Terrestrial Laser Scanning Intensity Data Research Articles

Leaf and Wood Separation for Individual Trees Using the Intensity and Density Data of Terrestrial Laser Scanners

Terrestrial laser scanning (TLS) is a highly effective and noninvasive technology for retrieving the structural and biophysical attributes of trees using 3-D high-accuracy and high-density point clouds. The separation of leaf and wood points in TLS data is a prerequisite for the accurate and reliable derivation of these attributes. In this study, a new method is proposed to separate the leaf and wood points of individual trees by combining the TLS radiometric (intensity) and geometric (density) data. The leaf points are separated from the wood ones through three steps. First, the corrected intensity data are used to separate a part of the leaf points preliminarily given the differences in reflectance characteristics. Second, the density data are adopted for the further separation of another part of the leaf points because the density of the remaining leaf points is smaller than that of the wood points. Finally, a connectivity clustering algorithm is conducted to form several clusters with different sizes (points) and the remaining leaf points are separated in accordance with the cluster sizes. Eight different trees are selected to evaluate the performance of the proposed method. The averaged overall accuracy and kappa coefficient of the eight trees are approximately 95% and 0.81, respectively. The results suggest that the combination of TLS intensity and density data can perform a superior separation of leaf and wood points in terms of efficiency and accuracy, and the proposed separation method can be accurately and robustly used for various trees with different species, sizes, and structures.

DUAL-WAVELENGTH TERRESTRIAL LASER SCANNING AS A CALIBRATION TOOL FOR SATELLITE ESTIMATION OF FOREST CANOPY MOISTURE CONTENT

Abstract. Satellites can estimate forest canopy moisture content at the landscape level, and thus have been widely utilized in forest health monitoring. However, the calibration and validation of the estimation models can be challenging. Collecting a sufficient number of leaf samples from the canopy top layers in sampling plots that match the pixel size of the sensor is needed, which is a cost, time and effort consuming process. Dual-wavelength Terrestrial Laser Scanning (TLS) has been successfully used in estimating canopy moisture content of individual trees in three dimensions (3D) in several recent studies. Such 3D estimates, if produced at the plot level, can be used in the calibration and validation of satellite forest canopy moisture content estimation models. In this study, forest canopy moisture content, quantified as the leaf Equivalent Water Thickness (EWT), was estimated in 3D at the plot level in a mixed-species deciduous broadleaf forest plot using dual-wavelength TLS intensity data (808 nm near infrared and 1550 nm shortwave infrared wavelengths). The relative error in the EWT estimation was 6%, and the EWT point cloud revealed vertical heterogeneity in the EWT distribution. EWT was 37% higher in the canopy top layers than in the canopy bottom layers. The results obtained in this study showed that dual-wavelength TLS has the potential to be used in operational landscape-scale EWT estimation, and can be a useful tool for the calibration and validation of satellite EWT estimation models.

Application of TLS Intensity Data for Detection of Brick Walls Defects

Terrestrial Laser Scanning (TLS) is a well-established technique for remote acquisition of geometrical data of a tested object. For the past two decades it has been commonly used in geodesy, surveying and related areas for acquiring data about spacing of civil engineering structures and buildings. An average TLS apparatus, apart from 3D coordinates registers radiometric information of laser beam reflectance. This radiometric information of the laser beam reflectance is usually called intensity and has no meaning for solely geometric measurements. Nevertheless, the value of intensity depends mainly on physicochemical properties of scanned material such as roughness, colour and saturation. Keeping these facts in mind, authors suggest using changes in value of intensity to locate various imperfections on a brick wall. So far, authors have conducted a thorough and successful research programme dedicated to detection of saturation and saturation movement in brick walls. Based on this experience a new research programme was conducted focused on various aspects of detection of brick wall defects. The main aim of the paper is to present the possibility of using the intensity value in for the diagnostics of the technical condition of a brick walls. Advantages and limitations of harnessing TLS for detection of surface defects of brick walls are presented and discussed in the paper.

Corn Seedling Monitoring Using 3-D Point Cloud Data From Terrestrial Laser Scanning and Registered Camera Data

In precision farming, the separation of crops from soil is crucial for monitoring growth and fertilization. In this letter, a novel method is proposed for the accurate detection of corn seedlings from cropland by combining terrestrial laser scanning (TLS) and camera data. First, a piecewise linear interpolation method was used to eliminate the effect of distance on the TLS intensity data for more accurate intensity features of scanned targets. Second, the point cloud and camera data were registered to obtain the true color of each point in the point cloud. Third, we used a random forest algorithm to separate corn seedlings from soil by combining the geometric features from the TLS data with the radiometric features including the corrected intensity and RGB values derived from the TLS and camera data. To evaluate the proposed method, a case study was conducted by using a commercial TLS sensor with an embedded camera. The results demonstrated that corn seedlings can be separated from soil with an accuracy of 98.8% by using both the geometric and radiometric features, which is significantly higher than that by using any one of the two kinds of features.

