THE INFLUENCE OF FLIGHT PLANNING AND CAMERA ORIENTATION IN UAVs PHOTOGRAMMETRY. A TEST IN THE AREA OF ROCCA SAN SILVESTRO (LI), TUSCANY

The purpose of this paper is to discuss how much the phases of flight planning and the setting of the camera orientation can affect a UAVs photogrammetric survey. The test site chosen for these evaluations was the Rocca of San Silvestro, a medieval monumental castle near Livorno, Tuscany (Italy). During the fieldwork, different sets of data have been acquired using different parameters for the camera orientation and for the set up of flight plans. Acquisition with both nadiral and oblique orientation of the camera have been performed, as well as flights with different direction of the flight lines (related with the shape of the object of the survey). The different datasets were then processed in several blocks using Pix4D software and the results of the processing were analysed and compared. Our aim was to evaluate how much the parameters described above can affect the generation of the final products of the survey, in particular the product chosen for this evaluation was the point cloud.

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Handheld Laser Scanner Research

Geodesy and Cartography ◽

10.22389/0016-7126-2019-952-10-47-54 ◽

2019 ◽

Vol 952 (10) ◽

pp. 47-54

Author(s):

A.V. Komissarov ◽

A.V. Remizov ◽

M.M. Shlyakhova ◽

K.K. Yambaev

Keyword(s):

Point Cloud ◽

Three Dimensional ◽

Laser Scanner ◽

Test Site ◽

Optical Systems ◽

Advantages And Disadvantages ◽

Site Survey ◽

Laser Scanners ◽

Three Dimensional Models ◽

The Stability

The authors consider hand-held laser scanners, as a new photogrammetric tool for obtaining three-dimensional models of objects. The principle of their work and the newest optical systems based on various sensors measuring the depth of space are described in detail. The method of simultaneous navigation and mapping (SLAM) used for combining single scans into point cloud is outlined. The formulated tasks and methods for performing studies of the DotProduct (USA) hand-held laser scanner DPI?8X based on a test site survey are presented. The accuracy requirements for determining the coordinates of polygon points are given. The essence of the performed experimental research of the DPI?8X scanner is described, including scanning of a test object at various scanner distances, shooting a test polygon from various scanner positions and building point cloud, repeatedly shooting the same area of the polygon to check the stability of the scanner. The data on the assessment of accuracy and analysis of research results are given. Fields of applying hand-held laser scanners, their advantages and disadvantages are identified.

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Pilot provision of EARLINET/ACTRIS lidar profiles to CAMS

10.5194/egusphere-egu21-14943 ◽

2021 ◽

Author(s):

Lucia Mona ◽

Giuseppe D'Amico ◽

Simone Gagliardi ◽

Francesco Amato ◽

Aldo Amodeo ◽

...

Keyword(s):

Real Time ◽

Test Site ◽

Atmospheric Composition ◽

Successful Implementation ◽

European Continent ◽

Aerosol Optical Property ◽

Controlled Processing ◽

Data Provision ◽

Systematic Solution ◽

Set Up

In December 2019, a contract between CNR and ECMWF was signed for a pilot ACTRIS/EARLINET data provision to the Copernicus Atmosphere Monitoring Service (CAMS). Such pilot contract (CAMS21b) aims to put in place a first data provision for a set of selected stations and it will demonstrate the feasibility of fully traceable and quality-controlled data provision for the whole network.In CAMS21b, the main effort is devoted to design, test and set up the provision of quality-controlled ACTRIS/EARLINET products in Real Real Time (RRT) and/or Near Real Time (NRT) to CAMS. The activities are focused on the automatic centralized data processing and data provision, ensuring the full traceability of the products from the data acquisition level up to the final quality-controlled data level. Most of the activities are done at ARES, the EARLINET/ACTRIS data center node at CNR, for assuring the centralized, harmonized and quality-controlled processing in compliance with FAIR principles.New modules and submodules of the ACTRIS/EARLINET Single Calculus Chain (SCC) as well as optimized algorithms for cloud screening have been designed. Additional procedures were implemented for improving the quality of the data provided in NRT, but also for the quality control of the Level 2 products which are delivered with a time delay.The release of a new version of SCC and of QC procedure is planned for mid-February.The data provision started in October 2020 at the test site of Potenza. A system has been set up for measurement reporting and monitoring of KPIs (Key Performance Indicators). After 3 months of measurements, the overall data provision system showed no critical points.In January 2021, the provision started for a group of 9 stations which are seen as representative for the whole network in terms of instrumental capability, but also ensuring a good geographical coverage of the European continent.In order to accommodate also measurements from non-continuous operation systems, a measurement schedule has been set up, compromising between the need of a large number of measurements and costs/efforts at each station. The measurement schedule has been designed through a representativeness study and foresees 6 slots of measurements per week, 3 in daytime and 3 in nighttime conditions.The successful implementation of the pilot allows the provision of aerosol optical property profiles to the CAMS services. from a set of observational sites distributed over the different European regions. These profiles is expected to be of interest for the assimilation, near real time evaluation and re-analysis evaluation of several CAMS products, including the aerosol load over Europe for air quality issues, atmospheric composition, climate forcing and solar and UV products. This allows for having a systematic solution for looking into specific events as they develop (e.g. the dust plume that you investigated earlier this month or the Californian fires in September), supporting or contradicting model forecasts. This pilot is the first provision of aerosol profiles from a high-quality ground-based network in NRT for this kind of applications. It is expected that these efforts will be continued in the next phase of CAMS/Copernicus (2021-2027).

