scholarly journals Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments

2021 ◽  
Vol 10 (10) ◽  
pp. 665
Author(s):  
Xukai Zhang ◽  
Xuelian Meng ◽  
Chunyan Li ◽  
Nan Shang ◽  
Jiaze Wang ◽  
...  
Keyword(s):  
Correction Factor ◽  
Laser Scanning ◽  
Accuracy Assessment ◽  
Correction Method ◽  
Terrain Correction ◽  
Surface Model ◽  
Coastal Environments ◽  
Terrestrial Lidar ◽  
Dense Vegetation ◽  
Micro Topography

Terrestrial Light Detection And Ranging (LiDAR), also referred to as terrestrial laser scanning (TLS), has gained increasing popularity in terms of providing highly detailed micro-topography with millimetric measurement precision and accuracy. However, accurately depicting terrain under dense vegetation remains a challenge due to the blocking of signal and the lack of nearby ground. Without dependence on historical data, this research proposes a novel and rapid solution to map densely vegetated coastal environments by integrating terrestrial LiDAR with GPS surveys. To verify and improve the application of terrestrial LiDAR in coastal dense-vegetation areas, we set up eleven scans of terrestrial LiDAR in October 2015 along a sand berm with vegetation planted in Plaquemines Parish of Louisiana. At the same time, 2634 GPS points were collected for the accuracy assessment of terrain mapping and terrain correction. Object-oriented classification was applied to classify the whole berm into tall vegetation, low vegetation and bare ground, with an overall accuracy of 92.7% and a kappa value of 0.89. Based on the classification results, terrain correction was conducted for the tall-vegetation and low-vegetation areas, respectively. An adaptive correction factor was applied to the tall-vegetation area, and the 95th percentile error was calculated as the correction factor from the surface model instead of the terrain model for the low-vegetation area. The terrain correction method successfully reduced the mean error from 0.407 m to −0.068 m (RMSE errors from 0.425 m to 0.146 m) in low vegetation and from 0.993 m to −0.098 m (RMSE from 1.070 m to 0.144 m) in tall vegetation.

scholarly journals Accuracy assessment of TanDEM-X IDEM using airborne LiDAR on the area of Poland

2017 ◽  
Vol 66 (1) ◽  
pp. 137-148 ◽  
Author(s):  
Małgorzata Woroszkiewicz ◽  
Ireneusz Ewiak ◽  
Paulina Lulkowska
Keyword(s):  
Digital Elevation Model ◽  
Laser Scanning ◽  
Accuracy Assessment ◽  
Shuttle Radar Topography Mission ◽  
Reference Points ◽  
Airborne Lidar ◽  
Surface Model ◽  
Digital Elevation ◽  
Elevation Model ◽  
German Aerospace

Abstract The TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) mission launched in 2010 is another programme – after the Shuttle Radar Topography Mission (SRTM) in 2000 – that uses space-borne radar interferometry to build a global digital surface model. This article presents the accuracy assessment of the TanDEM-X intermediate Digital Elevation Model (IDEM) provided by the German Aerospace Center (DLR) under the project “Accuracy assessment of a Digital Elevation Model based on TanDEM-X data” for the southwestern territory of Poland. The study area included: open terrain, urban terrain and forested terrain. Based on a set of 17,498 reference points acquired by airborne laser scanning, the mean errors of average heights and standard deviations were calculated for areas with a terrain slope below 2 degrees, between 2 and 6 degrees and above 6 degrees. The absolute accuracy of the IDEM data for the analysed area, expressed as a root mean square error (Total RMSE), was 0.77 m.

scholarly journals ACCURACY ASSESSMENT OF COASTAL TOPOGRAPHY DERIVED FROM UAV IMAGES

2016 ◽  
Vol XLI-B1 ◽  
pp. 1127-1134 ◽  
Author(s):  
N. Long ◽  
B. Millescamps ◽  
F. Pouget ◽  
A. Dumon ◽  
N. Lachaussée ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Laser Scanning ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Temporal Frequency ◽  
Digital Camera ◽  
Image Resolution ◽  
Homogeneous Distribution ◽  
Surface Model ◽  
Small Water

