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Articles containing the keyword 'temporal transferability'

Category: Research article

article id 10695, category Research article
Ana de Lera Garrido, Terje Gobakken, Hans Ole Ørka, Erik Næsset, Ole M. Bollandsås. (2022). Estimating forest attributes in airborne laser scanning based inventory using calibrated predictions from external models. Silva Fennica vol. 56 no. 2 article id 10695. https://doi.org/10.14214/sf.10695
Keywords: forest inventory; LIDAR; calibration; area-based approach; spatial transferability; temporal transferability
Highlights: Three approaches to calibrate temporal and spatial external models using field observations from different numbers of local plots are presented; Calibration produced satisfactory results, reducing the mean difference between estimated and observed values in 89% of all trials; Using few calibration plots, ratio-calibration provided the lowest mean difference; Calibration using 20 plots gave comparable results to a local forest inventory.
Abstract | Full text in HTML | Full text in PDF | Author Info

Forest management inventories assisted by airborne laser scanner data rely on predictive models traditionally constructed and applied based on data from the same area of interest. However, forest attributes can also be predicted using models constructed with data external to where the model is applied, both temporal and geographically. When external models are used, many factors influence the predictions’ accuracy and may cause systematic errors. In this study, volume, stem number, and dominant height were estimated using external model predictions calibrated using a reduced number of up-to-date local field plots or using predictions from reparametrized models. We assessed and compared the performance of three different calibration approaches for both temporally and spatially external models. Each of the three approaches was applied with different numbers of calibration plots in a simulation, and the accuracy was assessed using independent validation data. The primary findings were that local calibration reduced the relative mean difference in 89% of the cases, and the relative root mean squared error in 56% of the cases. Differences between application of temporally or spatially external models were minor, and when the number of local plots was small, calibration approaches based on the observed prediction errors on the up-to-date local field plots were better than using the reparametrized models. The results showed that the estimates resulting from calibrating external models with 20 plots were at the same level of accuracy as those resulting from a new inventory.

  • de Lera Garrido, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway E-mail: ana.de.lera@nmbu.no (email)
  • Gobakken, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway E-mail: terje.gobakken@nmbu.no
  • Ørka, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway E-mail: hans-ole.orka@nmbu.no
  • Næsset, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway E-mail: erik.naesset@nmbu.no
  • Bollandsås, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway E-mail: ole.martin.bollandsas@nmbu.no

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