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Railway Ballast Monitoring by Gpr: A Test Site Investigation

Remote Sensing ◽

10.3390/rs11202381 ◽

2019 ◽

Vol 11 (20) ◽

pp. 2381 ◽

Cited By ~ 6

Author(s):

Bianchini Ciampoli ◽

Calvi ◽

D’Amico

Keyword(s):

Asset Management ◽

Construction Materials ◽

Site Investigation ◽

Horn Antenna ◽

Test Site ◽

Electromagnetic Response ◽

Actual Condition ◽

Railway Ballast ◽

Set Up ◽

Ground Penetrating

Effective maintenance of railways requires a comprehensive assessment of the actual condition of the construction materials involved. In this regard, Ground-Penetrating Radar (GPR) stands as a viable alternative to the invasive and time-consuming traditional techniques for the inspection of these infrastructures. This work reports the experimental activities carried out on a test-site area within a railway depot in Rome, Italy. To this purpose, a 30 m-long railway section was divided into 10 sub-sections reproducing different various physical and structural conditions of the track-bed. In more detail, combinations of varying scenarios of fragmentation and fouling of the ballast were reproduced. The set-up was then investigated using different multi-frequency GPR horn antenna systems. The effects of the different physical conditions of ballast on the electromagnetic response of the material were analysed for each scenario using time- and frequency-domain signal processing techniques. Parallel to this, modelling was provided to estimate fouling content. Interpretation of results has proven the viability of the GPR method in detecting signs of decay at the network level, thereby proving this technique to be worthy of implementation in asset management systems.

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A new in situ sensor for large-scale snow-cover monitoring

Annals of Glaciology ◽

10.3189/172756404781814933 ◽

2004 ◽

Vol 38 ◽

pp. 273-278 ◽

Cited By ~ 20

Author(s):

Manfred Stähli ◽

Markus Stacheder ◽

David Gustafsson ◽

Stefan Schlaeger ◽

Martin Schneebeli ◽

...

Keyword(s):

Large Scale ◽

Snow Water Equivalent ◽

Soil Surface ◽

Test Site ◽

Liquid Water Content ◽

Flat Band ◽

Snow Layer ◽

In Situ Sensor ◽

Set Up

AbstractA new in situ sensor for the simultaneous measurement of snow water equivalent, snow density and liquid-water content is presented in this paper. The system consists of radio frequency transmission lines of up to 25 m length cast in a flat PVC band, which can be set up either horizontally to monitor single snow-layer properties or sloping from a mast to the soil surface to determine vertical snowpack properties. The dielectric coefficient along the flat-band cable is measured with a time-domain reflectometer at high frequencies, and with a low-frequency impedance analyzer. The performance of the sensor system was tested during two winter seasons (2001–03) at the high-alpine test site Weissfluhjoch, Davos, Switzerland. The cable suspension and set-up of the sloping cable was shown to be critical with regard to stability and the formation of unwanted air gaps along the cable. Overall, the sensing system proved quite robust and produced results in agreement with manual snowpack observations.

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An Automatic Designing Method for Apparel

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.88-89.175 ◽

2011 ◽

Vol 88-89 ◽

pp. 175-179

Author(s):

Xiao Gang Wang ◽

Qin Zheng ◽

Xin Zhan Li

Keyword(s):

Point Cloud ◽

Science Research ◽

Mathematic Model ◽

New Method ◽

Scanning System ◽

Body Scanning ◽

3D Shape ◽

Vertical Sections ◽

Set Up ◽

Designing Method

In this article we discuss a new method for describing the 3D shape of woman warm jacket and set up its mathematic model, which is by dint of body scanning technology. Telmat scanning system scanned samples. The scanning point cloud were analyzed in horizontal and vertical sections. Outlines of vertical sections were described and mathematic models were set up. The result helped to prognosticate the shape of woman warm jacket. A new describing method for 3D shape is discussed. And it opens our mind to utilize body-scanning technology for deeper science research.

