scholarly journals Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions

2020 ◽  
Vol 12 (12) ◽  
pp. 1946 ◽  
Author(s):  
Sara Cucchiaro ◽  
Daniel J. Fallu ◽  
He Zhang ◽  
Kevin Walsh ◽  
Kristof Van Oost ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Fusion ◽  
Laser Scanning ◽  
Control Point ◽  
Degradation Process ◽  
Real Surface ◽  
Heritage Sites ◽  
Data Merging ◽  
Starting Point ◽  
Historical Heritage

Agricultural terraced landscapes, which are important historical heritage sites (e.g., UNESCO or Globally Important Agricultural Heritage Systems (GIAHS) sites) are under threat from increased soil degradation due to climate change and land abandonment. Remote sensing can assist in the assessment and monitoring of such cultural ecosystem services. However, due to the limitations imposed by rugged topography and the occurrence of vegetation, the application of a single high-resolution topography (HRT) technique is challenging in these particular agricultural environments. Therefore, data fusion of HRT techniques (terrestrial laser scanning (TLS) and aerial/terrestrial structure from motion (SfM)) was tested for the first time in this context (terraces), to the best of our knowledge, to overcome specific detection problems such as the complex topographic and landcover conditions of the terrace systems. SfM–TLS data fusion methodology was trialed in order to produce very high-resolution digital terrain models (DTMs) of two agricultural terrace areas, both characterized by the presence of vegetation that covers parts of the subvertical surfaces, complex morphology, and inaccessible areas. In the unreachable areas, it was necessary to find effective solutions to carry out HRT surveys; therefore, we tested the direct georeferencing (DG) method, exploiting onboard multifrequency GNSS receivers for unmanned aerial vehicles (UAVs) and postprocessing kinematic (PPK) data. The results showed that the fusion of data based on different methods and acquisition platforms is required to obtain accurate DTMs that reflect the real surface roughness of terrace systems without gaps in data. Moreover, in inaccessible or hazardous terrains, a combination of direct and indirect georeferencing was a useful solution to reduce the substantial inconvenience and cost of ground control point (GCP) placement. We show that in order to obtain a precise data fusion in these complex conditions, it is essential to utilize a complete and specific workflow. This workflow must incorporate all data merging issues and landcover condition problems, encompassing the survey planning step, the coregistration process, and the error analysis of the outputs. The high-resolution DTMs realized can provide a starting point for land degradation process assessment of these agriculture environments and supplies useful information to stakeholders for better management and protection of such important heritage landscapes.

scholarly journals MULTISCALE DOCUMENTATION AND MONITORING OF L’AQUILA HISTORICAL CENTRE USING UAV PHOTOGRAMMETRY

2017 ◽  
Vol XLII-5/W1 ◽  
pp. 365-371 ◽  
Author(s):  
D. Dominici ◽  
M. Alicandro ◽  
E. Rosciano ◽  
V. Massimi
Keyword(s):  
High Resolution ◽  
Cultural Heritage ◽  
Laser Scanning ◽  
3D Models ◽  
High Resolution Satellite Images ◽  
Wide Range ◽  
Effective Science ◽  
Historical Heritage ◽  
A Minor ◽  
Short Time

Nowadays geomatic techniques can guarantee not only a precise and accurate survey for the documentation of our historical heritage but also a solution to monitor its behaviour over time after, for example, a catastrophic event (earthquakes, landslides, ecc). Europe is trying to move towards harmonized actions to store information on cultural heritage (MIBAC with the ICCS forms, English heritage with the MIDAS scheme, etc) but it would be important to provide standardized methods in order to perform measuring operations to collect certified metric data. The final result could be a database to support the entire management of the cultural heritage and also a checklist of “what to do” and “when to do it”. The wide range of geomatic techniques provides many solutions to acquire, to organize and to manage data at a multiscale level: high resolution satellite images can provide information in a short time during the “early emergency” while UAV photogrammetry and laser scanning can provide digital high resolution 3D models of buildings, ortophotos of roofs and facades and so on. This paper presents some multiscale survey case studies using UAV photogrammetry: from a minor historical village (Aielli) to the centre of L’Aquila (Santa Maria di Collemaggio Church) from the post-emergency to now. This choice has been taken not only to present how geomatics is an effective science for modelling but also to present a complete and reliable way to perform conservation and/or restoration through precise monitoring techniques, as shown in the third case study.

