scholarly journals VERTICAL ORIENTATION CORRECTION OF UAV IMAGE-BASED POINT CLOUDS USING STATISTICAL MODELING OF GABLE ROOF GEOMETRY

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 519-523 ◽  
Author(s):  
P. Polewski ◽  
W. Yao ◽  
L. Fang
Keyword(s):  
Rural Areas ◽  
Laser Scanning ◽  
Low Cost ◽  
Remote Sensing Data ◽  
Point Clouds ◽  
Density Estimator ◽  
Vertical Orientation ◽  
Gable Roof ◽  
The World ◽  
Uav Image

<p><strong>Abstract.</strong> Coregistration of point clouds obtained from various sensors is an important part of workflows for automatic building reconstruction from remote sensing data. Many approaches assume a common Z axis between the coordinate systems, and perform coregistration in 2D. While this assumption is usually valid for laser scanning (LS) data, for photogrammetric point clouds the Z axis is in general different from the world Z axis, and requires correction e.g. by manually measured ground control points (GCP). In this paper, we propose a fully automatic, GCP-free procedure for finding the world Z axis in rural areas, based on the relationships of planar surfaces in building gable roofs. Instead of performing direct gable line detection, we derive these lines as theoretical intersections between adjacent roof planes from 3D shape fitting. Each gable roof then casts a vote for both the Z axis direction and sign based on roof convexity constraints, and the votes are aggregated through a non-parametric kernel density estimator model. Experiments on two real world UAV image-based point clouds show that the Z axis recovered by our method leads to high-accuracy planimetric coregistration, with a median distance over 89 as well as 149 matched linear feature pairs (respectively for dataset 1 and 2) lying below 1&amp;thinsp;cm. Our results indicate that a high-quality vertical orientation can be achieved without using any GNSS or IMU hardware, which enables the use of low-cost UAV platforms for suburban and rural mapping tasks.</p>

Green Communication Infrastructure (GCI) Serving Different Smart City Applications

2021 ◽  
Vol 01 ◽  
Author(s):  
Qutaiba I. Ali ◽  
Issam Jafar
Keyword(s):  
Rural Areas ◽  
Smart City ◽  
Low Cost ◽  
System Level ◽  
Green Communication ◽  
Communication Infrastructure ◽  
Wide Range ◽  
The World ◽  
Self Powered ◽  
Application Fields

Aims: The aim of the Green Communication Infrastructure ‎‎(GCI) project is to understand the idea of a self ‎‎"sustainably" controlled correspondence foundation ‎fitting for smart city application fields. ‎ Background: This paper shows the endeavors to understand the idea of a ‎self "sustainably" energized communication foundation ‎fitting for smart city application fields. The recommended ‎Green Communication Infrastructure (CGI) comprises ‎different kinds of remote settled (or even versatile) hubs ‎performing diverse activities as per the application ‎requests. An imperative class of these hubs is the Wireless ‎Solar Router (WSR). Objective: The work in this venture was begun in 2009 with the aim ‎of demonstrating the essential advances that must be taken to ‎accomplish such framework and to proclaim the value of ‎embracing natural vitality assets in building mission ‎basic frameworks. Alternate destinations of this venture ‎are introducing a sensibly cost, solid, verified, and simple ‎to introduce correspondence foundation.‎ Method: The arrangement to actualize the GCI was accomplished ‎subsequent to passing two structure levels: device level and ‎system level. Result: The suggested system is highly applicable and serves a wide ‎range of smart city application fields and hence many ‎people and organizations can utilize this system. ‎ Conclusion: The presence of a reliable, secured, low cost, easy to install ‎and self-powered communication infrastructure is ‎mandatory in our nowadays. The communities in ‎developing countries or in rural areas need such a system ‎highly in order to communicate with other people in the ‎world which will affect positively their social and ‎economic situation.

A Reality Integrated BIM for Architectural Heritage Conservation

2019 ◽  
pp. 142-176
Author(s):  
Fabrizio Ivan Apollonio ◽  
Marco Gaiani ◽  
Zheng Sun
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
Information Modeling ◽  
Free Form ◽  
Architectural Heritage ◽  
Ideal Model ◽  
Double Curvature ◽  
Building Information ◽  
Architectural Treatises

Building Information Modeling (BIM) has attracted wide interest in the field of documentation and conservation of Architectural Heritage (AH). Existing approaches focus on converting laser scanned point clouds to BIM objects, but laser scanning is usually limited to planar elements which are not the typical state of AH where free-form and double-curvature surfaces are common. We propose a method that combines low-cost automatic photogrammetric data acquisition techniques with parametric BIM objects founded on Architectural Treatises and a syntax allowing the transition from the archetype to the type. Point clouds with metric accuracy comparable to that from laser scanning allows accurate as-built model semantically integrated with the ideal model from parametric library. The deviation between as-built model and ideal model is evaluated to determine if feature extraction from point clouds is essential to improve the accuracy of as-built BIM.

