Urban energetics applications and Geomatic technologies in a Smart City perspective

2015 ◽  
Vol 6 (1) ◽  
pp. 19-29 ◽  
Author(s):  
G. Bitelli ◽  
P. Conte ◽  
T. Csoknyai ◽  
E. Mandanici
Keyword(s):  
Smart City ◽  
Laser Scanning ◽  
Near Infrared ◽  
Three Dimensional ◽  
Energy Sector ◽  
Primary Objective ◽  
Airborne Lidar ◽  
City Management ◽  
Urban Context ◽  
Research Areas

The management of an urban context in a Smart City perspective requires the development of innovative projects, with new applications in multidisciplinary research areas. They can be related to many aspects of city life and urban management: fuel consumption monitoring, energy efficiency issues, environment, social organization, traffic, urban transformations, etc. Geomatics, the modern discipline of gathering, storing, processing, and delivering digital spatially referenced information, can play a fundamental role in many of these areas, providing new efficient and productive methods for a precise mapping of different phenomena by traditional cartographic representation or by new methods of data visualization and manipulation (e.g. three-dimensional modelling, data fusion, etc.). The technologies involved are based on airborne or satellite remote sensing (in visible, near infrared, thermal bands), laser scanning, digital photogrammetry, satellite positioning and, first of all, appropriate sensor integration (online or offline). The aim of this work is to present and analyse some new opportunities offered by Geomatics technologies for a Smart City management, with a specific interest towards the energy sector related to buildings. Reducing consumption and CO2 emissions is a primary objective to be pursued for a sustainable development and, in this direction, an accurate knowledge of energy consumptions and waste for heating of single houses, blocks or districts is needed. A synoptic information regarding a city or a portion of a city can be acquired through sensors on board of airplanes or satellite platforms, operating in the thermal band. A problem to be investigated at the scale A problem to be investigated at the scale of the whole urban context is the Urban Heat Island (UHI), a phenomenon known and studied in the last decades. UHI is related not only to sensible heat released by anthropic activities, but also to land use variations and evapotranspiration reduction. The availability of thermal satellite sensors is fundamental to carry out multi-temporal studies in order to evaluate the dynamic behaviour of the UHI for a city. Working with a greater detail, districts or single buildings can be analysed by specifically designed airborne surveys. The activity has been recently carried out in the EnergyCity project, developed in the framework of the Central Europe programme established by UE. As demonstrated by the project, such data can be successfully integrated in a GIS storing all relevant data about buildings and energy supply, in order to create a powerful geospatial database for a Decision Support System assisting to reduce energy losses and CO2 emissions. Today, aerial thermal mapping could be furthermore integrated by terrestrial 3D surveys realized with Mobile Mapping Systems through multisensor platforms comprising thermal camera/s, laser scanning, GPS, inertial systems, etc. In this way the product can be a true 3D thermal model with good geometric properties, enlarging the possibilities in respect to conventional qualitative 2D images with simple colour palettes. Finally, some applications in the energy sector could benefit from the availability of a true 3D City Model, where the buildings are carefully described through three-dimensional elements. The processing of airborne LiDAR datasets for automated and semi-automated extraction of 3D buildings can provide such new generation of 3D city models.

scholarly journals Toward a Novel Laser-Based Approach for Estimating Snow Interception

2020 ◽  
Vol 12 (7) ◽  
pp. 1146 ◽  
Author(s):  
Micah Russell ◽  
Jan U. H. Eitel ◽  
Andrew J. Maguire ◽  
Timothy E. Link
Keyword(s):  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Primary Objective ◽  
Snow Accumulation ◽  
Future Research ◽  
Snow Density ◽  
Canopy Interception ◽  
Terrestrial Lidar ◽  
Large Trees