scholarly journals THE GREAT WALL 3D DOCUMENTATION AND APPLICATION BASED ON MULTI-SOURCE DATA FUSION – A CASE STUDY OF NO.15 ENEMY TOWER OF THE NEW GUANGWU GREAT WALL

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 1465-1470
Author(s):  
W. Hua ◽  
Y. Qiao ◽  
M. Hou
Keyword(s):  
Data Fusion ◽  
Cultural Heritage ◽  
Structure Data ◽  
Laser Scanning ◽  
3D Structure ◽  
Terrestrial Laser Scanning ◽  
Heritage Sites ◽  
3D Data ◽  
Digital Documentation ◽  
Great Wall

Abstract. Laser scanning or photogrammetry are useful individual techniques for digital documentation of cultural heritage sites. However, these techniques are of limited usage if cultural heritage such as the Great Wall is in harsh geographical conditions. The Great Wall is usually built on the ridge with cliffs on both sides, so it is very difficult to construct scaffolding. Therefore, the three-dimensional (3D) data obtained from the traditional 3D laser scanning is not complete. As UAV cannot enter the enemy tower, the 3D structure data inside the enemy tower with unmanned aerial vehicle (UAV) photogrammetry is missing. In order to explore effective methods to completely collect the 3D data of cultural heritage under harsh geographical environment, this study focuses on establishing a 3D model and the associated digital documentation for the No.15 enemy tower of the New Guangwu Great Wall using a combination of terrestrial laser scanning and UAV photogrammetry. This paper proposes an integrated data collection method and reduces the layout of image control points using RTK-UAV technology, which improved work efficiency and reduced work risks as well. In this paper, the internal structure data of the Great Wall enemy tower was collected by laser scanning, the external structure data was collected by UAV photogrammetry, and data fusion was based on ICP algorithm. Finally, we obtained the complete and high quality 3D digital documentation of the Great Wall enemy tower, the data can be displayed digitally and help heritage experts complete the Great Wall's restoration. This study demonstrates the potential of integrating terrestrial laser scanning and UAV photogrammetry in 3D digital documentation of cultural heritage sites.

scholarly journals ALS and TLS data fusion in cultural heritage documentation and modeling

2015 ◽  
Vol XL-5/W7 ◽  
pp. 147-150 ◽  
Author(s):  
A. Fryskowska ◽  
P. Walczykowski ◽  
P. Delis ◽  
M. Wojtkowska
Keyword(s):  
Cultural Heritage ◽  
Laser Scanning ◽  
3D Models ◽  
Reference Points ◽  
Heritage Sites ◽  
Historical Structures ◽  
Data Merging ◽  
Combining Data ◽  
Merging Process ◽  
3D Information

One of the most important aspects of documenting cultural heritage sites is acquiring detailed and accurate data. A popular method of storing 3D information about historical structures is using 3D models. These models are built based on terrestrial or aerial laser scanning data. These methods are seldom used together. Historical buildings usually have a very complex design, therefore the input data, on the basis of which their 3D models are being built, must provide a high enough accuracy to model these complexities. The data processing methods used, as well as the modeling algorithms implemented, should be highly automated and universal. The main of the presented research was to analyze and compare various methods for extracting matching points. The article presents the results of combining data from ALS and TLS using reference points extracted both manually and automatically. Finally, the publication also includes an analysis of the accuracy of the data merging process.

Algorithms for automated montage synthesis of images from laser-scanning confocal microscopes

1995 ◽  
Vol 53 ◽  
pp. 650-651
Author(s):  
D. E. Becker
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Laser Scanning ◽  
Cell Counting ◽  
Wide Area ◽  
Data Set ◽  
Computational Synthesis ◽  
Automated Cell Counting ◽  
Partial View ◽  
The Individual

An efficient, robust, and widely-applicable technique is presented for computational synthesis of high-resolution, wide-area images of a specimen from a series of overlapping partial views. This technique can also be used to combine the results of various forms of image analysis, such as segmentation, automated cell counting, deblurring, and neuron tracing, to generate representations that are equivalent to processing the large wide-area image, rather than the individual partial views. This can be a first step towards quantitation of the higher-level tissue architecture. The computational approach overcomes mechanical limitations, such as hysterisis and backlash, of microscope stages. It also automates a procedure that is currently done manually. One application is the high-resolution visualization and/or quantitation of large batches of specimens that are much wider than the field of view of the microscope.The automated montage synthesis begins by computing a concise set of landmark points for each partial view. The type of landmarks used can vary greatly depending on the images of interest. In many cases, image analysis performed on each data set can provide useful landmarks. Even when no such “natural” landmarks are available, image processing can often provide useful landmarks.