scholarly journals Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 905 ◽  
Author(s):  
Guerra-Hernández ◽  
Cosenza ◽  
Cardil ◽  
Silva ◽  
Botequim ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Basal Area ◽  
Remote Sensing Data ◽  
Tree Height ◽  
Point Clouds ◽  
Volume Estimation ◽  
P Value ◽  
Test Statistic ◽  
Individual Tree ◽  
Significant Difference

Estimating forest inventory variables is important in monitoring forest resources and mitigating climate change. In this respect, forest managers require flexible, non-destructive methods for estimating volume and biomass. High-resolution and low-cost remote sensing data are increasingly available to measure three-dimensional (3D) canopy structure and to model forest structural attributes. The main objective of this study was to evaluate and compare the individual tree volume estimates derived from high-density point clouds obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) in Eucalyptus spp. plantations. Object-based image analysis (OBIA) techniques were applied for individual tree crown (ITC) delineation. The ITC algorithm applied correctly detected and delineated 199 trees from ALS-derived data, while 192 trees were correctly identified using DAP-based point clouds acquired from Unmanned Aerial Vehicles (UAV), representing accuracy levels of respectively 62% and 60%. Addressing volume modelling, non-linear regression fit based on individual tree height and individual crown area derived from the ITC provided the following results: Model Efficiency (Mef) = 0.43 and 0.46, Root Mean Square Error (RMSE) = 0.030 m3 and 0.026 m3, rRMSE = 20.31% and 19.97%, and an approximately unbiased results (0.025 m3 and 0.0004 m3) using DAP and ALS-based estimations, respectively. No significant difference was found between the observed value (field data) and volume estimation from ALS and DAP (p-value from t-test statistic = 0.99 and 0.98, respectively). The proposed approaches could also be used to estimate basal area or biomass stocks in Eucalyptus spp. plantations.

scholarly journals Automatic Workflow for Roof Extraction and Generation of 3D CityGML Models from Low-Cost UAV Image-Derived Point Clouds

2020 ◽  
Vol 9 (12) ◽  
pp. 743
Author(s):  
Arnadi Murtiyoso ◽  
Mirza Veriandi ◽  
Deni Suwardhi ◽  
Budhy Soeksmantono ◽  
Agung Budi Harto
Keyword(s):  
3D Modeling ◽  
Low Cost ◽  
Point Clouds ◽  
3D Models ◽  
Additional Advantage ◽  
Planar Surfaces ◽  
Modeling Process ◽  
Point Cloud Segmentation ◽  
Segmentation Approach ◽  
Uav Image

Developments in UAV sensors and platforms in recent decades have stimulated an upsurge in its application for 3D mapping. The relatively low-cost nature of UAVs combined with the use of revolutionary photogrammetric algorithms, such as dense image matching, has made it a strong competitor to aerial lidar mapping. However, in the context of 3D city mapping, further 3D modeling is required to generate 3D city models which is often performed manually using, e.g., photogrammetric stereoplotting. The aim of the paper was to try to implement an algorithmic approach to building point cloud segmentation, from which an automated workflow for the generation of roof planes will also be presented. 3D models of buildings are then created using the roofs’ planes as a base, therefore satisfying the requirements for a Level of Detail (LoD) 2 in the CityGML paradigm. Consequently, the paper attempts to create an automated workflow starting from UAV-derived point clouds to LoD 2-compatible 3D model. Results show that the rule-based segmentation approach presented in this paper works well with the additional advantage of instance segmentation and automatic semantic attribute annotation, while the 3D modeling algorithm performs well for low to medium complexity roofs. The proposed workflow can therefore be implemented for simple roofs with a relatively low number of planar surfaces. Furthermore, the automated approach to the 3D modeling process also helps to maintain the geometric requirements of CityGML such as 3D polygon coplanarity vis-à-vis manual stereoplotting.

scholarly journals Topographic Base Maps from Remote Sensing Data for Engineering Geomorphological Modelling: An Application on Coastal Mediterranean Landscape

Geosciences ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 500 ◽  
Author(s):  
Maurizio Barbarella ◽  
Albina Cuomo ◽  
Alessandro Di Benedetto ◽  
Margherita Fiani ◽  
Domenico Guida
Keyword(s):  
Laser Scanning ◽  
Risk Mitigation ◽  
Rapid Evolution ◽  
Remote Sensing Data ◽  
Point Clouds ◽  
Feature Maps ◽  
Good Correspondence ◽  
Contour Maps ◽  
High Resolution Satellite Images ◽  
Multi Temporal

