Automated Detection of Three-Dimensional Cars in Mobile Laser Scanning Point Clouds Using DBM-Hough-Forests

High Accuracy Driving Maps (HADMs) are the core component of Intelligent Drive Assistant Systems (IDAS), which can effectively reduce the traffic accidents due to human error and provide more comfortable driving experiences. Vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. This paper proposes a novel method to extract road features (e.g., road surfaces, road boundaries, road markings, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, vehicles and so on) for HADMs in highway environment. Quantitative evaluations show that the proposed algorithm attains an average precision and recall in terms of 90.6% and 91.2% in extracting road features. Results demonstrate the efficiencies and feasibilities of the proposed method for extraction of road features for HADMs.

Download Full-text

VISUALIZATION OF THE CONSTRUCTION OF ANCIENT ROMAN BUILDINGS IN OSTIA USING POINT CLOUD DATA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w3-345-2017 ◽

2017 ◽

Vol XLII-2/W3 ◽

pp. 345-352

Author(s):

Y. Hori ◽

T. Ogawa

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Feature Matching ◽

Three Dimensional ◽

Point Clouds ◽

Final Report ◽

Point Cloud Data ◽

Cloud Data ◽

Coverage Accuracy ◽

New Research

The implementation of laser scanning in the field of archaeology provides us with an entirely new dimension in research and surveying. It allows us to digitally recreate individual objects, or entire cities, using millions of three-dimensional points grouped together in what is referred to as "point clouds". In addition, the visualization of the point cloud data, which can be used in the final report by archaeologists and architects, should usually be produced as a JPG or TIFF file. Not only the visualization of point cloud data, but also re-examination of older data and new survey of the construction of Roman building applying remote-sensing technology for precise and detailed measurements afford new information that may lead to revising drawings of ancient buildings which had been adduced as evidence without any consideration of a degree of accuracy, and finally can provide new research of ancient buildings. We used laser scanners at fields because of its speed, comprehensive coverage, accuracy and flexibility of data manipulation. Therefore, we “skipped” many of post-processing and focused on the images created from the meta-data simply aligned using a tool which extended automatic feature-matching algorithm and a popular renderer that can provide graphic results.

Download Full-text

Weighing trees with lasers: advances, challenges and opportunities

Interface Focus ◽

10.1098/rsfs.2017.0048 ◽

2018 ◽

Vol 8 (2) ◽

pp. 20170048 ◽

Cited By ~ 44

Author(s):

M. I. Disney ◽

M. Boni Vicari ◽

A. Burt ◽

K. Calders ◽

S. L. Lewis ◽

...

Keyword(s):

Laser Scanning ◽

Large Scale ◽

Three Dimensional ◽

Point Clouds ◽

3D Models ◽

Tree Form ◽

Form And Function ◽

Challenges And Opportunities ◽

And Function ◽

Non Destructive

Terrestrial laser scanning (TLS) is providing exciting new ways to quantify tree and forest structure, particularly above-ground biomass (AGB). We show how TLS can address some of the key uncertainties and limitations of current approaches to estimating AGB based on empirical allometric scaling equations (ASEs) that underpin all large-scale estimates of AGB. TLS provides extremely detailed non-destructive measurements of tree form independent of tree size and shape. We show examples of three-dimensional (3D) TLS measurements from various tropical and temperate forests and describe how the resulting TLS point clouds can be used to produce quantitative 3D models of branch and trunk size, shape and distribution. These models can drastically improve estimates of AGB, provide new, improved large-scale ASEs, and deliver insights into a range of fundamental tree properties related to structure. Large quantities of detailed measurements of individual 3D tree structure also have the potential to open new and exciting avenues of research in areas where difficulties of measurement have until now prevented statistical approaches to detecting and understanding underlying patterns of scaling, form and function. We discuss these opportunities and some of the challenges that remain to be overcome to enable wider adoption of TLS methods.

Download Full-text

A new drone laser scanning benchmark dataset for characterization of single-tree and forest biophysical properties

10.5194/egusphere-egu21-10677 ◽

2021 ◽

Author(s):

Puliti Stefano ◽

Grant D. Pears ◽

Michael S. Watt ◽

Edward Mitchard ◽

Iain McNicol ◽

...

