Articles | Volume 13, issue 4
https://doi.org/10.5194/bg-13-961-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-13-961-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Modelling above-ground carbon dynamics using multi-temporal airborne lidar: insights from a Mediterranean woodland
W. Simonson
CORRESPONDING AUTHOR
Forest Ecology and Conservation Group, Department of Plant
Sciences, University of Cambridge, Cambridge CB2 3EA, UK
current address: United Nations Environment Programme World
Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge CB3 0DL, UK
P. Ruiz-Benito
Biological and Environmental Sciences, School of Natural Sciences,
University of Stirling, Stirling, FK9 4LA, UK
Forest Ecology and Restoration Group, Department of Life Sciences,
University of Alcalá, Science Building, Campus Universitario, 28871
Alcalá de Henares, Madrid
F. Valladares
Museo Nacional de Ciencias Naturales, CSIC, Serrano 115 dpdo, E28006
Madrid, Spain
Departamento de Ciencias, Universidad Rey Juan Carlos, Mostoles,
Madrid, Spain
D. Coomes
Forest Ecology and Conservation Group, Department of Plant
Sciences, University of Cambridge, Cambridge CB2 3EA, UK
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- Forest structure explains spatial heterogeneity of decadal carbon dynamics in a cool-temperate forest K. Takagi et al. 10.1088/1748-9326/ad774a
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- Potential of ecological modelling and smart-drainage development for mitigating adverse effects of future global change-type droughts for the Estonian forest sector J. George et al. 10.2478/fsmu-2020-0017
- Vegetation biomass estimation with remote sensing: focus on forest and other wooded land over the Mediterranean ecosystem G. Galidaki et al. 10.1080/01431161.2016.1266113
- A Growth-Model-Driven Technique for Tree Stem Diameter Estimation by Using Airborne LiDAR Data C. Paris & L. Bruzzone 10.1109/TGRS.2018.2852364
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- Fusion of NASA Airborne Snow Observatory (ASO) Lidar Time Series over Mountain Forest Landscapes A. Ferraz et al. 10.3390/rs10020164
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- A paradigm shift to CO2 sequestration to manage global warming – With the emphasis on developing countries S. Bhattacharyya et al. 10.1016/j.scitotenv.2021.148169
- Waveform LiDAR concepts and applications for potential vegetation phenology monitoring and modeling: a comprehensive review E. Salas 10.1080/10095020.2020.1761763
- Effect of Tree Phenology on LiDAR Measurement of Mediterranean Forest Structure W. Simonson et al. 10.3390/rs10050659
- Caracterización del crecimiento y producción de rodales forestales a partir de datos PNOA-LiDAR multitemporales en la provincia de Lugo L. Salgado Fernández et al. 10.31167/csecfv5i45.19907
- Assessment of changes in formations of non-forest woody vegetation in southern Denmark based on airborne LiDAR I. Angelidis et al. 10.1007/s10661-017-6119-8
- Improving Individual Tree Crown Delineation and Attributes Estimation of Tropical Forests Using Airborne LiDAR Data W. Wan Mohd Jaafar et al. 10.3390/f9120759
- Prediction of Competition Indices in a Norway Spruce and Silver Fir-Dominated Forest Using Lidar Data S. Versace et al. 10.3390/rs11232734
- Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches M. Nunes et al. 10.3390/rs9080816
- Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data D. Coomes et al. 10.1016/j.rse.2017.03.017
- Airborne lidar change detection: An overview of Earth sciences applications U. Okyay et al. 10.1016/j.earscirev.2019.102929
- Diagnosing pristine pine forest development through pansharpened-surface-reflectance Landsat image derived aboveground biomass productivity N. Doyog et al. 10.1016/j.foreco.2021.119011
- Characterizing forest carbon dynamics using multi-temporal lidar data M. Dalponte et al. 10.1016/j.rse.2019.02.018
- An IPCC-Compliant Technique for Forest Carbon Stock Assessment Using Airborne LiDAR-Derived Tree Metrics and Competition Index C. Lin et al. 10.3390/rs8060528
- High-resolution data reveal a surge of biomass loss from temperate and Atlantic pine forests, contextualizing the 2022 fire season distinctiveness in France L. Vallet et al. 10.5194/bg-20-3803-2023
- Resilience of Spanish forests to recent droughts and climate change S. Khoury & D. Coomes 10.1111/gcb.15268
- Assessing spatiotemporal variations of forest carbon density using bi-temporal discrete aerial laser scanning data in Chinese boreal forests Z. Qi et al. 10.1016/j.fecs.2023.100135
- Estimating Urban Vegetation Biomass from Sentinel-2A Image Data L. Li et al. 10.3390/f11020125
- Recovery of logged forest fragments in a human-modified tropical landscape during the 2015-16 El Niño M. Nunes et al. 10.1038/s41467-020-20811-y
- Dynamics of a human‐modified tropical peat swamp forest revealed by repeat lidar surveys B. Wedeux et al. 10.1111/gcb.15108
26 citations as recorded by crossref.