Forests reduce snow accumulation on the ground through canopy interception and subsequent evaporative losses. To understand snow interception and associated hydrological processes, studies have typically relied on resource-intensive point scale measurements derived from weighed trees or indirect measurements that compared snow accumulation between forested sites and nearby clearings. Weighed trees are limited to small or medium-sized trees, and indirect comparisons can be confounded by wind redistribution of snow, branch unloading, and clearing size. A potential alternative method could use terrestrial lidar (light detection and ranging) because three-dimensional lidar point clouds can be generated for any size tree and can be utilized to calculate volume of the intercepted snow. The primary objective of this study was to provide a feasibility assessment for estimating snow interception volume with terrestrial laser scanning (TLS), providing information on challenges and opportunities for future research. During the winters of 2017 and 2018, intercepted snow masses were continuously measured for two model trees suspended from load-cells. Simultaneously, autonomous terrestrial lidar scanning (ATLS) was used to develop volumetric estimates of intercepted snow. Multiplying ATLS volume estimates by snow density estimates (derived from empirical models based on air temperature) enabled the comparison of predicted vs. measured snow mass. Results indicate agreement between predicted and measured values (R2 ≥ 0.69, RMSE ≥ 0.91 kg, slope ≥ 0.97, intercept ≥ −1.39) when multiplying TLS snow interception volume with a constant snow density estimate. These results suggest that TLS might be a viable alternative to traditional approaches for mapping snow interception, potentially useful for estimating snow loads on large trees, collecting data in difficult to access terrain, and calibrating snow interception models to new forest types around the globe.

Assessing Terrestrial Laser Scanning in Complex Environments

2014 ◽  
Vol 2 (2) ◽  
pp. 123-137 ◽  
Author(s):  
Jennifer Weber ◽  
Terry G. Powis
Keyword(s):  
Laser Scanning ◽  
Visual Analysis ◽  
Three Dimensional ◽  
Data Interpretation ◽  
Current Data ◽  
Airborne Lidar ◽  
Archaeological Sites ◽  
Complex Environments ◽  
Non Invasive ◽  
Maya Site

AbstractThe majority of terrestrial scanning projects in archaeology have focused on heritage documentation, preservation, and the three-dimensional (3D) reconstruction of prominent sites and objects. While these are very important archaeological foci, not many have used terrestrial scanning methods for prospection and feature analysis, similar to the way many have employed airborne LiDAR. While airborne LiDAR scanning is able to situate and analyze archaeological sites on an expansive scale, the ground-based method also captures and defines any landscape anomalies or depressions from cultural features that have remained invisible to the naked eye due to environmental restrictions. In an attempt to test this recording method, we set out to paint a non-invasive, 3D digitized picture of the ancient Maya site of Pacbitun, Belize, using terrestrial scanning to distinctly detail Pacbitun’s structures, plazas, causeways, and karst features. This paper details the process through which 3D terrestrial scanning was executed at Pacbitun and three associated peripheral caves during the 2012 and 2013 field seasons. We discuss the potential laser scanning has for visual analysis in archaeology and evaluate application difficulties encountered in the field, as well as current data interpretation issues.

scholarly journals TLS FIELD DATA BASED INTENSITY CORRECTION FOR FOREST ENVIRONMENTS

2016 ◽  
Vol XLI-B8 ◽  
pp. 643-649
Author(s):  
J. Heinzel ◽  
M. O. Huber
Keyword(s):  
Laser Scanning ◽  
Field Data ◽  
Near Infrared ◽  
Three Dimensional ◽  
Correction Method ◽  
Laser Wavelength ◽  
Absolute Calibration ◽  
Equal Distribution ◽  
Model Driven ◽  
Specific Factors

Terrestrial laser scanning (TLS) is increasingly used for forestry applications. Besides the three dimensional point coordinates, the 'intensity' of the reflected signal plays an important role in forestry and vegetation studies. The benefit of the signal intensity is caused by the wavelength of the laser that is within the near infrared (NIR) for most scanners. The NIR is highly indicative for various vegetation characteristics. <br><br> However, the intensity as recorded by most terrestrial scanners is distorted by both external and scanner specific factors. Since details about system internal alteration of the signal are often unknown to the user, model driven approaches are impractical. On the other hand, existing data driven calibration procedures require laborious acquisition of separate reference datasets or areas of homogenous reflection characteristics from the field data. <br><br> In order to fill this gap, the present study introduces an approach to correct unwanted intensity variations directly from the point cloud of the field data. The focus is on the variation over range and sensor specific distortions. Instead of an absolute calibration of the values, a relative correction within the dataset is sufficient for most forestry applications. Finally, a method similar to time series detrending is presented with the only pre-condition of a relative equal distribution of forest objects and materials over range. Our test data covers 50 terrestrial scans captured with a FARO Focus 3D S120 scanner using a laser wavelength of 905 nm. Practical tests demonstrate that our correction method removes range and scanner based alterations of the intensity.

