the simulation period for the mature umbrella pine stand, where great green and woody biomass variations are not expected in a relatively short time period.…”

Section: Data Processingmentioning

confidence: 99%

Use of Remote Sensing and Biogeochemical Modelling to Simulate the Impact of Climatic and Anthropogenic Factors on Forest Carbon Fluxes

Chiesi,

Fibbi,

Vanucci

et al. 2024

Preprint

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The current communication presents the application of a consolidated model combination strategy to analyze the medium-term carbon fluxes in two Mediterranean pine wood ecosystems. The modelling strategy is based on the use of a NDVI-driven parametric model, Modified C-Fix, and of a bio-geochemical model, BIOME-BGC, the outputs of which are combined taking into account the actual development phase of each ecosystem. The two pine ecosystems examined correspond to an old-growth forest and to a secondary succession after clearcuts, which differently respond to the same climatic condition during a ten-year period (2013-2022). Increasing dryness, in fact, exerts a fundamental role in controlling the gross primary and net ecosystem production of the mature stand, while the effect of forest regeneration is prevalent for the uprising of the same variables in the other stand. In particular, the simulated net carbon exchange fluctuates around 200 g C m-2 year-1 in the first stand and rises to over 600 g C m-2 year-1 in the second stand; correspondingly, the accumulation of new biomass is nearly undetectable in the former case while becomes notable in the latter. The study therefore supports the potential of the applied strategy for predicting the forest carbon balances consequent on diversified natural and human-induced factors.

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“…These data were then averaged on a stand basis basis (NDVI 1 and NDVI 2), linearly interpolated to a daily time step and combined with the weather data to drive Modified C-Fix (Equation ( 1)). A BIOME-BGC version parameterized for Mediterranean pines was then applied using the same meteorological dataset and ancillary information [20]. Three series of GPP estimates were thus obtained, the first from BIOME-BGC, referred to both stands (GPP BIOME), and the others from C-Fix driven by the NDVI series of the two stands (i.e., GPP C-Fix 1 for umbrella pine and GPP C-Fix 2 for maritime pine).…”

Section: Data Processingmentioning

confidence: 99%

“…The actual status of the two stands was instead accounted for by modifying the model combination strategy on the basis of the previously exposed considerations. The scalars describing vegetation status required by Equation (3) (FC and NV) were derived from the analysis of the LiDAR dataset taken in 2015 using the allometric relationships described in [20]. These scalars were kept constant during the simulation period for the mature umbrella pine stand, where great green and woody biomass variations are not expected over a relatively short time period.…”

Section: Data Processingmentioning

confidence: 99%

“…On the contrary, for the regrowing maritime pine stand, the two scalars were initialized using the LiDAR data and updated annually through the consideration of net primary production (NPP) estimates. As described in [20], the annual updating was performed by converting the respective NPP estimate into FC and NV increments. For both stands, the scalar which regulates soil heterotrophic respiration (NS) was assumed to remain constant and was obtained from the SOC map of Tuscany corrected for the soil depth considered by BIOME-BGC [12].…”

Section: Data Processingmentioning

confidence: 99%

See 1 more Smart Citation

Use of Remote Sensing and Biogeochemical Modeling to Simulate the Impact of Climatic and Anthropogenic Factors on Forest Carbon Fluxes

Chiesi,

Fibbi,

Vanucci

et al. 2024

Remote Sensing

Self Cite

View full text Add to dashboard Cite

The current communication presents the application of a consolidated model combination strategy to analyze the medium-term carbon fluxes in two Mediterranean pine wood ecosystems. This strategy is based on the use of a NDVI-driven parametric model, Modified C-Fix, and of a biogeochemical model, BIOME-BGC, the outputs of which are combined taking into account the actual development phase of each ecosystem. The two pine ecosystems examined correspond to an old-growth forest and to a secondary succession after clearcuts, which differently respond to the same climatic condition during a ten-year period (2013–2022). Increasing dryness, in fact, exerts a fundamental role in controlling the gross primary and net ecosystem production of the mature stand, while the effect of forest regeneration is prevalent for the uprising of the same variables in the other stand. In particular, the simulated net carbon exchange fluctuates around 200 g C m−2 year−1 in the first stand and rises to over 600 g C m−2 year−1 in the second stand; correspondingly, the accumulation of new biomass is nearly undetectable in the former case while becomes notable in the latter. The study, therefore, supports the potential of the applied strategy for predicting the forest carbon balances consequent on diversified natural and human-induced factors.

show abstract

Use of lidar data to simulate forest net primary production

Cited by 6 publications

References 29 publications

Assessing most relevant factors to simulate current annual increments of beech forests in Italy

Assessing most relevant factors to simulate current annual increments of beech forests in Italy

Use of Remote Sensing and Biogeochemical Modelling to Simulate the Impact of Climatic and Anthropogenic Factors on Forest Carbon Fluxes

Use of Remote Sensing and Biogeochemical Modeling to Simulate the Impact of Climatic and Anthropogenic Factors on Forest Carbon Fluxes

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