Creating vegetation density profiles for a diverse range of ecological habitats using terrestrial laser scanning

Mapping Understory Vegetation Density in Mediterranean Forests: Insights from Airborne and Terrestrial Laser Scanning Integration

The understory is an essential ecological and structural component of forest ecosystems. The lack of efficient, accurate, and objective methods for evaluating and quantifying the spatial spread of understory characteristics over large areas is a challenge for forest planning and management, with specific regard to biodiversity and habitat governance. In this study, we used terrestrial and airborne laser scanning (TLS and ALS) data to characterize understory in a European beech and black pine forest in Italy. First, we linked understory structural features derived from traditional field measurements with TLS metrics, then, we related such metrics to the ones derived from ALS. Results indicate that (i) the upper understory density (5-10 m above ground) is significantly associated with two ALS metrics, specifically the mean height of points belonging to the lower third of the ALS point cloud within the voxel (HM_1/3) and the corresponding standard deviation (SD_1/3), while (ii) for the lower understory layer (2-5 m above ground), the most related metric is HM_1/3 alone. As an example application, we have produced a map of forest understory for each layer, extending over the entire study region covered by ALS data, based on the developed spatial prediction models. With this study, we also demonstrated the power of hand-held mobile-TLS as a fast and high-resolution tool for measuring forest structural attributes and obtaining relevant ecological data.

Technological innovation facilitates the practice of "three-dimensional ecology"

The development of "three-dimensional ecology" reveals refreshing phenomena and challenges us to use three-dimensional information for studying animal perception. We created a new processing framework to quantify the shielding effect using a reconstructed environmental structure. The framework achieves three objectives: 1) the observed is introduced, 2) the observed space size can be flexibly dealt with, and 3) three-dimensional attributes are assigned to the environmental structure. Our processing framework is an applicable method to "three-dimensional ecology" based on the three-dimensional attributes of physical structures. We advocate for greater emphasis on "three-dimensional ecology" to recreate realistic animal living conditions and better reveal their behaviors.

Influence of fuel structure derived from terrestrial laser scanning (TLS) on wildfire severity in logged forests

CONTEXT

Logging and wildfire can reduce the height of the forest canopy and the distance to the understorey vegetation below. These conditions may increase the likelihood of high severity wildfire (canopy scorch or consumption), which may explain the greater prevalence of high severity wildfire in some recently logged or burnt forests. However, the effects of these structural characteristics on wildfire severity have not clearly been demonstrated.

OBJECTIVES

We aimed to assess how the structure of forests affected by logging and wildfire influence the probability of high severity wildfire.

METHODS

We used terrestrial laser scanning to measure the connectivity of canopy and understorey vegetation in forests at various stages of recovery after logging and wildfire (approximately 0-80 years since disturbance). These sites were subsequently burnt by mixed severity wildfire during the 2019-20 'Black Summer' fire season in south-eastern Australia. We assessed how these forest structure metrics affected the probability of high severity wildfire.

RESULTS

The probability of high severity fire decreased as the canopy base height increased, and the distance between the canopy base and understorey increased. High severity wildfire was less likely in forests with taller understoreys and greater canopy or understorey cover, but these effects were not considered causal. Fire weather was the strongest driver of wildfire severity, which was also affected by topography.

CONCLUSIONS

These findings demonstrate a link between forest structure characteristics, that are strongly shaped by antecedent logging and fire, and fire severity. They also indicate that vertical fuel structure should be incorporated into assessments of fire risk.

Estimating Ground Elevation and Vegetation Characteristics in Coastal Salt Marshes Using UAV-Based LiDAR and Digital Aerial Photogrammetry

