Timber production assessment of a plantation forest: An integrated framework with field-based inventory,multi-source remote sensing data and forest management history |
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| Institution: | 1. Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China;2. Qingyuan Forest CERN, Chinese Academy of Sciences, Shenyang 110016, China;3. Institute of Mountain Science, Shinshu University, Nagano 399-4598, Japan;4. University of Chinese Academy of Sciences, Beijing 100049, China;1. Montane Forest Dynamics Laboratory, Department of Geology and Geography, West Virginia University, Morgantown, WV 26505, USA;2. Cook’s Mill, Post Office Box 128, Greenville, WV 24945, USA;1. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China;2. Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, 210023, China;3. Geospatial Laboratory for Environmental Dynamics, University of Idaho, Moscow, ID 83844-1135, USA;4. McCall Outdoor Science School, University of Idaho, McCall, ID 83638, USA;5. NASA Jet Propulsion Laboratory, 4800 Oak Grove Dr. MS 233-300, Pasadena, CA, 91109, USA;6. Remote Sensing and Geospatial Analysis Laboratory, Precision Forestry Cooperative, School of Environment and Forest Science, University of Washington, Box 352100, Seattle, WA, 98115-2100, USA;1. Institute of Remote Sensing and Geographic Information Systems, School of Earth and Space Science, Peking University, 100871 Beijing, China;2. Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, 6708 PB Wageningen, The Netherlands |
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| Abstract: | Timber production is the purpose for managing plantation forests, and its spatial and quantitative information is critical for advising management strategies. Previous studies have focused on growing stock volume (GSV), which represents the current potential of timber production, yet few studies have investigated historical process-harvested timber. This resulted in a gap in a synthetical ecosystem service assessment of timber production. In this paper, we established a Management Process–based Timber production (MPT) framework to integrate the current GSV and the harvested timber derived from historical logging regimes, trying to synthetically assess timber production for a historical period. In the MPT framework, age-class and current GSV determine the times of historical thinning and the corresponding harvested timber, by using a “space-for-time” substitution. The total timber production can be estimated by the historical harvested timber in each thinning and the current GSV. To test this MPT framework, an empirical study on a larch plantation (LP) with area of 43,946 ha was conducted in North China for a period from 1962 to 2010. Field-based inventory data was integrated with ALOS PALSAR (Advanced Land-Observing Satellite Phased Array L-band Synthetic Aperture Radar) and Landsat-8 OLI (Operational Land Imager) data for estimating the age-class and current GSV of LP. The random forest model with PALSAR backscatter intensity channels and OLI bands as input predictive variables yielded an accuracy of 67.9% with a Kappa coefficient of 0.59 for age-class classification. The regression model using PALSAR data produced a root mean square error (RMSE) of 36.5 m3 ha−1. The total timber production of LP was estimated to be 7.27 × 106 m3, with 4.87 × 106 m3 in current GSV and 2.40 × 106 m3 in harvested timber through historical thinning. The historical process-harvested timber accounts to 33.0% of the total timber production, which component has been neglected in the assessments for current status of plantation forests. Synthetically considering the RMSE for predictive GSV and misclassification of age-class, the error in timber production were supposed to range from −55.2 to 56.3 m3 ha−1. The MPT framework can be used to assess timber production of other tree species at a larger spatial scale, providing crucial information for a better understanding of forest ecosystem service. |
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| Keywords: | Larch plantation Growing stock volume Harvested timber Age-class Radar backscatter ALOS PALSAR Landsat-8 OLI Random forest model Logging regime |
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