scholarly journals UPDATING LIDAR DSM USING HIGH RESOLUTION STEREO-BASED DSM FROM WORLDVIEW-2

2014 ◽  
Vol XL-2/W3 ◽  
pp. 59-64
Author(s):  
H. Arefi ◽  
H. Hashemi ◽  
Th. Krauss ◽  
M. Gharibia
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Lidar Data ◽  
High Quality ◽  
Qualitative And Quantitative ◽  
Surface Models ◽  
Dense Point ◽  
Processing Techniques

In recent years, the acquisition and processing techniques of high resolution Digital Surface Models (DSM) have been rapidly improved. Airborne LiDAR production as a well-known and high quality DSM is still unbeatable in elevation accuracy and highly produced dense point clouds. In this paper, the objective is to update an old but high quality DSM produced by LiDAR data using a DSM generated from high resolution stereo satellite images. A classification-base algorithm is proposed to extract building changes between DSMs in two epochs. For image classification procedure, the DSM and Worldview-2 orthorectified images have been used as input data for a fuzzy-based classification method. Then, extracted buildings are classified into unchanged, destroyed, new, and changed classes. In this study a dataset related to Munich city, has been utilized to test the experimental investigation. The implemented qualitative and quantitative assessments demonstrate high quality as well as high feasibility of the proposed approach.

scholarly journals Methods for tree cover extraction from high resolution orthophotos and airborne LiDAR scanning in Spanish dehesas

2019 ◽  
pp. 17 ◽  
Author(s):  
I. Borlaf-Mena ◽  
M. A. Tanase ◽  
A. Gómez-Sal
Keyword(s):  
High Resolution ◽  
Laser Scanning ◽  
Remote Sensing Data ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Tree Cover ◽  
Lidar Data ◽  
Homogeneous Tree ◽  
Visual Interpretation ◽  
Management Changes

<p>Dehesas are high value agroecosystems that benefit from the effect tree cover has on pastures. Such effect occurs when tree cover is incomplete and homogeneous. Tree cover may be characterized from field data or through visual interpretation of remote sensing data, both time-consuming tasks. An alternative is the extraction of tree cover from aerial imagery using automated methods, on spectral derivate products (i.e. NDVI) or LiDAR point clouds. This study focuses on assessing and comparing methods for tree cover estimation from high resolution orthophotos and airborne laser scanning (ALS). RGB image processing based on thresholding of the ‘Excess Green minus Excess Red’ index with the Otsu method produced acceptable results (80%), lower than that obtained by thresholding the digital canopy model obtained from the ALS data (87%) or when combining RGB and LiDAR data (87.5%). The RGB information was found to be useful for tree delineation, although very vulnerable to confusion with the grass or shrubs. The ALS based extraction suffered for less confusion as it differentiated between trees and the remaining vegetation using the height. These results show that analysis of historical orthophotographs may be successfully used to evaluate the effects of management changes while LiDAR data may provide a substantial increase in the accuracy for the latter period. Combining RGB and Lidar data did not result in significant improvements over using LIDAR data alone.</p>

scholarly journals Comparison of Filters for Archaeology-Specific Ground Extraction from Airborne LiDAR Point Clouds

2020 ◽  
Vol 12 (18) ◽  
pp. 3025
Author(s):  
Benjamin Štular ◽  
Edisa Lozić
Keyword(s):  
Low Cost ◽  
Point Clouds ◽  
Quantitative Comparison ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Landscape Type ◽  
Cloud Data ◽  
Qualitative And Quantitative ◽  
Real World Problem ◽  
Airborne Lidar Data

Identifying bare-earth or ground returns within point cloud data is a crucially important process for archaeologists who use airborne LiDAR data, yet there has thus far been very little comparative assessment of the available archaeology-specific methods and their usefulness for archaeological applications. This article aims to provide an archaeology-specific comparison of filters for ground extraction from airborne LiDAR point clouds. The qualitative and quantitative comparison of the data from four archaeological sites from Austria, Slovenia, and Spain should also be relevant to other disciplines that use visualized airborne LiDAR data. We have compared nine filters implemented in free or low-cost off-the-shelf software, six of which are evaluated in this way for the first time. The results of the qualitative and quantitative comparison are not directly analogous, and no filter is outstanding compared to the others. However, the results are directly transferable to real-world problem-solving: Which filter works best for a given combination of data density, landscape type, and type of archaeological features? In general, progressive TIN (software: lasground_new) and a hybrid (software: Global Mapper) commercial filter are consistently among the best, followed by an open source slope-based one (software: Whitebox GAT). The ability of the free multiscale curvature classification filter (software: MCC-LIDAR) to remove vegetation is also commendable. Notably, our findings show that filters based on an older generation of algorithms consistently outperform newer filtering techniques. This is a reminder of the indirect path from publishing an algorithm to filter implementation in software.

