ACCURATE REGISTRATION OF AERIAL IMAGES AND ALS-POINTCLOUD VIA AUTOMATED JUNCTION MATCHING AND PLANAR CONSTRAINTS

Abstract. Accurate geometric registration of images and pointclouds is the key step of many 3D-reconstruction or 3D-sensing tasks. In this paper, a novel L-junction based approach is proposed for semi-automatic accurate registration of aerial images and the airborne laser scanning (ALS) point-cloud in urban areas. The approach achieves accurate registration by associating the LiDAR points with the local planes extracted via L-junction detection and matching from multi-view aerial images. An L-junction is an intersection of two line-segments. Through the forward intersection of multi-view corresponding L-junctions, an accurate local junction-plane can be obtained. In the proposed approach, L-junction is manually collected from one view on the flat object-surfaces like walls, roads, and roofs and then automatically matched to other views with the aid of epipolar-geometry and vanishing-point constraints. Then, a plane-constrained bundle block adjustment of the image-orientation parameters is conducted, where the LiDAR points are treated as reference data. The proposed approach was tested with two datasets collected in Guangzhou city and Ningbo city of China. The experimental results showed that the proposed approach had better accuracy than the closest-point based method. The horizontal/vertical registration RMS of the proposed approach reached 4.21cm/5.72cm in Guangzhou dataset and 4.46cm/4.34cm in Ningbo dataset, which was much less than the average LiDAR-point distance (over 25cm in both datasets) and was very close to the image GSDs (3.2cm in Guangzhou and 4.8cm in Ningbo) and the a-priori ranging accuracy of the ALS equipment (about 3cm).

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The Problem of Using and Measurement of Identifiable Ground Control Points on High Resolution Aerial Images

Archives of Photogrammetry, Cartography and Remote Sensing ◽

10.2478/apcrs-2019-0009 ◽

2019 ◽

Vol 31 (1) ◽

pp. 135-144

Author(s):

Zdzisław Kurczyński ◽

Krzysztof Bakuła ◽

Magdalena Pilarska ◽

Wojciech Ostrowski

Keyword(s):

High Resolution ◽

Urban Areas ◽

Aerial Images ◽

Control Points ◽

Linear Type ◽

Ground Control Points ◽

The Cost ◽

Image Orientation ◽

Point Type ◽

Selection Of

Abstract This paper shows the influence of the selection of photogrammetric control points as natural, identifiable points instead of signalized, premarked control points on the results of aerial triangulation of high-resolution aerial images with GSD below 10 cm. In the experiment, different selections of controls were tested using point-type and linear-type points with measurement of their centre or corner. In the experiment, 2 blocks with GSD of 5 and 10 cm were selected using the same measurements in 4 tested approaches with sets of natural identifiable points used by comparing the result with the reference variant. The experiment proves the possibility of using natural controls instead of premarked controls for images of urban areas. This can significantly reduce the cost of photogrammetric missions in urban areas where it is easy to find uniquely identifiable control points that can be used for image orientation.

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SECOND ITERATION OF PHOTOGRAMMETRIC PIPELINE TO ENHANCE THE ACCURACY OF IMAGE POSE ESTIMATION

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-1-w1-225-2017 ◽

2017 ◽

Vol XLII-1/W1 ◽

pp. 225-230 ◽

Cited By ~ 1

Author(s):

T. G. Nguyen ◽

M. Pierrot-Deseilligny ◽

J.-M. Muller ◽

C. Thom

Keyword(s):

Pose Estimation ◽

3D Model ◽

A Priori ◽

Aerial Images ◽

Processing Pipeline ◽

Multiple Case ◽

Multiple Case Studies ◽

Image Orientation ◽

Orientation Parameters

In classical photogrammetric processing pipeline, the automatic tie point extraction plays a key role in the quality of achieved results. The image tie points are crucial to pose estimation and have a significant influence on the precision of calculated orientation parameters. Therefore, both relative and absolute orientations of the 3D model can be affected. By improving the precision of image tie point measurement, one can enhance the quality of image orientation. The quality of image tie points is under the influence of several factors such as the multiplicity, the measurement precision and the distribution in 2D images as well as in 3D scenes. In complex acquisition scenarios such as indoor applications and oblique aerial images, tie point extraction is limited while only image information can be exploited. Hence, we propose here a method which improves the precision of pose estimation in complex scenarios by adding a second iteration to the classical processing pipeline. The result of a first iteration is used as a priori information to guide the extraction of new tie points with better quality. Evaluated with multiple case studies, the proposed method shows its validity and its high potiential for precision improvement.

