Influence of Natural and Anthropogenic Linear Canopy Openings on Forest Structural Patterns Investigated Using LiDAR

Abstract

In much of the commercial boreal forest, dense road networks and energy corridors have been developed to access natural resources with unintended and poorly understood effects on surrounding forest structure. In this study, we compare the effects of anthropogenic and natural linear openings on surrounding forest conditions in black spruce stands (gap fraction, tree and sapling height, and density). Forest structure within a 100 m band around the edges of anthropogenic (roads and power lines), natural linear openings (streams), and a reference black spruce forest was measured by identifying individual stems and canopy gaps on recent high density airborne LiDAR canopy height models. CUSUM curves were used to assess the distance of edge influence. Forests surrounding anthropogenic openings were found to be gappier, less dense, and have smaller trees than those around natural openings. Forests were denser around natural and anthropogenic linear openings than in the reference forest with edge effects observed up to 24-75 m and 18-54 m, respectively, into the forest. A high density of saplings in the gappier forests surrounding anthropogenic openings may eventually lead to a higher forest biomass in the zone area surrounding roads as is currently observed around natural openings.

Resnet-Based Tree Species Classification Using Uav Images

“…To perform tree crown delineation, an iterative local maxima filtering of varying moving window size based on the tree size measured in the field was used on a Gaussian smoothed DSM reconstructed from RGB images for identifying probable tree tops. Using these as markers, a marker controlled watershed segmentation (Vepakomma et al, 2018) was then performed on the complement of the DSM for segmenting the crowns. The tree crown segmented polygons for a part of the data is shown in Figure 7.…”

Evaluation of Forest Edge Structure and Stability in Peri-Urban Forests

“…We believe that the enhancement comes from the detailed information on forest edge structure and the increased spatial resolution derived from the ALS data in the area of peri-urban forests. In related studies of forest edges, the intention of the researches was primarily to evaluate the distance of influence of edge effects, measured on-site or using contiguous sampling forest bands for determining changes in vegetation composition of forests [30,54]. In addition, wall-to-wall mapping enables the grid-cell predictions to mean or other descriptive statistics of attributes of interest.…”

Urban Forest Growth and Gap Dynamics Detected by Yearly Repeated Airborne Light Detection and Ranging (LiDAR): A Case Study of Cheonan, South Korea

“…From 2014 to 2015, it seemed that because of gap closure, maximum gap area was divided into several patches, and the scaling exponent increased slightly. Finally, since AGp had lower λ values, larger mean gap areas, and slower gap closure rates (6% closed in AGp, while 36% closed in FGp in all total periods, 2012-2015), we can assume that AGp was more vulnerable to physical disturbances; therefore, frequent larger openings occurred in AGp than in FGp [6,32].…”

“…Urban forests are usually fragile to disturbances because the dense human population leads to severe conditions that can damage the forest directly (e.g., land-cover changes from forested to urbanized areas) [5]. Forest damage such as deforestation and landcover changes could result in relatively larger openings than small openings in forests, and human activities therein may hinder the forest equilibrium or change the forest ecosystems [6]. Particularly in South Korea, small and large mountainous urban forests are very common as they remain green areas after development, and many people use them for leisure activities, agriculture, and private graveyards that are accompanied with canopy openings [7][8][9][10][11][12].…”

“…Although ALS-based tree height estimations are less accurate than those using rigorous field measurements [22], the accuracy is acceptable, and the more efficient coverage of large areas by ALS offsets this weakness [17]. Especially, 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 also shown great potential for detecting changes in forest structure [23].…”