scholarly journals Cloth simulation-based construction of pit-free canopy height models from airborne LiDAR data

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Wuming Zhang ◽  
Shangshu Cai ◽  
Xinlian Liang ◽  
Jie Shao ◽  
Ronghai Hu ◽  
...  
Keyword(s):  
Tree Height ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Canopy Height ◽  
Lidar Data ◽  
Cloth Simulation ◽  
Simulation Based ◽  
Maximum Tree Height ◽  
Airborne Lidar Data ◽  
Better Than

Abstract Background The universal occurrence of randomly distributed dark holes (i.e., data pits appearing within the tree crown) in LiDAR-derived canopy height models (CHMs) negatively affects the accuracy of extracted forest inventory parameters. Methods We develop an algorithm based on cloth simulation for constructing a pit-free CHM. Results The proposed algorithm effectively fills data pits of various sizes whilst preserving canopy details. Our pit-free CHMs derived from point clouds at different proportions of data pits are remarkably better than those constructed using other algorithms, as evidenced by the lowest average root mean square error (0.4981 m) between the reference CHMs and the constructed pit-free CHMs. Moreover, our pit-free CHMs show the best performance overall in terms of maximum tree height estimation (average bias = 0.9674 m). Conclusion The proposed algorithm can be adopted when working with different quality LiDAR data and shows high potential in forestry applications.

scholarly journals QUALITY PREDICTION OF DENSE POINTS GENERATED BY STRUCTURE FROM MOTION FOR HIGH-QUALITY AND EFFICIENT AS-IS MODEL RECONSTRUCTION

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 95-101
Author(s):  
R. Moritani ◽  
S. Kanai ◽  
H. Date ◽  
Y. Niina ◽  
R. Honma
Keyword(s):  
Structure From Motion ◽  
Point Clouds ◽  
Quality Prediction ◽  
Construction Site ◽  
Model Reconstruction ◽  
High Quality ◽  
Bridge Column ◽  
Dense Point ◽  
Selection Of

<p><strong>Abstract.</strong> In this paper, we introduce a method for predicting the quality of dense points and selecting low-quality regions on the points generated by the structure from motion (SfM) and multi-view stereo (MVS) pipeline to realize high-quality and efficient as-is model reconstruction, using only results from the former: sparse point clouds and camera poses. The method was shown to estimate the quality of the final dense points as the quality predictor on an approximated model obtained from SfM only, without requiring the time-consuming MVS process. Moreover, the predictors can be used for selection of low-quality regions on the approximated model to estimate the next-best optimum camera poses which could improve quality. Furthermore, the method was applied to the prediction of dense point quality generated from the image sets of a concrete bridge column and construction site, and the prediction was validated in a time much shorter than using MVS. Finally, we discussed the correlation between the predictors and the final dense point quality.</p>

scholarly journals AUTOMATIC BUILDING CHANGE DETECTION USING MULTI-TEMPORAL AIRBORNE LIDAR DATA

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 19-24
Author(s):  
R. C. dos Santos ◽  
M. Galo ◽  
A. C. Carrilho ◽  
G. G. Pessoa ◽  
R. A. R. de Oliveira
Keyword(s):  
Change Detection ◽  
Average Density ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Qualitative And Quantitative ◽  
Multi Temporal ◽  
Quantitative Analyses ◽  
3D Information ◽  
Airborne Lidar Data ◽  
Area Monitoring

Abstract. The automatic detection of building changes is an essential process for urban area monitoring, urban planning, and database update. In this context, 3D information derived from multi-temporal airborne LiDAR scanning is one effective alternative. Despite several works in the literature, the separation of change areas in building and non-building remains a challenge. In this sense, it is proposed a new method for building change detection, having as the main contribution the use of height entropy concept to identify the building change areas. The experiments were performed considering multi-temporal airborne LiDAR data from 2012 and 2014, both with average density around 5 points/m2. Qualitative and quantitative analyses indicate that the proposed method is robust in building change detection, having the potential to identify small changes (larger than 20 m2). In general, the change detection method presented average completeness and correctness around 97% and 71%, respectively.