THE POTENTIAL OF DUAL-WAVELENGTH TERRESTRIAL LASER SCANNING IN 3D CANOPY FUEL MOISTURE CONTENT MAPPING

Abstract. Terrestrial laser scanning (TLS) instruments have been widely utilized in measuring vegetation canopy structural parameters, being capable of providing high density point clouds. However, less attention has been paid to using TLS intensity data in estimating vegetation biochemical attributes, and calculating water status metrics, that can help in early detection of vegetation stress and risk of wildfire. Water status metrics, such as the leaf Equivalent Water Thickness (EWT) and the Fuel Moisture Content (FMC), are being commonly estimated from optical remote sensing data. However, such estimates mainly reflect the water status of canopy top and ignore the vertical heterogeneity of water content distribution within the canopy. The estimates are also affected by canopy structure and understory reflectance. Such limitations can potentially be addressed using TLS intensity data, as observations are performed in three dimensions (3D). This study therefore investigated the potential of using dual-wavelength TLS intensity data to estimate FMC in 3D. The calculated Normalized Difference Index (NDI) of 808 nm near infrared and 1550 nm shortwave infrared wavelengths was found to be correlated to FMC at leaf level for four different tree species. The correlation was moderate, and the relationships were not consistent between species. NDI was subsequently used to estimate FMC at canopy level in seven trees in a small tree plot with an average error < 5 %. The 3D estimates of FMC revealed vertical heterogeneity in all trees measured, which varied between species and also between trees from the same species.

Specular Reflection Effects Elimination in Terrestrial Laser Scanning Intensity Data Using Phong Model

The intensity value recorded by terrestrial laser scanning (TLS) systems is significantly influenced by the incidence angle. The incidence angle effect is an object property, which is mainly related to target scattering properties, surface structures, and even some instrumental effects. Most existing models focus on diffuse reflections of rough surfaces and ignore specular reflections, despite that both reflections simultaneously exist in all natural surfaces. Due to the coincidence of the emitter and receiver in TLS, specular reflections can be ignored at large incidence angles. On the contrary, at small incidence angles, TLS detectors can receive a portion of specular reflections. The received specular reflections can trigger highlight phenomenon (hot-spot effects) in the intensity data of the scanned targets, particularly those with a relatively smooth or highly-reflective surface. In this study, a new method that takes diffuse and specular reflections, as well as the instrumental effects into consideration, is proposed to eliminate the specular reflection effects in TLS intensity data. Diffuse reflections and instrumental effects are modeled by a polynomial based on Lambertian reference targets, whereas specular reflections are modeled by the Phong model. The proposed method is tested and validated on different targets scanned by the Faro Focus3D 120 terrestrial scanner. Results imply that the coefficient of variation of the intensity data from a homogeneous surface is reduced by approximately 38% when specular reflections are considered. Compared with existing methods, the proposed method exhibits good feasibility and high accuracy in eliminating the specular reflection effects for intensity image interpretation and 3D point cloud representation by intensity.

Glacier Snowline Determination from Terrestrial Laser Scanning Intensity Data

Accurately identifying the extent of surface snow cover on glaciers is important for extrapolating end of year mass balance measurements, constraining the glacier surface radiative energy balance and evaluating model simulations of snow cover. Here, we use auxiliary information from Riegl VZ-6000 Terrestrial Laser Scanner (TLS) return signals to accurately map the snow cover over a glacier throughout an ablation season. Three classification systems were compared, and we find that supervised classification based on TLS signal intensity alone is outperformed by a rule-based classification employing intensity, surface roughness and an associated optical image, which achieves classification accuracy of 68–100%. The TLS intensity signal shows no meaningful relationship with surface or bulk snow density. Finally, we have also compared our Snow Line Altitude (SLA) derived from TLS with SLA derived from the model output, as well as one Landsat image. The results of the model output track the SLA from TLS well, however with a positive bias. In contrast, automatic Landsat-derived SLA slightly underestimates the SLA from TLS. To conclude, we demonstrate that the snow cover extent can be mapped successfully using TLS, although the snow mass remains elusive.

