Retrieval of remotely sensed LAI using Landsat ETM+ data and ground measurements of solar radiation and vegetation structure: Implication of leaf inclination angle |
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| Institution: | 2. Research Area of Ecology and Biodiversity, School for Biological Sciences, The University of Hong Kong, Hong Kong, China;3. Centre for Tropical Environmental and Sustainability Science, College of Science and Engineering, James Cook University, Cairns, Queensland 4878, Australia;4. Department of Biodiversity, Bioscience Institute, São Paulo State University UNESP, Rio Claro, São Paulo, Brazil;5. Department of Environmental and Climate Sciences, Brookhaven National Laboratory, NY11973, USA;6. Instituto Tecnológico Vale, Belém, Pará, Brazil;7. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA;8. College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China;9. International Research Center of Big Data for Sustainable Development Goals, Beijing, China;10. Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai, China;11. Department of Geography, The University of Hong Kong, Hong Kong, China;12. Institute for Climate and Carbon Neutrality, The University of Hong Kong, Hong Kong, China;13. Institute of Data Science and Department of Mathematics, The University of Hong Kong, Hong Kong, China;14. National Institute for Amazon Research (INPA), Manaus, Brazil;15. School of Life Sciences, University of Technology Sydney, Sydney, NSW 2007, Australia;1. CREA – Research Centre for Forestry and Wood, Arezzo, Italy;2. CREA – Research Centre for Agriculture and Environment, Rome, Italy;3. CREA – Research Centre for Forestry and Wood, Rome, Italy |
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| Abstract: | A time series of leaf area index (LAI) of a managed birch forest in Germany (near Dresden) has been developed based on 16-day normalized difference vegetation index (NDVI) data from the Landsat ETM+ sensor at 30 m resolution. The Landsat ETM+ LAI was retrieved using a modified physical radiative transfer (RTM) model which establishes a relationship between LAI, fractional vegetation cover (fC), and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation. In situ measurements of photosynthetically active radiation (PAR) and vegetation structure parameters using hemispherical photography (HSP) served for calibration of model parameters, while data from litter collection at the study site provided the ground-based estimates of LAI for validation of modelling results. Influence of view-illumination conditions on optical properties of canopy was simulated by a view angle geometry model incorporating the solar zenith angle and the sensor viewing angle. Effects of intra-annual and inter-annual variability of structural properties of the canopy on the light extinction coefficient were simulated by implementing variability of the leaf inclination angle (LIA), which was confirmed in the study site. The results revealed good compatibility of the produced Landsat ETM+ LAI data set with the litter-estimated LAI. The results also showed high sensitivity of the LAI retrieval algorithm to variability of structural properties of the canopy: the implementation of LIA dynamics into the LAI retrieval algorithm significantly improved the model accuracy. |
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| Keywords: | Birch Landsat ETM+ LAI Radiative transfer model Germany |
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