To monitor coastal environments, Unmanned Aerial Vehicle (UAV) is a low-cost and easy to use solution to enable data acquisition with high temporal frequency and spatial resolution. Compared to Light Detection And Ranging (LiDAR) or Terrestrial Laser Scanning (TLS), this solution produces Digital Surface Model (DSM) with a similar accuracy. To evaluate the DSM accuracy on a coastal environment, a campaign was carried out with a flying wing (eBee) combined with a digital camera. Using the Photoscan software and the photogrammetry process (Structure From Motion algorithm), a DSM and an orthomosaic were produced. Compared to GNSS surveys, the DSM accuracy is estimated. Two parameters are tested: the influence of the methodology (number and distribution of Ground Control Points, GCPs) and the influence of spatial image resolution (4.6 cm vs 2 cm). The results show that this solution is able to reproduce the topography of a coastal area with a high vertical accuracy (< 10 cm). The georeferencing of the DSM require a homogeneous distribution and a large number of GCPs. The accuracy is correlated with the number of GCPs (use 19 GCPs instead of 10 allows to reduce the difference of 4 cm); the required accuracy should be dependant of the research problematic. Last, in this particular environment, the presence of very small water surfaces on the sand bank does not allow to improve the accuracy when the spatial resolution of images is decreased.

scholarly journals ACCURACY ASSESSMENT OF COASTAL TOPOGRAPHY DERIVED FROM UAV IMAGES

2016 ◽  
Vol XLI-B1 ◽  
pp. 1127-1134 ◽  
Author(s):  
N. Long ◽  
B. Millescamps ◽  
F. Pouget ◽  
A. Dumon ◽  
N. Lachaussée ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Laser Scanning ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Temporal Frequency ◽  
Digital Camera ◽  
Image Resolution ◽  
Homogeneous Distribution ◽  
Surface Model ◽  
Small Water

To monitor coastal environments, Unmanned Aerial Vehicle (UAV) is a low-cost and easy to use solution to enable data acquisition with high temporal frequency and spatial resolution. Compared to Light Detection And Ranging (LiDAR) or Terrestrial Laser Scanning (TLS), this solution produces Digital Surface Model (DSM) with a similar accuracy. To evaluate the DSM accuracy on a coastal environment, a campaign was carried out with a flying wing (eBee) combined with a digital camera. Using the Photoscan software and the photogrammetry process (Structure From Motion algorithm), a DSM and an orthomosaic were produced. Compared to GNSS surveys, the DSM accuracy is estimated. Two parameters are tested: the influence of the methodology (number and distribution of Ground Control Points, GCPs) and the influence of spatial image resolution (4.6 cm vs 2 cm). The results show that this solution is able to reproduce the topography of a coastal area with a high vertical accuracy (< 10 cm). The georeferencing of the DSM require a homogeneous distribution and a large number of GCPs. The accuracy is correlated with the number of GCPs (use 19 GCPs instead of 10 allows to reduce the difference of 4 cm); the required accuracy should be dependant of the research problematic. Last, in this particular environment, the presence of very small water surfaces on the sand bank does not allow to improve the accuracy when the spatial resolution of images is decreased.

scholarly journals Spatio-Temporal Change Monitoring of Outside Manure Piles Using Unmanned Aerial Vehicle Images

Drones ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Geonung Park ◽  
Kyunghun Park ◽  
Bonggeun Song
Keyword(s):  
Point Source ◽  
Laser Scanning ◽  
Image Data ◽  
Surface Model ◽  
Point Source Pollution ◽  
Efficient Management ◽  
Aerial Vehicle ◽  
Spatio Temporal ◽  
Agricultural Areas ◽  
Water Quality Deterioration

Water quality deterioration due to outdoor loading of livestock manure requires efficient management of outside manure piles (OMPs). This study was designed to investigate OMPs using unmanned aerial vehicles (UAVs) for efficient management of non-point source pollution in agricultural areas. A UAV was used to acquire image data, and the distribution and cover installation status of OMPs were identified through ortho-images; the volumes of OMP were calculated using digital surface model (DSM). UAV- and terrestrial laser scanning (TLS)-derived DSMs were compared for identifying the accuracy of calculated volumes. The average volume accuracy was 92.45%. From April to October, excluding July, the monthly average volumes of OMPs in the study site ranged from 64.89 m3 to 149.69 m3. Among the 28 OMPs investigated, 18 were located near streams or agricultural waterways. Establishing priority management areas among the OMP sites distributed in a basin is possible using spatial analysis, and it is expected that the application of UAV technology will contribute to the efficient management of OMPs and other non-point source pollutants.

