Abstract
Understanding forest dynamics is important for assessing the health of urban forests, which experience various disturbances, both natural (e.g., treefall events) and artificial (e.g., making space for agricultural fields). Therefore, quantifying three-dimensional changes in canopies is a helpful way to manage and understand urban forests better. Multitemporal airborne light detection and ranging (LiDAR) datasets enable us to quantify the vertical and lateral growth of trees across a landscape scale. The goal of this study is to assess the annual changes in the 3-D structures of canopies and forest gaps in an urban forest using annual airborne LiDAR datasets for 2012–2015. The canopies were classified as high canopies and low canopies by a 5 m height threshold. Then, we generated pixel- and plot-level canopy height models and conducted change detection annually. The vertical growth rates and leaf area index showed consistent values year by year in both canopies, while the spatial distributions of the canopy and leaf area profile (e.g., leaf area density) showed inconsistent changes each year in both canopies. In total, high canopies expanded their foliage from 12 m height, while forest gap edge canopies (including low canopies) expanded their canopies from 5 m height. Annual change detection with LiDAR datasets might inform about both steady growth rates and different characteristics in the changes of vertical canopy structures for both high and low canopies in urban forests.
Highlights
Quantifying forest gaps is essential for monitoring the stability of the forest structure because these disturbances can change the light environment and drive forest dynamics [1,2,3,4]
Forest Gap (FGp) exhibited the greatest differences in canopy complexity for 2012–2015 (0.93 ± 4.15 m2/m2) followed by HC and AGp, which possibly indicated that FGp had an important role in increasing canopy structural diversity (Figure 6b)
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Summary
Quantifying forest gaps is essential for monitoring the stability of the forest structure because these disturbances can change the light environment and drive forest dynamics [1,2,3,4]. Airborne photogrammetry and satellite imagery are applied to measure the diameter at breast height, stand height, basal area, and species composition using terrestrial field sampling data These traditional methods have certain limitations related to the subjective interpretation of measurement results, low measurement accuracy, and lack of information about vertical canopy structures [15,16,17,18,19,20,21]. Vepakomma et al [6] reported the difference between the effects of natural and anthropogenic linear openings (i.e., steam and roads) with LiDAR data These days, with its acceptable accuracy and advantages in sensing vertical canopy structures, multitemporal LiDAR surveys have shown great potential for detecting changes in forest structure [23]. Artirfiticfiiacilaclacnaonpoypoypoepneinnginsgosr ograpgsa:p(sa: a(nadanbd), sbp),orstpsofratcsilfiaticeisli;t(icesa;n(dc dan),dprdiv),ate gprarivveaytaergdrsa;vaenydar(edsa;nadnfd),(aegarnicdufl)t,uargalrilcaunldtus.ral lands
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