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ROAD SURFACE DETECTION FROM MOBILE LIDAR DATA

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-5-95-2018 ◽

2018 ◽

Vol IV-5 ◽

pp. 95-101 ◽

Cited By ~ 1

Author(s):

M. Yadav ◽

B. Lohani ◽

A. K. Singh

Keyword(s):

Point Cloud ◽

Three Dimensional ◽

Test Site ◽

Road Surface ◽

Lidar Data ◽

Rural Roads ◽

The Road ◽

Surface Detection ◽

Rural Road ◽

Data Points

Abstract. The accurate three-dimensional road surface information is highly useful for health assessment and maintenance of roads. It is basic information for further analysis in several applications including road surface settlement, pavement condition assessment and slope collapse. Mobile LiDAR system (MLS) is frequently used now a days to collect detail road surface and its surrounding information in terms three-dimensional (3D) point cloud. Extraction of road surface from volumetric point cloud data is still in infancy stage because of heavy data processing requirement and the complexity in the road environment. The extraction of roads especially rural road, where road-curb is not present is very tedious job especially in Indian roadway settings. Only a few studies are available, and none for Indian roads, in the literature for rural road detection. The limitations of existing studies are in terms of their lower accuracy, very slow speed of data processing and detection of other objects having similar characteristics as the road surface. A fast and accurate method is proposed for LiDAR data points of road surface detection, keeping in mind the essence of road surface extraction especially for Indian rural roads. The Mobile LiDAR data in XYZI format is used as input in the proposed method. First square gridding is performed and ground points are roughly extracted. Then planar surface detection using mathematical framework of principal component analysis (PCA) is performed and further road surface points are detected using similarity in intensity and height difference of road surface pointe in their neighbourhood.A case study was performed on the MLS data points captured along wide-street (two-lane road without curb) of 156m length along rural roadway site in the outskirt of Bengaluru city (South-West of India). The proposed algorithm was implemented on the MLS data of test site and its performance was evaluated it terms of recall, precision and overall accuracy that were 95.27%, 98.85% and 94.23%, respectively. The algorithm was found computationally time efficient. A 7.6 million MLS data points of size 27.1MB from test site were processed in 24 minutes using the available computational resources. The proposed method is found to work even for worst case scenarios, i.e., complex road environments and rural roads, where road boundary is not clear and generally merged with road-side features.

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A NEW METHOD FOR DETERMINING THE DEFORMATION MONITORABLE INDICATOR OF POINT CLOUD

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsannals-iii-7-157-2016 ◽

2016 ◽

Vol III-7 ◽

pp. 157-164

Author(s):

W. Xuan ◽

X. H. Hua ◽

W. N. Qiu ◽

J. G. Zou ◽

X. J. Chen

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Terrestrial Laser Scanning ◽

Sampling Interval ◽

Deformation Monitoring ◽

Error Space ◽

Set Up ◽

The Relationship ◽

Error Ellipsoid ◽

Actual Point

With the continuous development of the terrestrial laser scanning (TLS) technique, the precision of the laser scanning has been improved which makes it possible that TLS could be used for high-precision deformation monitoring. A deformation monitorable indicator (DMI) should be determined to distinguish the deformation from the error of point cloud and plays an important role in the deformation monitoring using TLS. After the DMI determined, a scheme of the deformation monitoring case could be planned to choose a suitable instrument, set up a suitable distance and sampling interval. In this paper, the point error space and the point cloud error space are modelled firstly based on the point error ellipsoid. Secondly, the actual point error is derived by the relationship between the actual point cloud error space and the point error space. Then, the DMI is determined using the actual point error. Finally, two sets of experiments is carried out and the feasibility of the DMI is proved.

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UNMANNED AERIAL VEHICLE LASER SCANNING FOR EROSION MONITORING IN ALPINE GRASSLAND

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-2-w5-405-2019 ◽

2019 ◽

Vol IV-2/W5 ◽

pp. 405-412 ◽

Cited By ~ 2

Author(s):

A. Mayr ◽

M. Bremer ◽

M. Rutzinger ◽

C. Geitner

Keyword(s):