scholarly journals Topographical changes revealed by high-resolution airborne LiDAR data: The 1999 Tsaoling landslide induced by the Chi–Chi earthquake

2006 ◽  
Vol 88 (3-4) ◽  
pp. 160-172 ◽  
Author(s):  
Rou-Fei Chen ◽  
Kuo-Jen Chang ◽  
Jacques Angelier ◽  
Yu-Chang Chan ◽  
Benoît Deffontaines ◽  
...  
Keyword(s):  
High Resolution ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Airborne Lidar Data

scholarly journals UAV and LiDAR Data in the Service of Bank Gully Erosion Measurement in Rambla de Algeciras Lakeshore

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2748
Author(s):  
Radouane Hout ◽  
Véronique Maleval ◽  
Gil Mahe ◽  
Eric Rouvellac ◽  
Rémi Crouzevialle ◽  
...  
Keyword(s):  
High Resolution ◽  
Point Clouds ◽  
Sediment Budget ◽  
Lidar Data ◽  
Different Types ◽  
The Subject ◽  
Geomorphological Changes ◽  
Uncertainty Models ◽  
Geological Formations ◽  
Different Sources

The Rambla de Algeciras lake in Murcia is a reservoir for drinking water and contributes to the reduction of flooding. With a semi-arid climate and a very friable nature of the geological formations at the lakeshore level, the emergence and development of bank gullies is favored and poses a problem of silting of the dam. A study was conducted on these lakeshores to estimate the sediment input from the bank gullies. In 2018, three gullies of different types were the subject of three UAV photography missions to model in high resolution their low topographic change, using the SfM-MVS photogrammetry method. The combination of two configurations of nadir and oblique photography allowed us to obtain a complete high-resolution modeling of complex bank gullies with overhangs, as it was the case in site 3. To study annual lakeshore variability and sediment dynamics we used LiDAR data from the PNOA project taken in 2009 and 2016. For a better error analysis of UAV photogrammetry data we compared spatially variable and uniform uncertainty models, while taking into account the different sources of error. For LiDAR data, on the other hand, we used a spatially uniform error model. Depending on the geomorphology of the gullies and the configuration of the data capture, we chose the most appropriate method to detect geomorphological changes on the surfaces of the bank gullies. At site 3 the gully topography is complex, so we performed a 3D distance calculation between point clouds using the M3C2 algorithm to estimate the sediment budget. On sites 1 and 2 we used the DoD technique to estimate the sediment budget as it was the case for the LiDAR data. The results of the LiDAR and UAV data reveal significant lakeshore erosion activity by bank gullies since the annual inflow from the banks is estimated at 39 T/ha/year.

scholarly journals Measurement of Road Surface Deformation Using Images Captured from UAVs

2019 ◽  
Vol 11 (12) ◽  
pp. 1507 ◽  
Author(s):  
Javier Cardenal ◽  
Tomás Fernández ◽  
José Pérez-García ◽  
José Gómez-López
Keyword(s):  
High Resolution ◽  
Surface Deformation ◽  
Ground Level ◽  
Point Clouds ◽  
Road Surface ◽  
Flying Height ◽  
Total Period ◽  
Dense Point ◽  
Active Landslide ◽  
High Resolution Images

This paper presents a methodology for measuring road surface deformation due to terrain instability processes. The methodology is based on ultra-high resolution images acquired from unmanned aerial vehicles (UAVs). Flights are georeferenced by means of Structure from Motion (SfM) techniques. Dense point clouds, obtained using the multiple-view stereo (MVS) approach, are used to generate digital surface models (DSM) and high resolution orthophotographs (0.02 m GSD). The methodology has been applied to an unstable area located in La Guardia (Jaen, Southern Spain), where an active landslide was identified. This landslide affected some roads and accesses to a highway at the landslide foot. The detailed road deformation was monitored between 2012 and 2015 by means of eleven UAV flights of ultrahigh resolution covering an area of about 260 m × 90 m. The accuracy of the analysis has been established in 0.02 ± 0.01 m in XY and 0.04 ± 0.02 m in Z. Large deformations in the order of two meters were registered in the total period analyzed that resulted in maximum average rates of 0.62 m/month in the unstable area. Some boundary conditions were considered because of the low required flying height (<50 m above ground level) in order to achieve a suitable image GSD, the fast landslide dynamic, continuous maintenance works on the affected roads and dramatic seasonal vegetation changes throughout the monitoring period. Finally, we have analyzed the relation of displacements to rainfalls in the area, finding a significant correlation between the two variables, as well as two different reactivation episodes.

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