Development on Filtering Algorithms of Airborne LiDAR Point Clouds

2012 ◽  
Vol 226-228 ◽  
pp. 1892-1898
Author(s):  
Jian Qing Shi ◽  
Ting Chen Jiang ◽  
Ming Lian Jiao
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Filtering Algorithms ◽  
Filtering Algorithm ◽  
Digital Elevation ◽  
City Model ◽  
Elevation Model

Airborne LiDAR is a new kind of surveying technology of remote sensing which developed rapidly during recent years. Raw laser scanning point clouds data include terrain points, building points, vegetation points, outlier points, etc.. In order to generate digital elevation model (DEM) and three-dimensional city model,these point clouds data must be filtered. Mathematical morphology based filtering algorithm, slope based filtering algorithm, TIN based filtering algorithm, moving surface based filtering algorithm, scanning lines based filtering algorithm and so on several representative filtering algorithms for LiDAR point clouds data have been introduced and discussed and contrasted in this paper. Based on these algorithms summarize the studying progresss about the filtering algorithm of airborne LiDAR point clouds data in home and abroad. In the end, the paper gives an expectation which will provides a reference for the following relative study.

scholarly journals Important Airborne Lidar Metrics of Canopy Structure for Estimating Snow Interception

2021 ◽  
Vol 13 (20) ◽  
pp. 4188
Author(s):  
Micah Russell ◽  
Jan U. H. Eitel ◽  
Timothy E. Link ◽  
Carlos A. Silva
Keyword(s):  
Laser Scanning ◽  
Mean Squared Error ◽  
Canopy Structure ◽  
Three Dimensional ◽  
Variable Importance ◽  
Airborne Lidar ◽  
Extrinsic Factors ◽  
Area Index ◽  
Wide Range ◽  
Structural Metrics

Forest canopies exert significant controls over the spatial distribution of snow cover. Canopy snow interception efficiency is controlled by intrinsic processes (e.g., canopy structure), extrinsic processes (e.g., meteorological conditions), and the interaction of intrinsic-extrinsic factors (i.e., air temperature and branch stiffness). In hydrological models, intrinsic processes governing snow interception are typically represented by two-dimensional metrics like the leaf area index (LAI). To improve snow interception estimates and their scalability, new approaches are needed for better characterizing the three-dimensional distribution of canopy elements. Airborne laser scanning (ALS) provides a potential means of achieving this, with recent research focused on using ALS-derived metrics that describe forest spacing to predict interception storage. A wide range of canopy structural metrics that describe individual trees can also be extracted from ALS, although relatively little is known about which of them, and in what combination, best describes intrinsic canopy properties known to affect snow interception. The overarching goal of this study was to identify important ALS-derived canopy structural metrics that could help to further improve our ability to characterize intrinsic factors affecting snow interception. Specifically, we sought to determine how much variance in canopy intercepted snow volume can be explained by ALS-derived crown metrics, and what suite of existing and novel crown metrics most strongly affects canopy intercepted snow volume. To achieve this, we first used terrestrial laser scanning (TLS) to quantify snow interception on 14 trees. We then used these snow interception measurements to fit a random forest model with ALS-derived crown metrics as predictors. Next, we bootstrapped 1000 calculations of variable importance (percent increase in mean squared error when a given explanatory variable is removed), keeping nine canopy metrics for the final model that exceeded a variable importance threshold of 0.2. ALS-derived canopy metrics describing intrinsic tree structure explained approximately two-thirds of the snow interception variability (R2 ≥ 0.65, RMSE ≤ 0.52 m3, relative RMSE ≤ 48%) in our study when extrinsic factors were kept as constant as possible. For comparison, a generalized linear mixed-effects model predicting snow interception volume from LAI alone had a marginal R2 = 0.01. The three most important predictor variables were canopy length, whole-tree volume, and unobstructed returns (a novel metric). These results suggest that a suite of intrinsic variables may be used to map interception potential across larger areas and provide an improvement to interception estimates based on LAI.

scholarly journals A Method for Estimating the Surface Roughness of Rock Discontinuities

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Yi Cai ◽  
Hui-ming Tang ◽  
Ding-jian Wang ◽  
Tao Wen
Keyword(s):  
Surface Roughness ◽  
Shear Strength ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Back Analysis ◽  
Sampling Interval ◽  
Primary Objective ◽  
Roughness Coefficient ◽  
Rock Discontinuities ◽  
Estimation Formula

