Characterization of Canopy Layering in Forested Ecosystems Using Full Waveform Lidar

Abstract

Canopy structure, the vertical distribution of canopy material, is an important element of forest ecosystem dynamics and habitat preference. Although vertical stratification, or "canopy layering," is a basic characterization of canopy structure for research and forest management, it is difficult to quantify at landscape scales. In this paper we describe canopy structure and develop methodologies to map forest vertical stratification in a mixed temperate forest using full-waveform lidar. Two definitions-one categorical and one continuous-are used to map canopy layering over Hubbard Brook Experimental Forest, New Hampshire with lidar data collected in 2009 by NASA's Laser Vegetation Imaging Sensor (LVIS). The two resulting canopy layering datasets describe variation of canopy layering throughout the forest and show that layering varies with terrain elevation and canopy height. This information should provide increased understanding of vertical structure variability and aid habitat characterization and other forest management activities.

Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China

“…A typical example is using remotely sensed optical imagery for mapping the urban land use distribution, which is an important indicator of the economic status of a country [3][4][5]. In addition, remote sensing can also be used to investigate agriculture [6,7], fishery [8,9] and forestry [10], which are important components of a country's economy. Among the various sources of remote sensing data, nighttime light imagery has played a direct and unique role in investigating economic activities, because the artificial nighttime light can reflect the use of public lighting and commercial lighting, which are strongly associated with the state of the economy.…”

Towards Automated Characterization of Canopy Layering in Mixed Temperate Forests Using Airborne Laser Scanning

“…Furthermore, the length of the determined layers was estimated, whereby only changes in absolute point density (i.e., inflexion points in the height distribution function) were used as the criterion to define the borders of a layer, which are not necessarily coincident. Maltamo et al [36] also distribution functions of echo heights, in a manner comparable to Whitehurst et al [30], Ferraz et al [32], and Wang et al [35], to relate the modes of the function (i.e., unimodal or multimodal) to the amount of canopy layers. In contrast, however, a fundamental part of their algorithm was the prior definition of a threshold to separate the dominant tree layer and understory trees, which limits the determination of canopy layers to a maximum of two layers.…”

“…Existing approaches to assess canopy layers often require a substantial set of prior information about stand characteristics or rely on pre-defined height thresholds for an existing stratification of the canopy. Whitehurst et al [30], for example, on one hand used the cumulative canopy cover and pre-defined height thresholds to distinguish between understory (0 to 5 m), midstory (5 to 15 m), and overstory (>15 m). On the other hand, the peaks of the LiDAR waveform were used to determine canopy layers, assuming that each peak represents the mean layer height.…”

“…ALS-based assessment of canopy layering can be either derived from LiDAR waveform data (mostly the case for large or medium-footprint LiDAR systems) [29][30][31], or based on ALS point clouds directly [32,33] or indirectly, e.g., by generating a kind of synthetic waveform using classified echo height distributions or height distribution probability functions [34][35][36]. The assessment of canopy layering with ALS is mainly performed using area-based approaches (ABA).…”

“…On the other hand, the peaks of the LiDAR waveform were used to determine canopy layers, assuming that each peak represents the mean layer height. The peak definition parameters, however, were determined by visual analysis [30]. Ferraz et al [32] applied a mean shift segmentation algorithm to determine the modes of the distribution functions of echo heights and afterwards defined thresholds to divide the canopy into overstory, understory and ground vegetation.…”