This study evaluates the skills of two types of drone-based point clouds, derived from LiDAR and photogrammetric techniques, in estimating ground elevation, vegetation height, and vegetation density on a highly vegetated salt marsh. The proposed formulation is calibrated and tested using data measured on a Spartina alterniflora-dominated salt marsh in Little Sapelo Island, USA. The method produces high-resolution (ground sampling distance = 0.40 m) maps of ground elevation and vegetation characteristics and captures the large gradients in the proximity of tidal creeks. Our results show that LiDAR-based techniques provide more accurate reconstructions of marsh vegetation (height: MAEVH = 12.6 cm and RMSEVH = 17.5 cm; density: MAEVD = 6.9 stems m−2 and RMSEVD = 9.4 stems m−2) and morphology (MAEM = 4.2 cm; RMSEM = 5.9 cm) than Digital Aerial Photogrammetry (DAP) (MAEVH = 31.1 cm; RMSEVH = 38.1 cm; MAEVD = 12.7 stems m−2; RMSEVD = 16.6 stems m−2; MAEM = 11.3 cm; RMSEM = 17.2 cm). The accuracy of the classification procedure for vegetation calculation negligibly improves when RGB images are used as input parameters together with the LiDAR-UAV point cloud (MAEVH = 6.9 cm; RMSEVH = 9.4 cm; MAEVD = 10.0 stems m−2; RMSEVD = 14.0 stems m−2). However, it improves when used together with the DAP-UAV point cloud (MAEVH = 21.7 cm; RMSEVH = 25.8 cm; MAEVD = 15.2 stems m−2; RMSEVD = 18.7 stems m−2). Thus, we discourage using DAP-UAV-derived point clouds for high-resolution vegetation mapping of coastal areas, if not coupled with other data sources.

Coupling urban 3-D information and circuit theory to advance the development of urban ecological networks

Ongoing, rapid urban growth accompanied by habitat fragmentation and loss challenges biodiversity conservation and leads to decreases in ecosystem services. Application of the concept of ecological networks in the preservation and restoration of connections among isolated patches of natural areas is a powerful conservation strategy. However, previous approaches often failed to objectively consider the impacts of complex 3-D city environments on ecological niches. We used airborne lidar-derived information on the 3-D structure of the built environment and vegetation and detailed land use and cover data to characterize habitat quality, niche diversity, and human disturbance and to predict habitat connectivity among 38 identified habitat core areas (HCAs) in Nanjing, China. We used circuit theory and Linkage Mapper to create a landscape resistance layer, simulate habitat connectivity, and identify and prioritize important corridors. We mapped 64 links by using current flow centrality to evaluate each HCA's contribution and the links that facilitate intact connectivity. Values were highest for HCA links located in the west, south, and northeast of the study area, where natural forests with complex 3-D structures predominate. Two smaller HCA areas had high centrality scores relative to their extents, which means they could act as important stepping stones in connectivity planning. The mapped pinch-point regions had narrow and fragile links among the HCAs, suggesting they require special protection. The barriers with the highest impact scores were mainly located at the HCA connections to Purple Mountain and, based on these high scores, are more likely to indicate important locations that can be restored to improve potential connections. Our novel framework allowed us to sufficiently convey spatially explicit information to identify targets for habitat restoration and potential pathways for species movement and dispersal. Such information is critical for assessing existing or potential habitats and corridors and developing strategic plans to balance habitat conservation and other land uses based on scientifically informed connectivity planning and implementation.

Three-dimensional digital mapping of ecosystems: a new era in spatial ecology

Ecological processes occur over multiple spatial, temporal and thematic scales in three-dimensional (3D) ecosystems. Characterizing and monitoring change in 3D structure at multiple scales is challenging within the practical constraints of conventional ecological tools. Remote sensing from satellites and crewed aircraft has revolutionized broad-scale spatial ecology, but fine-scale patterns and processes operating at sub-metre resolution have remained understudied over continuous extents. We introduce two high-resolution remote sensing tools for rapid and accurate 3D mapping in ecology—terrestrial laser scanning and structure-from-motion photogrammetry. These technologies are likely to become standard sampling tools for mapping and monitoring 3D ecosystem structure across currently under-sampled scales. We present practical guidance in the use of the tools and address barriers to widespread adoption, including testing the accuracy of structure-from-motion models for ecologists. We aim to highlight a new era in spatial ecology that uses high-resolution remote sensing to interrogate 3D digital ecosystems.

Same Viewpoint Different Perspectives—A Comparison of Expert Ratings with a TLS Derived Forest Stand Structural Complexity Index

