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International Journal of Remote Sensing Volume 29, 2008 - Issue 8
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Remote Sensing Letters

Integration of remote sensing and ecosystem modelling techniques to estimate forest net carbon uptake

F. Maselli Institute of Biometeorology (IBIMET), National Research Council of Italy (CNR), Via Madonna del Piano 10, 50019 Sesto Fiorentino, Firenze, ItalyCorrespondence[email protected]
,
M. Chiesi Institute of Biometeorology (IBIMET), National Research Council of Italy (CNR), Via Madonna del Piano 10, 50019 Sesto Fiorentino, Firenze, Italy
,
L. Fibbi Institute of Biometeorology (IBIMET), National Research Council of Italy (CNR), Via Madonna del Piano 10, 50019 Sesto Fiorentino, Firenze, Italy
&
M. Moriondo Department of Agronomy and Land Management (DISAT), University of Florence, P. le delle Cascine 18, 50144 Firenze, Italy
Pages 2437-2443 | Received 29 May 2007, Accepted 02 Jan 2008, Published online: 25 Mar 2008

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Read on this site (2)

Fabio Maselli, Marta Chiesi, Luca Fibbi & Marco Moriondo. (2011) Use of ground and LiDAR data to model the NPP of a Mediterranean pine forest. Remote Sensing Letters 2:4, pages 309-316.
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Shoji Hashimoto, Martin Wattenbach & Pete Smith. (2011) Litter carbon inputs to the mineral soil of Japanese Brown forest soils: comparing estimates from the RothC model with estimates from MODIS. Journal of Forest Research 16:1, pages 16-25.
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Articles from other publishers (19)

Yajie Zheng, Zhiqiang Xiao, Juan Li, Hua Yang & Jinling Song. (2022) Evaluation of Global Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) Products at 500 m Spatial Resolution. Remote Sensing 14:14, pages 3304.
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Sungsik Cho, Minseok Kang, Kazuhito Ichii, Joon Kim, Jong-Hwan Lim, Jung-Hwa Chun, Chan-Woo Park, Hyun Seok Kim, Sung-Won Choi, Seung-Hoon Lee, Yohana Maria Indrawati & Jongho Kim. (2021) Evaluation of forest carbon uptake in South Korea using the national flux tower network, remote sensing, and data-driven technology. Agricultural and Forest Meteorology 311, pages 108653.
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Siyuan Chen, Liangyun Liu, Xue He, Zhigang Liu & Dailiang Peng. (2020) Upscaling from Instantaneous to Daily Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) for Satellite Products. Remote Sensing 12:13, pages 2083.
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. 2020. Advanced Remote Sensing. Advanced Remote Sensing 447 476 .
Xin Tao, Shunlin Liang, Dongdong Wang, Tao He & Chengquan Huang. (2018) Improving Satellite Estimates of the Fraction of Absorbed Photosynthetically Active Radiation Through Data Integration: Methodology and Validation. IEEE Transactions on Geoscience and Remote Sensing 56:4, pages 2107-2118.
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Rahul Raj, Christiaan van der Tol, Nicholas Alexander Samuel Hamm & Alfred Stein. (2018) Bayesian integration of flux tower data into a process-based simulator for quantifying uncertainty in simulated output. Geoscientific Model Development 11:1, pages 83-101.
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Xin Tian, Min Yan, Christiaan van der Tol, Zengyuan Li, Zhongbo Su, Erxue Chen, Xin Li, Longhui Li, Xufeng Wang, Xiaoduo Pan, Lushuang Gao & Zongtao Han. (2017) Modeling forest above-ground biomass dynamics using multi-source data and incorporated models: A case study over the qilian mountains. Agricultural and Forest Meteorology 246, pages 1-14.
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Xin Tao, Shunlin Liang, Tao He & Huiran Jin. (2016) Estimation of fraction of absorbed photosynthetically active radiation from multiple satellite data: Model development and validation. Remote Sensing of Environment 184, pages 539-557.
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Min Yan, Xin Tian, Zengyuan Li, Erxue Chen, Chunmei Li & Wenwu Fan. (2016) A long-term simulation of forest carbon fluxes over the Qilian Mountains. International Journal of Applied Earth Observation and Geoinformation 52, pages 515-526.
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L. Brilli, B. Gioli, P. Toscano, M. Moriondo, A. Zaldei, C. Cantini, R. Ferrise & M. Bindi. (2016) Rainfall regimes control C-exchange of Mediterranean olive orchard. Agriculture, Ecosystems & Environment 233, pages 147-157.
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Xin Tao, Shunlin Liang & Dongdong Wang. (2015) Assessment of five global satellite products of fraction of absorbed photosynthetically active radiation: Intercomparison and direct validation against ground-based data. Remote Sensing of Environment 163, pages 270-285.
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Gherardo Chirici, Marta Chiesi, Piermaria Corona, Nicola Puletti, Matteo Mura & Fabio Maselli. (2015) Prediction of forest NPP in Italy by the combination of ground and remote sensing data. European Journal of Forest Research 134:3, pages 453-467.
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Dongjie Fu, Baozhang Chen, Huifang Zhang, Juan Wang, T. Andy Black, Brian D. Amiro, Gil Bohrer, Paul Bolstad, Richard Coulter, Abdullah F. Rahman, Allison Dunn, J. Harry McCaughey, Tilden Meyers & Shashi Verma. (2014) Estimating landscape net ecosystem exchange at high spatial–temporal resolution based on Landsat data, an improved upscaling model framework, and eddy covariance flux measurements. Remote Sensing of Environment 141, pages 90-104.
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Jordan Golinkoff & Steven Running. 2013. Land Use and the Carbon Cycle. Land Use and the Carbon Cycle 259 286 .
Marta Chiesi, Paolo Cherubini & Fabio Maselli. (2011) Adaptation of a modelling strategy to predict the NPP of even-aged forest stands. European Journal of Forest Research 131:4, pages 1175-1184.
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M. Chiesi, L. Fibbi, L. Genesio, B. Gioli, R. Magno, F. Maselli, M. Moriondo & F.P. Vaccari. (2011) Integration of ground and satellite data to model Mediterranean forest processes. International Journal of Applied Earth Observation and Geoinformation 13:3, pages 504-515.
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M. ChiesiM. MoriondoF. MaselliL. GardinL. FibbiM. BindiS. W. Running. (2010) Simulation of Mediterranean forest carbon pools under expected environmental scenarios. Canadian Journal of Forest Research 40:5, pages 850-860.
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Fabio Maselli, Beniamino Gioli, Marta Chiesi, Francesco Vaccari, Alessandro Zaldei, Luca Fibbi, Marco Bindi & Franco Miglietta. (2010) Validating an integrated strategy to model net land carbon exchange against aircraft flux measurements. Remote Sensing of Environment 114:5, pages 1108-1116.
Crossref
F. Maselli, M. Chiesi, M. Moriondo, L. Fibbi, M. Bindi & S.W. Running. (2009) Modelling the forest carbon budget of a Mediterranean region through the integration of ground and satellite data. Ecological Modelling 220:3, pages 330-342.
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