The primary objective of this study is to develop a parameter with a clear physical meaning to estimate the surface roughness of rock discontinuities. This parameter must be closely related to the shear strength of rock discontinuities. The first part of this study focuses on defining and computing this parameter. The estimation formula for the shear strength of a triangle within a discontinuity surface is derived based on Patton’s model. The parameter, namely, the index of roughness (IR), is then proposed to quantitatively estimate discontinuity roughness. Based on laser scanning techniques, digital models of discontinuities and discontinuity profiles are constructed, and then their corresponding IR values are computed. In the second part of this study, the computational processes and estimated effects of the two-dimensional (2D) and three-dimensional (3D) IR values of the discontinuities are illustrated through several applications. Results show that the 2D and 3D IR values of these discontinuities indicate anisotropy and sampling interval effects. In addition, a strong linear correlation is detected between IR and the joint roughness coefficient (JRC) for seventy-four profiles and eleven discontinuity specimens, respectively. Finally, the proposed method, back analysis method, root mean square (Z2) method, and Grasselli’s method are compared to study the use of the parameter IR.

scholarly journals APPLICABILITY ANALYSIS OF CLOTH SIMULATION FILTERING ALGORITHM FOR MOBILE LIDAR POINT CLOUD

2018 ◽  
Vol XLII-3 ◽  
pp. 107-111 ◽  
Author(s):  
S. Cai ◽  
W. Zhang ◽  
J. Qi ◽  
P. Wan ◽  
J. Shao ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Cloth Simulation ◽  
Large Area ◽  
Three Samples ◽  
Separate Point ◽  
A New Technique

Classifying the original point clouds into ground and non-ground points is a key step in LiDAR (light detection and ranging) data post-processing. Cloth simulation filtering (CSF) algorithm, which based on a physical process, has been validated to be an accurate, automatic and easy-to-use algorithm for airborne LiDAR point cloud. As a new technique of three-dimensional data collection, the mobile laser scanning (MLS) has been gradually applied in various fields, such as reconstruction of digital terrain models (DTM), 3D building modeling and forest inventory and management. Compared with airborne LiDAR point cloud, there are some different features (such as point density feature, distribution feature and complexity feature) for mobile LiDAR point cloud. Some filtering algorithms for airborne LiDAR data were directly used in mobile LiDAR point cloud, but it did not give satisfactory results. In this paper, we explore the ability of the CSF algorithm for mobile LiDAR point cloud. Three samples with different shape of the terrain are selected to test the performance of this algorithm, which respectively yields total errors of 0.44&amp;thinsp;%, 0.77&amp;thinsp;% and1.20&amp;thinsp;%. Additionally, large area dataset is also tested to further validate the effectiveness of this algorithm, and results show that it can quickly and accurately separate point clouds into ground and non-ground points. In summary, this algorithm is efficient and reliable for mobile LiDAR point cloud.

scholarly journals Reconstruction and Measurement of Irregular Karst Caves Using BLST along the Shield Metro Line

2020 ◽  
Vol 10 (1) ◽  
pp. 392 ◽  
Author(s):  
Shangqu Sun ◽  
Liping Li ◽  
Jing Wang ◽  
Shuguang Song ◽  
Peng He ◽  
...  
Keyword(s):  
Laser Power ◽  
Laser Scanning ◽  
Near Infrared ◽  
Three Dimensional ◽  
Environmental Parameters ◽  
Shape Space ◽  
Karst Cave ◽  
Detection Distance ◽  
Karst Caves ◽  
High Turbidity

This study investigated the application of the borehole laser scanning technology (BLST) method in the detection of both dry and water-filled karst caves. In order to solve the problem of excessive laser attenuation during the detection, we designed a test for the characteristics of multiwavelength laser attenuation in water-filled karst caves and studied the influence exerted by various factors, including different wavelengths, different laser power levels, different suspended media, and effect of turbidity on the attenuation coefficient. During the test, we discovered the existence of a “blue-green window” with low turbidity and a “near infrared window” with high turbidity in karst cave water environments. Based on the general survey results of drilling and comprehensive geophysical prospecting, a quantitative method using targeted drilling was proposed to detect the spatial morphology of karst caves in complex environments. We also investigated the effects of complex environmental factors such as suspended media and high turbidity on the laser detection distance and accuracy in karst caves, and established a quantitative matching model of laser wavelengths, laser power, and complex environmental parameters. Based on this, we obtained the best acquisition mode for detecting lasers in different karst development environments. A high-precision, three-dimensional visualized model of a real karst cave was established to quantitatively obtain the characteristic parameters, such as accurate position, three-dimensional shape, space volume, and cave filling type, which was applied to the detection of karst caves along the Jinan subway line.