Forests are one of the most important terrestrial ecosystems for the protection of biodiversity, but at the same time they are under heavy production pressures. In many cases, management optimized for timber production leads to a simplification of forest structures, which is associated with species loss. In recent decades, the concept of retention forestry has been implemented in many parts of the world to mitigate this loss, by increasing structure in managed stands. Although this concept is widely adapted, our understanding what forest structure is and how to reliably measure and quantify it is still lacking. Thus, more insights into the assessment of biodiversity-relevant structures are needed, when aiming to implement retention practices in forest management to reach ambitious conservation goals. In this study we compare expert ratings on forest structural richness with a modern light detection and ranging (LiDAR) -based index, based on 52 research sites, where terrestrial laser scanning (TLS) data and 360° photos have been taken. Using an online survey (n = 444) with interactive 360° panoramic image viewers, we sought to investigate expert opinions on forest structure and learn to what degree measures of structure from terrestrial laser scans mirror experts’ estimates. We found that the experts’ ratings have large standard deviance and therefore little agreement. Nevertheless, when averaging the large number of participants, they distinguish stands according to their structural richness significantly. The stand structural complexity index (SSCI) was computed for each site from the LiDAR scan data, and this was shown to reflect some of the variation of expert ratings (p = 0.02). Together with covariates describing participants’ personal background, image properties and terrain variables, we reached a conditional R2 of 0.44 using a linear mixed effect model. The education of the participants had no influence on their ratings, but practical experience showed a clear effect. Because the SSCI and expert opinion align to a significant degree, we conclude that the SSCI is a valuable tool to support forest managers in the selection of retention patches.

The Laser Vegetation Detecting Sensor: A Full Waveform, Large-Footprint, Airborne Laser Altimeter for Monitoring Forest Resources

The use of satellite-borne large-footprint LiDAR (light detection and ranging) systems allows for the acquisition of forest monitoring data. This paper mainly describes the design, use, operating principles, installation and data properties of the new Laser Vegetation Detecting Sensor (LVDS), a LiDAR system designed and developed at the Academy of Forest Inventory and Planning (AFIP) and the Beijing Institute of Telemetry (BIT). Data from LVDS were used to calculate the mean height of forest trees on sample plots using data collected in the Hunan province of China. The results show that the full waveform data obtained by LVDS has the ability to accurately characterize forest height. The mean absolute percentage error of mean forest height per plot in flat areas was 6.8%, with a mean absolute deviation of 0.78 m. The airborne LVDS system provides prototype data sets and a platform for instrument proof-of-concept studies for China’s Terrestrial Ecosystem Carbon Monitoring (TECM) mission, which is an Earth remote sensing satellite due for launch in 2020. The information produced by LVDS allows for forest structure studies with high accuracy and coverage of large areas.

Analyzing the Vertical Distribution of Crown Material in Mixed Stand Composed of Two Temperate Tree Species

The material distribution inside tree crowns is difficult to quantify even though it is an important variable in forest management and ecology. The vertical distribution of a relative density index (i.e., vertical profile) of the total, woody, and leafy material at the crown scale were estimated from terrestrial laser scanner (TLS) data on two species, sugar maple (Acer saccharum Marsh.) and balsam fir (Abies Balsamea Mill.). An algorithm based on a geometrical approach readily available in the Computree open source platform was used. Beta distributions were then fitted to the vertical profiles and compared to each other. Total and leafy profiles had similar shapes, while woody profiles were different. Thus, the total vertical distribution could be a good proxy for the leaf distribution in the crown. Sugar maple and balsam fir had top heavy and bottom heavy distributions respectively, which can be explained by their respective architectural development. Moreover, the foliage distribution of sugar maples shifted towards the crown base when it was found in mixed stands, when compared to pure stands. The opposite behavior was observed for balsam firs, but less pronounced. According to the shape of the foliage distribution, sugar maple takes advantages from mixture contrarily to balsam fir. From a methodological point of view, we proposed an original approach to separate wood from leaf returns in TLS data while taking into account occlusion. Wood and leaf separation and occlusion problems are two challenging issues for most TLS-based studies in forest ecology.

Terrestrial laser scanning for vegetation sampling

We developed new vegetation indices utilizing terrestrial laser scanning (TLS) to quantify the three-dimensional spatial configuration of plant communities. These indices leverage the novelty of TLS data and rely on the spatially biased arrangement of a TLS point cloud. We calculated these indices from TLS data acquired within an existing long term manipulation of forest structure in Central Oregon, USA, and used these data to test for differences in vegetation structure. Results provided quantitative evidence of a significant difference in vegetation density due to thinning and burning, and a marginally significant difference in vegetation patchiness due to grazing. A comparison to traditional field sampling highlighted the novelty of the TLS based method. By creating a linkage between traditional field sampling and landscape ecology, these indices enable field investigations of fine-scale spatial patterns. Applications include experimental assessment, long-term monitoring, and habitat characterization.