scholarly journals Comparison and Evaluation of Different Pit-Filling Methods for Generating High Resolution Canopy Height Model Using UAV Laser Scanning Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2239
Author(s):  
Ying Quan ◽  
Mingze Li ◽  
Yuanshuo Hao ◽  
Bin Wang
Keyword(s):  
High Resolution ◽  
Laser Scanning ◽  
Evaluation Framework ◽  
Canopy Height ◽  
Filter Method ◽  
Individual Tree ◽  
Significant Difference ◽  
Point Interpolation ◽  
Canopy Height Model ◽  
Height Model

As a common form of light detection and ranging (LiDAR) in forestry applications, the canopy height model (CHM) provides the elevation distribution of aboveground vegetation. A CHM is traditionally generated by interpolating all the first LiDAR echoes. However, the first echo cannot accurately represent the canopy surface, and the resulting large amount of noise (data pits) also reduce the CHM quality. Although previous studies concentrate on many pit-filling methods, the applicability of these methods in high-resolution unmanned aerial vehicle laser scanning (UAVLS)-derived CHMs has not been revealed. This study selected eight widely used, recently developed, representative pit-filling methods, namely first-echo interpolation, smooth filtering (mean, medium and Gaussian), highest point interpolation, pit-free algorithm, spike-free algorithm and graph-based progressive morphological filtering (GPMF). A comprehensive evaluation framework was implemented, including a quantitative evaluation using simulation data and an additional application evaluation using UAVLS data. The results indicated that the spike-free algorithm and GPMF had excellent visual performances and were closest to the real canopy surface (root mean square error (RMSE) of simulated data were 0.1578 m and 0.1093 m, respectively; RMSE of UAVLS data were 0.3179 m and 0.4379 m, respectively). Compared with the first-echo method, the accuracies of the spike-free algorithm and GPMF improved by approximately 23% and 22%, respectively. The pit-free algorithm and highest point interpolation method also have advantages in high-resolution CHM generation. The global smooth filter method based on the first-echo CHM reduced the average canopy height by approximately 7.73%. Coniferous forests require more pit-filling than broad-leaved forests and mixed forests. Although the results of individual tree applications indicated that there was no significant difference between these methods except the median filter method, pit-filling is still of great significance for generating high-resolution CHMs. This study provides guidance for using high-resolution UAVLS in forestry applications.

High-resolution differential thermography of integrated circuits with optical feedback laser scanning microscopy

2005 ◽  
Vol 87 (23) ◽  
pp. 231104 ◽  
Author(s):  
Carlo Mar Blanca ◽  
Vernon Julius Cemine ◽  
Vera Marie Sastine ◽  
Caesar Saloma
Keyword(s):  
High Resolution ◽  
Integrated Circuits ◽  
Laser Scanning ◽  
Optical Feedback ◽  
Laser Scanning Microscopy ◽  
Scanning Microscopy

Multisensor Degradation Data Fusion and Remaining Life Prediction

2017 ◽  
Author(s):  
Changxi Wang ◽  
E. A. Elsayed ◽  
Kang Li ◽  
Javier Cabrera
Keyword(s):  
Data Fusion ◽  
Prediction Accuracy ◽  
Life Prediction ◽  
Clustering Algorithm ◽  
Partial Information ◽  
Degradation Process ◽  
Sensor Data ◽  
Multiple Sensors ◽  
Degradation Data ◽  
Degradation Monitoring

Multiple sensors are commonly used for degradation monitoring. Since different sensors may be sensitive at different stages of the degradation process and each sensor data contain only partial information of the degraded unit, data fusion approaches that integrate degradation data from multiple sensors can effectively improve degradation modeling and life prediction accuracy. We present a non-parametric approach that assigns weights to each sensor based on dynamic clustering of the sensors observations. A case study that involves a fatigue-crack-growth dataset is implemented in order evaluate the prognostic performance of the unit. Results show that the fused path obtained with the proposed approach outperforms any individual sensor data and other paths obtained with an adaptive threshold clustering algorithm in terms of life prediction accuracy.

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