Coastal landscapes are one of the most changeable areas of the earth’s surface. Given this spatial complexity and temporal variability, the construction of reference maps useful for geo-engineering is a challenge. In order to improve the performance of geomorphic models, reliable multiscale and multi-temporal base maps and Digital Elevation Models (DEM) are needed. The work presented in this paper addresses this issue using an inter-geo-disciplinary approach to optimize the processing of multisource and multi-temporal data and DEMs by using field surveys, conceptual model, and analytical computation on a test area. The data acquired with two surveying techniques were analyzed and compared: Aerial Laser Scanning (ALS) and photogrammetry from stereo pairs of High-Resolution Satellite Images (HRSI). To assess the reliability of the DEMs produced from point clouds, the residuals between the point cloud and the interpolated filtered surface were identified and analyzed statistically. In addition to the contour maps, some feature maps such as slope, planar, and profile curvature maps were produced and analyzed. The frequency distribution of the slope and curvature values were compared with the diffusion, advection, and stream power model, revealing a good agreement with the past and present geomorphic processes acting on the different parts of the study area. Moreover, the integrated geomatics–geomorphic analysis of the outliers’ map showed a good correspondence (more than 75%) between the identified outliers and some specific geomorphological features, such as micro-landforms, which are significant for erosive and gravity-driven mechanisms. The different distribution of the above singularities by different data sources allowed us to attribute their spatial model to the temporal variation of the topography and, consequently, to the geomorphic changes, rather than to the different accuracy. For monitoring purposes and risk mitigation activities, the methodology adopted seems to meet the requirements to make a digital mapping of the coast analyzed, characterized by a rapid evolution of the surface, and can be extended to other stretches of coast with similar characteristics.

scholarly journals Data processing workflows from low-cost digital survey to various applications: three case studies of Chinese historic architecture

2015 ◽  
Vol XL-5/W7 ◽  
pp. 409-416 ◽  
Author(s):  
Z. Sun ◽  
Y. K. Cao
Keyword(s):  
Structural Analysis ◽  
Data Processing ◽  
Case Studies ◽  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
Element Analysis ◽  
Prime Concern ◽  
Architectural Preservation ◽  
Digital Survey

The paper focuses on the versatility of data processing workflows ranging from BIM-based survey to structural analysis and reverse modeling. In China nowadays, a large number of historic architecture are in need of restoration, reinforcement and renovation. But the architects are not prepared for the conversion from the booming AEC industry to architectural preservation. As surveyors working with architects in such projects, we have to develop efficient low-cost digital survey workflow robust to various types of architecture, and to process the captured data for architects. Although laser scanning yields high accuracy in architectural heritage documentation and the workflow is quite straightforward, the cost and portability hinder it from being used in projects where budget and efficiency are of prime concern. We integrate Structure from Motion techniques with UAV and total station in data acquisition. The captured data is processed for various purposes illustrated with three case studies: the first one is as-built BIM for a historic building based on registered point clouds according to Ground Control Points; The second one concerns structural analysis for a damaged bridge using Finite Element Analysis software; The last one relates to parametric automated feature extraction from captured point clouds for reverse modeling and fabrication.

scholarly journals Object Segmentation on UAV Photo Data to Support the Provision of Rural Area Spatial Information

2015 ◽  
Vol 29 (1) ◽  
Author(s):  
Nurwita Mustika Sari ◽  
Dony Kushardono
Keyword(s):  
Rural Area ◽  
Rural Areas ◽  
Spatial Information ◽  
Remote Sensing Data ◽  
Image Data ◽  
Aerial Photographs ◽  
Segmentation Method ◽  
Object Based ◽  
Aerial Vehicle ◽  
Uav Image

The use of Unmanned Aerial Vehicle (UAV) to take aerial photographs is increasing in recent years. Photo data taken by UAV become one of reliable detailed-scale  remote sensing data sources. The capability to obtain cloud-free images and the flexibility of time are some of the advantages of UAV photo data compared to satellite images with optical sensor. Displayed area at the data shows the objects clearly. Rural area has certain characteristics in its land cover namely ricefield. To delineate the area correctly there is an object-based image analysis methods (OBIA) that could be applied. In this  study, proposed a novel method to  execute the separation of objects that exist in the data with segmentation method. The result shows an effective segmentation method to separate different objects in rural areas recorded on UAV image data. The accuracy obtained is 90.47% after optimization process. This segmentation can be a valid basis to support the provision of spatial information in rural area.

scholarly journals CAN WE USE LOW-COST 360 DEGREE CAMERAS TO CREATE ACCURATE 3D MODELS?