Keyword(s):

Boreal Forests ◽

Laser Scanning ◽

Method Development ◽

Three Dimensional ◽

Point Clouds ◽

Benchmark Dataset ◽

Validation Dataset ◽

Tree Structures ◽

Single Tree ◽

Individual Trees

<p>Survey-grade drone laser scanners suitable for unmanned aerial vehicles (UAV-LS) allow the efficient collection of finely detailed three-dimensional information of tree structures. This data type allows forests to be resolved into discrete individual trees and has shown promising results in providing accurate in-situ observations of key forestry variables. New and improved approaches for analyzing UAV-LS point clouds have to be developed to transform the vast amounts of data from UAV-LS into actionable insights and decision support. Many different studies have explored various methods for automating single tree detection, segmentation, parsing into different tree components, and measurement of biophysical variables (e.g., diameter at breast height). Despite the considerable efforts dedicated to developing automated ways to process UAV-LS data into useful data, current methods tend to be tailored to small datasets, and it remains challenging to evaluate the performance of different algorithms based on a consistent validation dataset. To fill this knowledge gap and to further advance our ability to measure forests from UAV-LS data, we present a new benchmarking dataset. This data is composed of manually labelled UAV-LS data acquired a number of continents and biomes which span tropical to boreal forests. The UAV-LS data was collected exclusively used survey-grade sensors such as the Riegl VUX and mini-VUX series which are characterized by a point density in the range&#160;1 &#8211; 10 k points m<sup>2</sup>. Currently, such data represent the state-of-the-art in aerial laser scanning data. The benchmark data consists of a library of single-tree point clouds, aggregated to sample plots, with each point classified as either stem, branch, or leaves. With the objective of releasing such a benchmark dataset as a public asset, in the future, researchers will be able to leverage such pre-existing labelled trees for developing new methods to measure forests from UAV-LS data. The availability of benchmarking datasets represents an important driver for enabling the development of robust and accurate methods. Such a benchmarking dataset will also be important for a consistent comparison of existing or future algorithms which will guide future method development.</p>

Download Full-text

Toward a Novel Laser-Based Approach for Estimating Snow Interception

Remote Sensing ◽

10.3390/rs12071146 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1146 ◽

Cited By ~ 1

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.

Download Full-text

Mobile Laser Scanning Data for the Evaluation of Pavement Surface Distress

Remote Sensing ◽

10.3390/rs12060942 ◽

2020 ◽

Vol 12 (6) ◽

pp. 942 ◽

Cited By ~ 3

Author(s):

Maria Rosaria De Blasiis ◽

Alessandro Di Benedetto ◽

Margherita Fiani

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Road Traffic ◽

Single Point ◽

Three Dimensional ◽

Point Clouds ◽

Road Surface ◽

Important Indicator ◽

The Road ◽

Laser Systems

The surface conditions of road pavements, including the occurrence and severity of distresses present on the surface, are an important indicator of pavement performance. Periodic monitoring and condition assessment is an essential requirement for the safety of vehicles moving on that road and the wellbeing of people. The traditional characterization of the different types of distress often involves complex activities, sometimes inefficient and risky, as they interfere with road traffic. The mobile laser systems (MLS) are now widely used to acquire detailed information about the road surface in terms of a three-dimensional point cloud. Despite its increasing use, there are still no standards for the acquisition and processing of the data collected. The aim of our work was to develop a procedure for processing the data acquired by MLS, in order to identify the localized degradations that mostly affect safety. We have studied the data flow and implemented several processing algorithms to identify and quantify a few types of distresses, namely potholes and swells/shoves, starting from very dense point clouds. We have implemented data processing in four steps: (i) editing of the point cloud to extract only the points belonging to the road surface, (ii) determination of the road roughness as deviation in height of every single point of the cloud with respect to the modeled road surface, (iii) segmentation of the distress (iv) computation of the main geometric parameters of the distress in order to classify it by severity levels. The results obtained by the proposed methodology are promising. The procedures implemented have made it possible to correctly segmented and identify the types of distress to be analyzed, in accordance with the on-site inspections. The tests carried out have shown that the choice of the values of some parameters to give as input to the software is not trivial: the choice of some of them is based on considerations related to the nature of the data, for others, it derives from the distress to be segmented. Due to the different possible configurations of the various distresses it is better to choose these parameters according to the boundary conditions and not to impose default values. The test involved a 100-m long urban road segment, the surface of which was measured with an MLS installed on a vehicle that traveled the road at 10 km/h.

Download Full-text

Assessing Understory Complexity in Beech-dominated Forests (Fagus sylvatica L.) in Central Europe—From Managed to Primary Forests

Sensors ◽

10.3390/s19071684 ◽

2019 ◽

Vol 19 (7) ◽

pp. 1684 ◽

Cited By ~ 9

Author(s):

Katharina Willim ◽

Melissa Stiers ◽

Peter Annighöfer ◽

Christian Ammer ◽

Martin Ehbrecht ◽

...