scholarly journals Remote Sensing for Land Administration

2020 ◽  
Vol 12 (15) ◽  
pp. 2497
Author(s):  
Rohan Bennett ◽  
Peter van Oosterom ◽  
Christiaan Lemmen ◽  
Mila Koeva
Keyword(s):  
Remote Sensing ◽  
Land Tenure ◽  
Laser Scanning ◽  
Poverty Reduction ◽  
Spatial Information ◽  
Cost Effective ◽  
Terrestrial Lidar ◽  
Land Administration ◽  
Tools And Techniques ◽  
Vertical Development

Land administration constitutes the socio-technical systems that govern land tenure, use, value and development within a jurisdiction. The land parcel is the fundamental unit of analysis. Each parcel has identifiable boundaries, associated rights, and linked parties. Spatial information is fundamental. It represents the boundaries between land parcels and is embedded in cadastral sketches, plans, maps and databases. The boundaries are expressed in these records using mathematical or graphical descriptions. They are also expressed physically with monuments or natural features. Ideally, the recorded and physical expressions should align, however, in practice, this may not occur. This means some boundaries may be physically invisible, lacking accurate documentation, or potentially both. Emerging remote sensing tools and techniques offers great potential. Historically, the measurements used to produce recorded boundary representations were generated from ground-based surveying techniques. The approach was, and remains, entirely appropriate in many circumstances, although it can be timely, costly, and may only capture very limited contextual boundary information. Meanwhile, advances in remote sensing and photogrammetry offer improved measurement speeds, reduced costs, higher image resolutions, and enhanced sampling granularity. Applications of unmanned aerial vehicles (UAV), laser scanning, both airborne and terrestrial (LiDAR), radar interferometry, machine learning, and artificial intelligence techniques, all provide examples. Coupled with emergent societal challenges relating to poverty reduction, rapid urbanisation, vertical development, and complex infrastructure management, the contemporary motivation to use these new techniques is high. Fundamentally, they enable more rapid, cost-effective, and tailored approaches to 2D and 3D land data creation, analysis, and maintenance. This Special Issue hosts papers focusing on this intersection of emergent remote sensing tools and techniques, applied to domain of land administration.

An Adaptive Response Surface Method Using Bayesian Metric and Model Bias Correction Function

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Lei Shi ◽  
Ren-Jye Yang ◽  
Ping Zhu
Keyword(s):  
Response Surface ◽  
Bias Correction ◽  
Adaptive Response ◽  
Large Scale ◽  
Correction Method ◽  
Data Uncertainty ◽  
Correction Function ◽  
Surface Model ◽  
Model Bias ◽  
Adaptive Response Surface Method

The Bayesian metric was used to select the best available response surface in the literature. One of the major drawbacks of this method is the lack of a rigorous method to quantify data uncertainty, which is required as an input. In addition, the accuracy of any response surface is inherently unpredictable. This paper employs the Gaussian process based model bias correction method to quantify the data uncertainty and subsequently improve the accuracy of a response surface model. An adaptive response surface updating algorithm is then proposed for a large-scale problem to select the best response surface. The proposed methodology is demonstrated by a mathematical example and then applied to a vehicle design problem.

scholarly journals MULTISPECTRAL AIRBORNE LASER SCANNING FOR AUTOMATED MAP UPDATING

2016 ◽  
Vol XLI-B3 ◽  
pp. 323-330 ◽  
Author(s):  
Leena Matikainen ◽  
Juha Hyyppä ◽  
Paula Litkey
Keyword(s):  
Change Detection ◽  
Laser Scanning ◽  
Point Clouds ◽  
Airborne Laser Scanning ◽  
Aerial Images ◽  
Sensor Technology ◽  
Classification Error ◽  
Surface Model ◽  
Airborne Laser ◽  
Map Updating