- Forest structure explains spatial heterogeneity of decadal carbon dynamics in a cool-temperate forest K. Takagi et al. 10.1088/1748-9326/ad774a
- Predicting biomass dynamics at the national extent from digital aerial photogrammetry B. Price et al. 10.1016/j.jag.2020.102116
- Potential of ecological modelling and smart-drainage development for mitigating adverse effects of future global change-type droughts for the Estonian forest sector J. George et al. 10.2478/fsmu-2020-0017
- Vegetation biomass estimation with remote sensing: focus on forest and other wooded land over the Mediterranean ecosystem G. Galidaki et al. 10.1080/01431161.2016.1266113
- A Growth-Model-Driven Technique for Tree Stem Diameter Estimation by Using Airborne LiDAR Data C. Paris & L. Bruzzone 10.1109/TGRS.2018.2852364
- Available and missing data to model impact of climate change on European forests P. Ruiz-Benito et al. 10.1016/j.ecolmodel.2019.108870
- Fusion of NASA Airborne Snow Observatory (ASO) Lidar Time Series over Mountain Forest Landscapes A. Ferraz et al. 10.3390/rs10020164
- Blind image fusion for hyperspectral imaging with the directional total variation L. Bungert et al. 10.1088/1361-6420/aaaf63
- A paradigm shift to CO2 sequestration to manage global warming – With the emphasis on developing countries S. Bhattacharyya et al. 10.1016/j.scitotenv.2021.148169
- Waveform LiDAR concepts and applications for potential vegetation phenology monitoring and modeling: a comprehensive review E. Salas 10.1080/10095020.2020.1761763
- Effect of Tree Phenology on LiDAR Measurement of Mediterranean Forest Structure W. Simonson et al. 10.3390/rs10050659
- Caracterización del crecimiento y producción de rodales forestales a partir de datos PNOA-LiDAR multitemporales en la provincia de Lugo L. Salgado Fernández et al. 10.31167/csecfv5i45.19907
- Assessment of changes in formations of non-forest woody vegetation in southern Denmark based on airborne LiDAR I. Angelidis et al. 10.1007/s10661-017-6119-8
- Improving Individual Tree Crown Delineation and Attributes Estimation of Tropical Forests Using Airborne LiDAR Data W. Wan Mohd Jaafar et al. 10.3390/f9120759
- Prediction of Competition Indices in a Norway Spruce and Silver Fir-Dominated Forest Using Lidar Data S. Versace et al. 10.3390/rs11232734
- Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches M. Nunes et al. 10.3390/rs9080816
- Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data D. Coomes et al. 10.1016/j.rse.2017.03.017
- Airborne lidar change detection: An overview of Earth sciences applications U. Okyay et al. 10.1016/j.earscirev.2019.102929
- Diagnosing pristine pine forest development through pansharpened-surface-reflectance Landsat image derived aboveground biomass productivity N. Doyog et al. 10.1016/j.foreco.2021.119011
- Characterizing forest carbon dynamics using multi-temporal lidar data M. Dalponte et al. 10.1016/j.rse.2019.02.018
- An IPCC-Compliant Technique for Forest Carbon Stock Assessment Using Airborne LiDAR-Derived Tree Metrics and Competition Index C. Lin et al. 10.3390/rs8060528
- High-resolution data reveal a surge of biomass loss from temperate and Atlantic pine forests, contextualizing the 2022 fire season distinctiveness in France L. Vallet et al. 10.5194/bg-20-3803-2023
- Resilience of Spanish forests to recent droughts and climate change S. Khoury & D. Coomes 10.1111/gcb.15268
- Assessing spatiotemporal variations of forest carbon density using bi-temporal discrete aerial laser scanning data in Chinese boreal forests Z. Qi et al. 10.1016/j.fecs.2023.100135
- Estimating Urban Vegetation Biomass from Sentinel-2A Image Data L. Li et al. 10.3390/f11020125
- Recovery of logged forest fragments in a human-modified tropical landscape during the 2015-16 El Niño M. Nunes et al. 10.1038/s41467-020-20811-y
1 citations as recorded by crossref.
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Latest update: 23 Nov 2024
Short summary
Repeat-survey airborne laser scanning is used to build a simulation model of vegetation carbon dynamics in a Spanish woodland. Analyses of National Forest Inventory and tree-ring data are used to validate the woodland growth estimates. An average carbon sequestration rate of 1.95 Mg C/ha/year over a 100-year period is predicted, but this is highly sensitive to fire frequency. The study contributes to the important need to monitor large-scale carbon dynamics in the age of climate change.
Repeat-survey airborne laser scanning is used to build a simulation model of vegetation carbon...
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