Correction of Mobile TLS Intensity Data for Water Leakage Spots Detection in Metro Tunnels

Terrestrial laser scanning (TLS) can accurately and thoroughly document the actual geometrical deformations and surface conditions of metro tunnel structures using high-density point clouds. In addition, TLS can record the backscattered intensity values of each point simultaneously. Backscattered intensity values are significant measures of the spectral property of scanned objects in the near-infrared region of the electromagnetic spectrum. The intensity values of water leakage regions are theoretically lower than those of the background because of the high water absorption coefficient in the near-infrared spectrum. Thus, the intensity data can be used in water leakage detection and quantitative analysis. This letter investigates the feasibility of a new mobile system called Faro Focus3D X330 for data collection, processing, and intensity correction to detect and extract water leakage spots in metro tunnels. A case study of the Shanghai Metro was conducted. Results show that the corrected intensity value is an effective physical criterion to detect water leakages in metro tunnels. By combing the 3-D point cloud, the location, area, and even water content of the leakage regions can be accurately determined.

Modeling hemispherical reflectance for natural surfaces based on terrestrial laser scanning backscattered intensity data.

Independent of instrumental properties and scanning geometry, target reflectance is significantly important for terrestrial laser scanning (TLS) data processing and utilization, especially in multi-temporal and multi-sensor cases. In addition to the 3D topographic coordinates, TLS systems also record the backscattered intensity value of each point that provides additional information on the reflectance characteristics of the scanned surface. However, a number of confounding variables, particularly the distance and incidence angle, distort the ability of the original intensity to directly retrieve the target reflectance. This study proposes a new method to model the hemispherical reflectance of natural surfaces from the TLS intensity data by eliminating the effects of incidence angle and distance. The incidence angle effect is corrected by the Oren-Nayar reflectance model which takes individual surface roughness into account whereas the irregular distance effect is eliminated by reference targets without estimating the specific distance-intensity function. The Faro Focus3D 120 terrestrial scanner is utilized in the case study. Six typical natural surfaces are chosen as the experimental objects. Results imply that the proposed method exhibits high accuracy in retrieving reflectance values. The deviation of the retrieved reflectance values from that measured by a spectrometer is approximately 4.29% and the root mean square error (RMSE) is approximately 0.0562.

Intensity data correction based on incidence angle and distance for terrestrial laser scanner

Terrestrial laser scanning (TLS) systems not only convey geometric information but also deliver backscattered intensity data of the scanned targets, which are generally acknowledged as significant observations that involve target reflectance information. Numerous studies have shown the potential of TLS intensity in many applications. However, directly using original intensity data is not recommended because of the existence of radiometric system variations, scan geometry discrepancies, environmental differences, and other factors. Performing radiometric correction is, therefore, indispensable to fully eliminate these effects and to compute target reflectance as accurately as possible. In this study, we investigate the effects of incidence angle and distance on intensity measurements and propose a practical method to eliminate the two effects for different TLS instruments. The results show that incidence angle and distance significantly influence TLS intensity data, and the proposed model with versatility can accurately correct the laser intensity value to eliminate the effects of incidence angle and distance.

Deriving Fuel Mass by Size Class in Douglas-fir (Pseudotsuga menziesii) Using Terrestrial Laser Scanning

Requirements for describing coniferous forests are changing in response to wildfire concerns, bio-energy needs, and climate change interests. At the same time, technology advancements are transforming how forest properties can be measured. Terrestrial Laser Scanning (TLS) is yielding promising results for measuring tree biomass parameters that, historically, have required costly destructive sampling and resulted in small sample sizes. Here we investigate whether TLS intensity data can be used to distinguish foliage and small branches (≤0.635 cm diameter; coincident with the one-hour timelag fuel size class) from larger branchwood (>0.635 cm) in Douglas-fir (Pseudotsuga menziesii) branch specimens. We also consider the use of laser density for predicting biomass by size class. Measurements are addressed across multiple ranges and scan angles. Results show TLS capable of distinguishing fine fuels from branches at a threshold of one standard deviation above mean intensity. Additionally, the relationship between return density and biomass is linear by fuel type for fine fuels (r2 = 0.898; SE 22.7%) and branchwood (r2 = 0.937; SE 28.9%), as well as for total mass (r2 = 0.940; SE 25.5%). Intensity decays predictably as scan distances increase; however, the range-intensity relationship is best described by an exponential model rather than 1/d2. Scan angle appears to have no systematic effect on fine fuel discrimination, while some differences are observed in density-mass relationships with changing angles due to shadowing.

Terrestrial laser scanning intensity data applied to damage detection for historical buildings

This paper presents a methodology to combine the technology of the terrestrial laser scanner with the techniques of digital image processing in order to study damages on stony materials that constitute historical buildings. This methodology has been tested using intensity data from three terrestrial laser scanners with different technical specifications. The unsupervised classification algorithms were used for the classification of 2D intensity images derived from the 3D information obtained from laser scanner equipment. The results obtained show the potential of the use of intensity data from terrestrial laser scanner for the recognition and characterization of certain pathologies in building materials that constitute historical buildings.