During the last 20 years, airborne laser scanning (ALS), often combined with multispectral information from aerial images, has shown its high feasibility for automated mapping processes. Recently, the first multispectral airborne laser scanners have been launched, and multispectral information is for the first time directly available for 3D ALS point clouds. This article discusses the potential of this new single-sensor technology in map updating, especially in automated object detection and change detection. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from a random forests analysis suggest that the multispectral intensity information is useful for land cover classification, also when considering ground surface objects and classes, such as roads. An out-of-bag estimate for classification error was about 3% for separating classes asphalt, gravel, rocky areas and low vegetation from each other. For buildings and trees, it was under 1%. According to feature importance analyses, multispectral features based on several channels were more useful that those based on one channel. Automatic change detection utilizing the new multispectral ALS data, an old digital surface model (DSM) and old building vectors was also demonstrated. Overall, our first analyses suggest that the new data are very promising for further increasing the automation level in mapping. The multispectral ALS technology is independent of external illumination conditions, and intensity images produced from the data do not include shadows. These are significant advantages when the development of automated classification and change detection procedures is considered.

scholarly journals UAV AERIAL SURVEY: ACCURACY ESTIMATION FOR AUTOMATICALLY GENERATED DENSE DIGITAL SURFACE MODEL AND ORTHOTHOTO PLAN

2016 ◽  
Vol XLI-B6 ◽  
pp. 155-159
Author(s):  
M. A. Altyntsev ◽  
S. A. Arbuzov ◽  
R. A. Popov ◽  
G. V. Tsoi ◽  
M. O. Gromov
Keyword(s):  
Survey Data ◽  
Laser Scanning ◽  
Aerial Survey ◽  
Surface Model ◽  
Model Generation ◽  
Digital Surface Model ◽  
Reliable Criterion ◽  
Accuracy Estimation ◽  
Survey Accuracy ◽  
Digital Orthophoto

A dense digital surface model is one of the products generated by using UAV aerial survey data. Today more and more specialized software are supplied with modules for generating such kind of models. The procedure for dense digital model generation can be completely or partly automated. Due to the lack of reliable criterion of accuracy estimation it is rather complicated to judge the generation validity of such models. One of such criterion can be mobile laser scanning data as a source for the detailed accuracy estimation of the dense digital surface model generation. These data may be also used to estimate the accuracy of digital orthophoto plans created by using UAV aerial survey data. The results of accuracy estimation for both kinds of products are presented in the paper.

scholarly journals Terrestrial Laser Scanning and Settled Techniques: A Support to Detect Pathologies and Safety Conditions of Timber Structures

2013 ◽  
Vol 778 ◽  
pp. 350-357 ◽  
Author(s):  
Clara Bertolini-Cestari ◽  
Filiberto Chiabrando ◽  
Stefano Invernizzi ◽  
Tanja Marzi ◽  
Antonia Spanò
Keyword(s):  
Laser Scanning ◽  
Planning Process ◽  
Laser Scanner ◽  
Texture Mapping ◽  
Surface Model ◽  
Resolution Model ◽  
Close Range ◽  
High Resolution Model ◽  
Increasing Demand ◽  
Non Destructive

Nowadays, there is an increasing demand for detailed geometrical representation of the existing cultural heritage, in particular to improve the comprehension of interactions between different phenomena and to allow a better decisional and planning process. The LiDAR technology (Light Detection and Ranging) can be adopted in different fields, ranging from aerial applications to mobile and terrestrial mapping systems. One of the main target of this study is to propose an integration of innovative and settled inquiring techniques, ranging from the reading of the technological system, to non-destructive tools for diagnosis and 3D metric modeling of buildings heritage. Many inquiring techniques, including Terrestrial Laser Scanner (TLS) method, have been exploited to study the main room of the Valentino Castle in Torino. The so-called “Salone delle Feste”, conceived in the XVIIth century under the guidance of Carlo di Castellamonte, has been selected as a test area. The beautiful frescos and stuccoes of the domical vault are sustained by a typical Delorme carpentry, whose span is among the largest of their kind. The dome suffered from degradation during the years, and a series of interventions were put into place. A survey has revealed that the suspender cables above the vault in the region close to the abutments have lost their tension. This may indicate an increase of the vault deformation; therefore a structural assessment of the dome is mandatory. The high detailed metric survey, carried out with integrated laser scanning and digital close range photogrammetry, reinforced the structural hypothesis of damages and revealed the deformation effects. In addition, the correlation between the survey-model of the intrados and of the extrados allowed a non-destructive and extensive determination of the dome thickness. The photogram-metrical survey of frescos, with the re-projection of images on vault surface model (texture mapping), is purposed to exactly localize formers restoration and their signs on frescos continuity. The present paper illustrates the generation of the 3D high-resolution model and its relations with the results of the structural survey; both of them support the Finite Element numerical simulation of the dome.

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