Unmanned Aerial Vehicle ◽

Point Cloud ◽

Laser Scanning ◽

Test Site ◽

Satellite System ◽

Alpine Grassland ◽

Proof Of Concept ◽

Aerial Vehicle ◽

Geomorphological Changes ◽

Global Navigation Satellite

Abstract. With this contribution we assess the potential of unmanned aerial vehicle (UAV) based laser scanning for monitoring shallow erosion in Alpine grassland. A 3D point cloud has been acquired by unmanned aerial vehicle laser scanning (ULS) at a test site in the subalpine/alpine elevation zone of the Dolomites (South Tyrol, Italy). To assess its accuracy, this point cloud is compared with (i) differential global navigation satellite system (GNSS) reference measurements and (ii) a terrestrial laser scanning (TLS) point cloud. The ULS point cloud and an airborne laser scanning (ALS) point cloud are rasterized into digital surface models (DSMs) and, as a proof-of-concept for erosion quantification, we calculate the elevation difference between the ULS DSM from 2018 and the ALS DSM from 2010. For contiguous spatial objects of elevation change, the volumetric difference is calculated and a land cover class (bare earth, grassland, trees), derived from the ULS reflectance and RGB colour, is assigned to each change object. In this test, the accuracy and density of the ALS point cloud is mainly limiting the detection of geomorphological changes. Nevertheless, the plausibility of the results is confirmed by geomorphological interpretation and documentation in the field. A total eroded volume of 672&thinsp;m3 is estimated for the test site (48&thinsp;ha). Such volumetric estimates of erosion over multiple years are a key information for improving sustainable soil management. Based on this proof-of-concept and the accuracy analysis, we conclude that repeated ULS campaigns are a well-suited tool for erosion monitoring in Alpine grassland.

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Highly Accurate Pose Estimation as Reference for Autonomous Vehicles in Near-Range Scenarios

10.20944/preprints202112.0206.v1 ◽

2021 ◽

Author(s):

Ursula Kälin ◽

Louis Staffa ◽

David Eugen Grimm ◽

Axel Wendt

Keyword(s):

Autonomous Vehicles ◽

Tracking System ◽

Autonomous Driving ◽

Test Site ◽

Moving Vehicle ◽

System Interoperability ◽

Set Up ◽

Reference Environment ◽

Onboard System ◽

Detection And Localization

To validate the accuracy and reliability of onboard sensors for object detection and localization in driver assistance, as well as autonomous driving applications under realistic conditions (indoors and outdoors), a novel tracking system is presented. This tracking system is developed to determine the position and orientation of a slow-moving vehicle (e.g. car during parking maneuvers), independent of the onboard sensors, during test maneuvers within a reference environment. One requirement is a 6 degree of freedom (DoF) pose with a position uncertainty below 5 mm (3σ), an orientation uncertainty below 0.3° (3σ) at a frequency higher than 20 Hz, and a latency smaller than 500 ms. To compare the results from the reference system with the vehicle’s onboard system, a synchronization via Precision Time Protocol (PTP) and a system interoperability to Robot Operating System (ROS) is implemented. The developed system combines motion capture cameras mounted in a 360° panorama view set-up on the vehicle with robotic total stations. A point cloud of the test site serves as a digital twin of the environment, in which the movement of the vehicle is simulated. Results have shown that the fused measurements of these sensors complement each other, so that the accuracy requirements for the 6 DoF pose can be met, while allowing a flexible installation in different environments.

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HIGH ACCURATE POINTWISE (GEO-)REFERENCING OF A K-TLS BASED MULTI-SENSOR-SYSTEM

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-4-81-2018 ◽

2018 ◽

Vol IV-4 ◽

pp. 81-88 ◽

Cited By ~ 4

Author(s):

J. Hartmann ◽

P. Trusheim ◽

H. Alkhatib ◽

J.-A. Paffenholz ◽

D. Diener ◽

...

Keyword(s):

Kalman Filter ◽

Point Cloud ◽

Laser Scanning ◽

Laser Scanner ◽

High Accuracy ◽

Laser Tracker ◽

3D Point Cloud ◽

Filter Model ◽

Measurement Frequency ◽

Set Up

Abstract. In recent years, the requirements in the industrial production, e.g., ships or planes, have been increased. In addition to high accuracy requirements with a standard deviation of 1mm, an efficient 3D object capturing is required. In terms of efficiency, kinematic laser scanning (k-TLS) has been proven its worth in recent years. It can be seen as an alternative to the well established static terrestrial laser scanning (s-TLS). However, current k-TLS based multi-sensor-systems (MSS) are not able to fulfil the high accuracy requirements. Thus, a new k-TLS based MSS and suitable processing algorithms have to be developed. In this contribution a new k-TLS based MSS will be presented. The main focus will lie on the (geo-)referencing process. Due to the high accuracy requirements, a novel procedure of external (geo-)referencing is used here. Hereby, a mobile platform, which is equipped with a profile laser scanner, will be tracked by a laser tracker. Due to the fact that the measurement frequency of the laser scanner is significantly higher than the measurement frequency of the laser tracker a direct point wise (geo-)referencing is not possible. To enable this a Kalman filter model is set up and implemented. In the prediction step each point is shifted according to the determined velocity of the platform. Because of the nonlinear motion of the platform an iterative extended Kalman filter (iEKF) is used here. Furthermore, test measurements of a panel with the k-TLS based MSS and with s-TLS were carried out. To compare the results, the 3D distances with the M3C2-algorithm between the s-TLS 3D point cloud and the k-TLS 3D point cloud are estimated. It can be noted, that the usage of a system model for the (geo-)referencing is essential. The results show that the mentioned high accuracy requirements have been achieved.

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