Plot location errors of National Forest Inventory: related factors and adverse effects on continuity of plot data

Nakajima, Haruki

doi:10.1007/s10310-016-0538-1

Cited by 5 publications

(1 citation statement)

References 24 publications

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“…One of the key issues of combining remote sensing-based CHMs and field data from national forest inventory for assessing forest parameters relates to the spatial adjustment of both data sources (Nakajima 2016;Johnson et al 2014). While 3D remote sensing data might provide a sub-metric accuracy in both the vertical and horizontal dimensions (Favorskaya and Jain 2017;Baltsavias 1999), the accuracy of field plots positioning is constrained by the interaction of the Global Navigation Satellite System (GNSS) signal with the canopy elements, resulting in accuracies of a few meters (~5 m) with low-cost differential GNSS measurements (Ransom et al 2010;Valbuena et al 2010;Danskin et al 2009;Wing and Eklund 2007).…”

Section: Introductionmentioning

confidence: 99%

RegisTree: a registration algorithm to enhance forest inventory plot georeferencing

Fadili

Renaud

Bock

et al. 2019

Annals of Forest Science

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& Key message The accuracy of remote sensing-based models of forest attributes could be improved by controlling the spatial registration of field and remote sensing data. We have demonstrated the potential of an algorithm matching plotlevel field tree positions with lidar canopy height models and derived local maxima to achieve a precise registration automatically. & Context The accuracy of remote sensing-based estimates of forest parameters depends on the quality of the spatial registration of the training data. & Aims This study introduces an algorithm called RegisTree to correct field plot positions by matching a spatialized field tree height map with lidar canopy height models (CHMs). & Methods RegisTree is based on a point (field positions) to surface (CHM) adjustment approach modified to ensure that at least one field tree position corresponds to CHM local maxima. & Results RegisTree has been validated with respect to positioning errors and the performance of lidar-derived estimation of plot volume. Overall, RegisTree enabled to register field plots surveyed in a range of forest conditions with a precision of 1.5 m (± 1.23 m), but a higher performance for conifer plots, and a limited efficiency in homogeneous stands, having similar heights. Improved plot positions were found to have a limited impact on volume predictions under the range of tested conditions, with a gain up to 1.3%. & Conclusion RegisTree could be used to improve the forest plot position from field surveys collected with low-grade GPS and to contribute to the development of processing chains of 3D remote sensing-based models of forest parameters.

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Section: Introductionmentioning

confidence: 99%

RegisTree: a registration algorithm to enhance forest inventory plot georeferencing

Fadili

Renaud

Bock

et al. 2019

Annals of Forest Science

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Region-wide mass mortality of Japanese oak due to ambrosia beetle infestation: Mortality factors and change in oak abundance

Nakajima

2019

Forest Ecology and Management

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富山県における森林生態系多様性基礎調査データを用いたナラ枯れ被害材積統計値の検証

Nakajima

2023

J. Jpn. For. Soc.

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Statistics regarding wood volume damaged by Japanese oak wilt (JOW) are presented annually in the governmentʼs annual report on forests and forestry. Although these statistics are used as basic information to consider countermeasures against damage due to JOW, they are unverified. Therefore, in this study, the statistics for private forests of Toyama Prefecture, where an epidemic of JOW occurred from 2004 to 2011, were verified. The statistics were based on the number of dead crowns counted visually from roads. The total statistics of damaged wood volume from 2002 to 2017, encompassing the period when mortality from JOW occurred, was 0.12 million m 3 . In contrast, the estimated damaged wood volume calculated from two successive measurements before and after the JOW epidemic in 101 plots of the National Forest Inventory, was 1.78 ± 0.81 million m 3 (point estimate ± 95％ confidence intervals). This suggests that the statistics are an underestimation; the main reason for this is probably the existence of parts that cannot be visually observed. The volume loss rates of Quercus crispula and Quercus serrata were estimated as 57 and 9％, respectively; thus, the impact of JOW on forest resources was clarified at a regional scale.

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Plot location errors of National Forest Inventory: related factors and adverse effects on continuity of plot data

Cited by 5 publications

References 24 publications

RegisTree: a registration algorithm to enhance forest inventory plot georeferencing

RegisTree: a registration algorithm to enhance forest inventory plot georeferencing

Region-wide mass mortality of Japanese oak due to ambrosia beetle infestation: Mortality factors and change in oak abundance

富山県における森林生態系多様性基礎調査データを用いたナラ枯れ被害材積統計値の検証

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