Laser scanning as a tool for the analysis of the greenery on the example of Poremba district in Lublin

2015 ◽  
Vol 26 (3-4) ◽  
pp. 132-140
Author(s):  
P. G. Kotsyuba ◽  
I. D. Semko ◽  
I. I. Kozak ◽  
T. V. Parpan ◽  
G. G. Kozak ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Green Space ◽  
Three Dimensional ◽  
Tree Height ◽  
Field Measurements ◽  
Airborne Lidar ◽  
Dimensional Structure ◽  
Lidar Data ◽  
Definition Of ◽  
Airborne Lidar Data

World experience shows that the survey of green spaces by traditional methods is very time consuming, costly and does not always get all the information you need to make of adequate management decisions by municipal authorities. The aim of this article was to show the main stages of analysis and prospects of urban green space using aerial lidar data and submit the effect of three-dimensional visualization of the study area. There were presented the possibilities and perspectives of using the data obtained from airborne laser scanning (ALS) for the analysis of greenery on the example of Poremba district in Lublin (Poland). Research conducted in Poremba district in the Polish city of Lublin (district was built from 1988 to 2005 and is located in the western part of the city). Analysis of green space conducted using quantitative analytical methods. By detailed analysis of the study area were used aerial lidar data from the year 2015. To classify aerial lidar data such software were used: LP360, ArcMap 10.3, Toolbox LAStools. The process of analysis begins with the definition of points, belonging to ground (Ground - GR), and the classification was realized using «lasground» with tools LAStools. The article is dedicated to development the method of estimation the tree height based on airborne LiDAR data. Method applies more information about the three-dimensional structure of natural objects derived from the processing of airborne LiDAR data compared with known methods. Furthermore, the method is adapted to determine and calculate characteristics of stand which using for tree inventory in cities. Methodological and algorithmic instructions to determine the tree parameters in city were proposed. These instructions allow automatically calculating the characteristics of the tree parameters, such as the allocation of each tree and tree height. The study area was analyzed in terms of the distribution of vegetation (separately individual growing trees and groups of trees). For that purpose there was applied an available ALS data. Based on the ALS data there were separated the tops of the trees and their height. In order to verify the ALS data there were used the results of field measurements (coordinates for the tree trunks, the diameter at breast height of trees, their height, crown projection). The analysis of the greenery within the Poremba district using the ALS data after verification with the field measurements proved to be an effective tool for the characterization of the greenery areas in particular city. This research may be important in terms of planning the planting of greenery areas and spatial development of the Lublin.

scholarly journals Extraction of Three-Dimensional Information of Biological Membranous Tissue with Scanning Confocal Infrared Laser Microscope Tomography

2013 ◽  
Vol 19 (S5) ◽  
pp. 194-197 ◽  
Author(s):  
Soonwook Kwon ◽  
Se-Bum Choi ◽  
Min Gyu Park ◽  
Hyunung Yu ◽  
Seung-Woo Suh ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Near Infrared ◽  
Materials Science ◽  
Three Dimensional ◽  
Biological Tissues ◽  
Rat Aorta ◽  
Confocal Laser Scanning Microscope ◽  
Confocal Laser ◽  
Mechanical Cutting

AbstractThe “LEXT” confocal laser scanning microscope has been used for the three-dimensional (3D) imaging of the surface of specimens, especially in materials science fields, by the penetration of near-infrared (NIR) light without mechanical cutting, deposition, or other specimen pretreatment. Noninvasive investigation of various biological tissues such as human spinal dura mater, rat aorta, and cornea without the dehydration process was successfully carried out with the “LEXT,” in order to access both surface and internal topographic images of the biological structures at a good status of the wet tissue such asin vivo, especially in measuring tissue thickness. The confocal NIR laser microscopy offers the viable means to visualize tissue architecture and its thickness in microdomain to integrate 3D images efficiently. We believe that the “LEXT” has a good application for biological researchers to study biomaterials, and it would be useful as a diagnostic tool in the near future.

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