Keyword(s):

National Parks ◽

Fagus Sylvatica ◽

Laser Scanning ◽

Three Dimensional ◽

European Beech ◽

Point Clouds ◽

Tree Regeneration ◽

Understory Vegetation ◽

Fagus Sylvatica L ◽

Primary Forests

Understory vegetation influences several ecosystem services and functions of European beech (Fagus sylvatica L.) forests. Despite this knowledge on the importance of understory vegetation, it is still difficult to measure its three-dimensional characteristics in a quantitative manner. With the recent advancements in terrestrial laser scanning (TLS), we now have the means to analyze detailed spatial patterns of forests. Here, we present a new measure to quantify understory complexity. We tested the approach for different management types, ranging from traditionally and alternatively managed forests and national parks in Germany to primary forests of Eastern Europe and the Ukraine, as well as on an inventory site with more detailed understory reference data. The understory complexity index (UCI) was derived from point clouds from single scans and tested for its relationship with forest management and conventional inventory data. Our results show that advanced tree regeneration is a strong driver of the UCI. Furthermore, the newly developed index successfully measured understory complexity of differently managed beech stands and was able to distinguish scanning positions located on and away from skid-trails in managed stands. The approach enables a deeper understanding of the complexity of understory structures of forests and their drivers and dependents.

Download Full-text

INTEGRATION OF GEODATA IN DOCUMENTING CASTLE RUINS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b3-345-2016 ◽

2016 ◽

Vol XLI-B3 ◽

pp. 345-349

Author(s):

P. Delis ◽

M. Wojtkowska ◽

P. Nerc ◽

I. Ewiak ◽

A. Lada

Keyword(s):

Laser Scanning ◽

Three Dimensional ◽

Digital Camera ◽

Terrestrial Laser Scanning ◽

Point Clouds ◽

3D Models ◽

Digital Imagery ◽

Historical Structures ◽

Three Dimensional Models ◽

Different Sources

Textured three dimensional models are currently the one of the standard methods of representing the results of photogrammetric works. A realistic 3D model combines the geometrical relations between the structure’s elements with realistic textures of each of its elements. Data used to create 3D models of structures can be derived from many different sources. The most commonly used tool for documentation purposes, is a digital camera and nowadays terrestrial laser scanning (TLS). Integration of data acquired from different sources allows modelling and visualization of 3D models historical structures. Additional aspect of data integration is possibility of complementing of missing points for example in point clouds. The paper shows the possibility of integrating data from terrestrial laser scanning with digital imagery and an analysis of the accuracy of the presented methods. The paper describes results obtained from raw data consisting of a point cloud measured using terrestrial laser scanning acquired from a Leica ScanStation2 and digital imagery taken using a Kodak DCS Pro 14N camera. The studied structure is the ruins of the Ilza castle in Poland.

Download Full-text

RECORDING AND MODELLING OF MONUMENTS' INTERIOR SPACE USING RANGE AND OPTICAL SENSORS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b5-939-2016 ◽

2016 ◽

Vol XLI-B5 ◽

pp. 939-944

Author(s):

Charalampos Georgiadis ◽

Petros Patias ◽

Vasilios Tsioukas

Keyword(s):

Optical Sensors ◽

Laser Scanning ◽

Three Dimensional ◽

Point Clouds ◽

Research Field ◽

Interior Space ◽

Range Camera ◽

Highly Active ◽

Fixed Base ◽

Active Research

Three dimensional modelling of artefacts and building interiors is a highly active research field in our days. Several techniques are being utilized to perform such a task, spanning from traditional surveying techniques and photogrammetry to structured light scanners, laser scanners and so on. New technological advancements in both hardware and software create new recording techniques, tools and approaches. In this paper we present a new recording and modelling approach based on the SwissRanger SR4000 range camera coupled with a Canon 400D dSLR camera. The hardware component of our approach consists of a fixed base, which encloses the range and SLR cameras. The two sensors are fully calibrated and registered to each other thus we were able to produce colorized point clouds acquired from the range camera. In this paper we present the initial design and calibration of the system along with experimental data regarding the accuracy of the proposed approach. We are also providing results regarding the modelling of interior spaces and artefacts accompanied with accuracy tests from other modelling approaches based on photogrammetry and laser scanning.

Download Full-text