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Urban-Tree-Attribute Update Using Multisource Single-Tree Inventory

Authors: Saarinen, Ninni; Vastaranta, Mikko; Kankare, Ville; Tanhuanpaa, Topi; Holopainen, Markus; Hyyppä, Juha; Hyyppä; +1 Authors

Urban-Tree-Attribute Update Using Multisource Single-Tree Inventory

Abstract

The requirements for up-to-date tree data in city parks and forests are increasing, and an important question is how to keep the digital databases current for various applications. Traditional map-updating procedures, such as visual interpretation of digital aerial images or field measurements using tachymeters, are either inaccurate or expensive. Recently, the development of laser-scanning technology has opened new opportunities for tree mapping and attributes updating. For a detailed measurement and attributes update of urban trees, we tested the use of a multisource single-tree inventory (MS-STI) for heterogeneous urban forest conditions. MS-STI requires an existing tree map as input information in addition to airborne laser-scanning (ALS) data. In our study, the tested input tree map was produced by terrestrial laser scanning (TLS) and by using a Global Navigation Satellite System (GNSS). Tree attributes were either measured from ALS or predicted by using metrics extracted from ALS data. Stem diameter-at-breast height (DBH) was predicted and compared to the field measures, and tree height and crown area were directly measured from ALS data at the two different urban-forest areas. The results indicate that MS-STI can be used for updating urban-forest attributes. The accuracies of DBH estimations were improved compared to the existing attribute information in the city of Helsinki’s urban-tree register. In addition, important attributes, such as tree height and crown dimensions, were extracted from ALS and added as attributes to the urban-tree register.

Country
Finland
Keywords

NEAREST-NEIGHBOR IMPUTATION, TERRESTRIAL, ta520, ta222, LiDAR, ta1171, BIOMASS, remote sensing, city planning, HEIGHT, AIRBORNE LASER SCANNER, forest inventory, FOREST STAND CHARACTERISTICS, ta513, ta212, ta113, INDIVIDUAL TREES, STEM ATTRIBUTES, Airborne laser scanning, Forestry, GIS, GROUND-BASED LIDAR, VOLUME, urban forest; remote sensing; LiDAR; Airborne laser scanning; GIS; forest inventory; forest mapping; city planning; land-use planning, urban forest, forest mapping, land-use planning

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
37
Top 10%
Top 10%
Top 10%
Green
gold