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Application of the metabolic scaling theory and water–energy balance equation to model large‐scale patterns of maximum forest canopy height
Authors:Sungho Choi  Christopher P. Kempes  Taejin Park  Sangram Ganguly  Weile Wang  Liang Xu  Saikat Basu  Jennifer L. Dungan  Marc Simard  Sassan S. Saatchi  Shilong Piao  Xiliang Ni  Yuli Shi  Chunxiang Cao  Ramakrishna R. Nemani  Yuri Knyazikhin  Ranga B. Myneni
Affiliation:1. Department of Earth and Environment, Boston University, Boston, MA, USA;2. Control and Dynamical Systems, California Institute of Technology, Pasadena, CA 3. 91125, USA/The Santa Fe Institute, Santa Fe, NM, USA;4. Bay Area Environmental Research Institute (BAERI) and NASA Ames Research Center, Moffett Field, CA, USA;5. Division of Science and Environmental Policy, California State University Monterey Bay, Seaside, CA 93955/ Biospheric Science Branch, NASA Ames Research Center, Moffett Field, CA, USA;6. Institute of the Environment and Sustainability, University of California, Los Angeles, CA, USA;7. Department of Computer Science, Louisiana State University, Baton Rouge, LA, USA;8. Earth Science Division, NASA Ames Research Center, Moffett Field, CA, USA;9. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA;10. College of Urban and Environmental Sciences and Sino‐French Institute for Earth System Science, Peking University, Beijing, China;11. State Key Laboratory of Remote Sensing Sciences, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China;12. School of Remote Sensing, Nanjing University of Information Science and Technology, Nanjing, China;13. NASA Advanced Supercomputing Division, NASA Ames Research Center, Moffett Field, CA, USA
Abstract:
Keywords:Carbon monitoring  disturbance history  geospatial predictors  large‐scale modelling  maximum forest height  mechanistic understanding  metabolic scaling theory  prognostic applications  water–  energy balance
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