2018 ◽  
Vol XLII-2 ◽  
pp. 69-75 ◽  
Author(s):  
L. Barazzetti ◽  
M. Previtali ◽  
F. Roncoroni
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
3D Models ◽  
Bundle Adjustment ◽  
Field Of View ◽  
Large Field ◽  
Single Shot ◽  
New Paradigm ◽  
Image Orientation

360 degree cameras capture the whole scene around a photographer in a single shot. Cheap 360 cameras are a new paradigm in photogrammetry. The camera can be pointed to any direction, and the large field of view reduces the number of photographs. This paper aims to show that accurate metric reconstructions can be achieved with affordable sensors (less than 300 euro). The camera used in this work is the Xiaomi Mijia Mi Sphere 360, which has a cost of about 300 USD (January 2018). Experiments demonstrate that millimeter-level accuracy can be obtained during the image orientation and surface reconstruction steps, in which the solution from 360&amp;deg; images was compared to check points measured with a total station and laser scanning point clouds. The paper will summarize some practical rules for image acquisition as well as the importance of ground control points to remove possible deformations of the network during bundle adjustment, especially for long sequences with unfavorable geometry. The generation of orthophotos from images having a 360&amp;deg; field of view (that captures the entire scene around the camera) is discussed. Finally, the paper illustrates some case studies where the use of a 360&amp;deg; camera could be a better choice than a project based on central perspective cameras. Basically, 360&amp;deg; cameras become very useful in the survey of long and narrow spaces, as well as interior areas like small rooms.

scholarly journals PROGRESS ON ISPRS BENCHMARK ON MULTISENSORY INDOOR MAPPING AND POSITIONING

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1709-1713
Author(s):  
C. Wang ◽  
Y. Dai ◽  
N. El-Sheimy ◽  
C. Wen ◽  
G. Retscher ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
Indoor Positioning ◽  
Benchmark Dataset ◽  
Scanning System ◽  
Indoor Environments ◽  
Building Management ◽  
Common Framework

<p><strong>Abstract.</strong> This paper presents the design of the benchmark dataset on multisensory indoor mapping and position (MIMAP) which is sponsored by ISPRS scientific initiatives. The benchmark dataset including point clouds captured by indoor mobile laser scanning system (IMLS) in indoor environments of various complexity. The benchmark aims to stimulate and promote research in the following three fields: (1) SLAM-based indoor point cloud generation; (2) automated BIM feature extraction from point clouds, with an emphasis on the elements, such as floors, walls, ceilings, doors, windows, stairs, lamps, switches, air outlets, that are involved in building management and navigation tasks ; and (3) low-cost multisensory indoor positioning, focusing on the smartphone platform solution. MIMAP provides a common framework for the evaluation and comparison of LiDAR-based SLAM, BIM feature extraction, and smartphone indoor positioning methods.</p>

scholarly journals The Feasibility of Modelling the Crown Profile of Larix olgensis Using Unmanned Aerial Vehicle Laser Scanning Data

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5555 ◽  
Author(s):  
Ying Quan ◽  
Mingze Li ◽  
Zhen Zhen ◽  
Yuanshuo Hao ◽  
Bin Wang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Laser Scanning ◽  
Low Cost ◽  
Pearson Correlation ◽  
Point Clouds ◽  
Larix Olgensis ◽  
Individual Tree ◽  
Profile Fitting ◽  
Aerial Vehicle ◽  
Individual Trees

Unmanned aerial vehicle (UAV) laser scanning, as an emerging form of near-ground light detection and ranging (LiDAR) remote sensing technology, is widely used for crown structure extraction due to its flexibility, convenience, and high point density. Herein, we evaluated the feasibility of using a low-cost UAV-LiDAR system to extract the fine-scale crown profile of Larix olgensis. Specifically, individual trees were isolated from LiDAR point clouds and then stratified from the point clouds of segmented individual tree crowns at 0.5 m intervals to obtain the width percentiles of each layer as profile points. Four equations (the parabola, Mitscherlich, power, and modified beta equations) were then applied to model the profiles of the entire and upper crown. The results showed that a region-based hierarchical cross-section analysis algorithm can successfully delineate 77.4% of the field-measured trees in high-density (>2400 trees/ha) forest stands. The crown profile generated with the 95th width percentile was adequate when compared with the predicted value of the existing field-based crown profile model (the Pearson correlation coefficient (ρ) was 0.864, root mean square error (RMSE) = 0.3354 m). The modified beta equation yielded slightly better results than the other equations for crown profile fitting and explained 85.9% of the variability in the crown radius for the entire crown and 87.8% of this variability for the upper crown. Compared with the cone and 3D convex hull volumes, the crown volumes predicted by our profile models had significantly smaller errors. The results revealed that the crown profile can be well described by using UAV-LiDAR, providing a novel way to obtain crown profile information without destructive sampling and showing the potential of the use of UAV-LiDAR in future forestry investigations and monitoring.

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