Статья

Data acquisition considerations for Terrestrial Laser Scanning of forest plots

Phil WilkesNERC National Center for Earth Observation, UKAlvaro LauLaboratory of Geo-Information Science and Remote Sensing, Wageningen University, P.O. Box 47, Wageningen 6700 AA, the NetherlandsMathias DisneyDepartment of Geography, University College London, Gower Street, London WC1E 6BT, UKKim CaldersEarth Observation, Climate and Optical Group, National Physical Laboratory, Hampton Road, Teddington, TW11 0LW, UKAndrew BurtDepartment of Geography, University College London, Gower Street, London WC1E 6BT, UKJose Gonzalez de TanagoLaboratory of Geo-Information Science and Remote Sensing, Wageningen University, P.O. Box 47, Wageningen 6700 AA, the NetherlandsHarm BartholomeusLaboratory of Geo-Information Science and Remote Sensing, Wageningen University, P.O. Box 47, Wageningen 6700 AA, the NetherlandsBenjamin BredeLaboratory of Geo-Information Science and Remote Sensing, Wageningen University, P.O. Box 47, Wageningen 6700 AA, the NetherlandsMartin HeroldLaboratory of Geo-Information Science and Remote Sensing, Wageningen University, P.O. Box 47, Wageningen 6700 AA, the Netherlands

2017en

ABI

Аннотация

The poor constraint of forest Above Ground Biomass (AGB) is responsible, in part, for large uncertainties in modelling future climate scenarios. Terrestrial Laser Scanning (TLS) can be used to derive unbiased and non-destructive estimates of tree structure and volume and can, therefore, be used to address key uncertainties in forest AGB estimates. Here we review our experience of TLS sampling strategies from 27 campaigns conducted over the past 5 years, across tropical and temperate forest plots, where data was captured with a RIEGL VZ-400 laser scanner. The focus is on strategies to derive Geometrical Modelling metrics (e.g. tree volume) over forest plots (=1 ha) which require the accurate co-registration of 10s to 100s of individual point clouds. We recommend a 10 m × 10 m sampling grid as an approach to produce a point cloud with a uniform point distribution, that can resolve higher order branches (down to a few cm in diameter) towards the top of 30+ m canopies and can be captured in a timely fashion i.e. ~3–6 days per ha. A data acquisition protocol, such as presented here, would facilitate data interoperability and inter-comparison of metrics between instruments/groups, from plot to plot and over time.

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Идентификаторы

DOI: 10.1016/j.rse.2017.04.030

Цитирования и источники

Цитирований: 2Использованных источников: 0

Показатели — AkademScholar