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Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales

International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing 210023, China
School of Geographic and Oceanographic Science, Nanjing University, Nanjing 210023, China
Numerical Terradynamic Simulation Group, the University of Montana, Missoula, MT 59812, USA
College of Forestry, Oregon State University, Corvallis, OR 97331, USA
Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
Center ďÉtude de la Forêt, Laval University, Quebec City, QC G1V 0A6, Canada
Institute for Environment and Sustainability, Joint Research Center, European Commission, 20127 Ispra, Italy
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Forest Services, Autonomous Province of Bolzano, Via Brennero 6, 39100 Bolzano, Italy
Faculty of Science and Technology, Free University of Bolzano, Piazza Università 5, 39100 Bolzano, Italy
Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695, USA
Department of Soil, Water, and Climate, University of Minnesota, St. Paul, MN 55108, USA
Department of Chemical and Biochemical Engineering, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark
Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Lenisky pr.33, Moscow 119071, Russia
Department for Innovation in Biological, Aro-food and Forest Systems, University of Tuscia, 01100 Viterbo, Italy
Department of Geography, University of Colorado, CO 80309, USA
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing 100101, China
State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, China
Jiangsu Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Author to whom correspondence should be addressed.
Academic Editors: Conghe Song, Dengsheng Lu and Prasad S. Thenkabail
Remote Sens. 2015, 7(3), 2238-2278;
Received: 20 August 2014 / Revised: 6 February 2015 / Accepted: 14 February 2015 / Published: 25 February 2015
(This article belongs to the Special Issue Carbon Cycle, Global Change, and Multi-Sensor Remote Sensing)
The reliable simulation of gross primary productivity (GPP) at various spatial and temporal scales is of significance to quantifying the net exchange of carbon between terrestrial ecosystems and the atmosphere. This study aimed to verify the ability of a nonlinear two-leaf model (TL-LUEn), a linear two-leaf model (TL-LUE), and a big-leaf light use efficiency model (MOD17) to simulate GPP at half-hourly, daily and 8-day scales using GPP derived from 58 eddy-covariance flux sites in Asia, Europe and North America as benchmarks. Model evaluation showed that the overall performance of TL-LUEn was slightly but not significantly better than TL-LUE at half-hourly and daily scale, while the overall performance of both TL-LUEn and TL-LUE were significantly better (p < 0.0001) than MOD17 at the two temporal scales. The improvement of TL-LUEn over TL-LUE was relatively small in comparison with the improvement of TL-LUE over MOD17. However, the differences between TL-LUEn and MOD17, and TL-LUE and MOD17 became less distinct at the 8-day scale. As for different vegetation types, TL-LUEn and TL-LUE performed better than MOD17 for all vegetation types except crops at the half-hourly scale. At the daily and 8-day scales, both TL-LUEn and TL-LUE outperformed MOD17 for forests. However, TL-LUEn had a mixed performance for the three non-forest types while TL-LUE outperformed MOD17 slightly for all these non-forest types at daily and 8-day scales. The better performance of TL-LUEn and TL-LUE for forests was mainly achieved by the correction of the underestimation/overestimation of GPP simulated by MOD17 under low/high solar radiation and sky clearness conditions. TL-LUEn is more applicable at individual sites at the half-hourly scale while TL-LUE could be regionally used at half-hourly, daily and 8-day scales. MOD17 is also an applicable option regionally at the 8-day scale. View Full-Text
Keywords: gross primary productivity (GPP); light use efficiency model; sunlit and shaded leaves; vegetation types; temporal scales gross primary productivity (GPP); light use efficiency model; sunlit and shaded leaves; vegetation types; temporal scales
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MDPI and ACS Style

Wu, X.; Ju, W.; Zhou, Y.; He, M.; Law, B.E.; Black, T.A.; Margolis, H.A.; Cescatti, A.; Gu, L.; Montagnani, L.; Noormets, A.; Griffis, T.J.; Pilegaard, K.; Varlagin, A.; Valentini, R.; Blanken, P.D.; Wang, S.; Wang, H.; Han, S.; Yan, J.; Li, Y.; Zhou, B.; Liu, Y. Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales. Remote Sens. 2015, 7, 2238-2278.

AMA Style

Wu X, Ju W, Zhou Y, He M, Law BE, Black TA, Margolis HA, Cescatti A, Gu L, Montagnani L, Noormets A, Griffis TJ, Pilegaard K, Varlagin A, Valentini R, Blanken PD, Wang S, Wang H, Han S, Yan J, Li Y, Zhou B, Liu Y. Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales. Remote Sensing. 2015; 7(3):2238-2278.

Chicago/Turabian Style

Wu, Xiaocui, Weimin Ju, Yanlian Zhou, Mingzhu He, Beverly E. Law, T. Andrew Black, Hank A. Margolis, Alessandro Cescatti, Lianhong Gu, Leonardo Montagnani, Asko Noormets, Timothy J. Griffis, Kim Pilegaard, Andrej Varlagin, Riccardo Valentini, Peter D. Blanken, Shaoqiang Wang, Huimin Wang, Shijie Han, Junhua Yan, Yingnian Li, Bingbing Zhou, and Yibo Liu. 2015. "Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales" Remote Sensing 7, no. 3: 2238-2278.

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