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PHOTOGRAMMETRIC POINT CLOUDS GENERATION IN URBAN AREAS FROM INTEGRATED IMAGE MATCHING AND SEGMENTATION

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-2-w4-279-2017 ◽

2017 ◽

Vol IV-2/W4 ◽

pp. 279-285

Author(s):

L. Ye ◽

B. Wu

Keyword(s):

High Resolution ◽

Image Matching ◽

Urban Areas ◽

Laser Scanning ◽

Tall Buildings ◽

Point Clouds ◽

Aerial Images ◽

High Resolution Imagery ◽

Dense Matching ◽

High Resolution Satellite Images

High-resolution imagery is an attractive option for surveying and mapping applications due to the advantages of high quality imaging, short revisit time, and lower cost. Automated reliable and dense image matching is essential for photogrammetric 3D data derivation. Such matching, in urban areas, however, is extremely difficult, owing to the complexity of urban textures and severe occlusion problems on the images caused by tall buildings. Aimed at exploiting high-resolution imagery for 3D urban modelling applications, this paper presents an integrated image matching and segmentation approach for reliable dense matching of high-resolution imagery in urban areas. The approach is based on the framework of our existing self-adaptive triangulation constrained image matching (SATM), but incorporates three novel aspects to tackle the image matching difficulties in urban areas: 1) occlusion filtering based on image segmentation, 2) segment-adaptive similarity correlation to reduce the similarity ambiguity, 3) improved dense matching propagation to provide more reliable matches in urban areas. Experimental analyses were conducted using aerial images of Vaihingen, Germany and high-resolution satellite images in Hong Kong. The photogrammetric point clouds were generated, from which digital surface models (DSMs) were derived. They were compared with the corresponding airborne laser scanning data and the DSMs generated from the Semi-Global matching (SGM) method. The experimental results show that the proposed approach is able to produce dense and reliable matches comparable to SGM in flat areas, while for densely built-up areas, the proposed method performs better than SGM. The proposed method offers an alternative solution for 3D surface reconstruction in urban areas.

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AUTOMATIC FEATURE DETECTION, DESCRIPTION AND MATCHING FROM MOBILE LASER SCANNING DATA AND AERIAL IMAGERY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b1-609-2016 ◽

2016 ◽

Vol XLI-B1 ◽

pp. 609-616

Author(s):

Zille Hussnain ◽

Sander Oude Elberink ◽

George Vosselman

Keyword(s):

Urban Areas ◽

Laser Scanning ◽

Feature Detection ◽

Image Resolution ◽

Aerial Images ◽

Image Feature ◽

Aerial Image ◽

Feature Points ◽

Data Set ◽

Feature Extraction Method

In mobile laser scanning systems, the platform’s position is measured by GNSS and IMU, which is often not reliable in urban areas. Consequently, derived Mobile Laser Scanning Point Cloud (MLSPC) lacks expected positioning reliability and accuracy. Many of the current solutions are either semi-automatic or unable to achieve pixel level accuracy. We propose an automatic feature extraction method which involves utilizing corresponding aerial images as a reference data set. The proposed method comprise three steps; image feature detection, description and matching between corresponding patches of nadir aerial and MLSPC ortho images. In the data pre-processing step the MLSPC is patch-wise cropped and converted to ortho images. Furthermore, each aerial image patch covering the area of the corresponding MLSPC patch is also cropped from the aerial image. For feature detection, we implemented an adaptive variant of Harris-operator to automatically detect corner feature points on the vertices of road markings. In feature description phase, we used the LATCH binary descriptor, which is robust to data from different sensors. For descriptor matching, we developed an outlier filtering technique, which exploits the arrangements of relative Euclidean-distances and angles between corresponding sets of feature points. We found that the positioning accuracy of the computed correspondence has achieved the pixel level accuracy, where the image resolution is 12cm. Furthermore, the developed approach is reliable when enough road markings are available in the data sets. We conclude that, in urban areas, the developed approach can reliably extract features necessary to improve the MLSPC accuracy to pixel level.

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AUTOMATIC FEATURE DETECTION, DESCRIPTION AND MATCHING FROM MOBILE LASER SCANNING DATA AND AERIAL IMAGERY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b1-609-2016 ◽

2016 ◽

Vol XLI-B1 ◽

pp. 609-616 ◽

Cited By ~ 7

Author(s):

Zille Hussnain ◽

Sander Oude Elberink ◽

George Vosselman

Keyword(s):

Urban Areas ◽

Laser Scanning ◽

Feature Detection ◽

Image Resolution ◽

Aerial Images ◽

Image Feature ◽

Aerial Image ◽

Feature Points ◽

Data Set ◽

Feature Extraction Method

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ACCURACY OF MEASUREMENTS IN OBLIQUE AERIAL IMAGES FOR URBAN ENVIRONMENT

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w2-79-2016 ◽

2016 ◽

Vol XLII-2/W2 ◽

pp. 79-85 ◽

Cited By ~ 5

Author(s):

W. Ostrowski

Keyword(s):

Urban Areas ◽

Aerial Images ◽

Exterior Orientation ◽

Digital Elevation ◽

Accuracy Of Measurements ◽

Gps Rtk ◽

Accuracy Check ◽

Elevation Model ◽

Oblique Images ◽

Image Orientation

Oblique aerial images have been a source of data for urban areas for several years. However, the accuracy of measurements in oblique images during this time has been limited to a single meter due to the use of direct -georeferencing technology and the underlying digital elevation model. Therefore, oblique images have been used mostly for visualization purposes. This situation changed in recent years as new methods, which allowed for a higher accuracy of exterior orientation, were developed. Current developments include the process of determining exterior orientation and the previous but still crucial process of tie point extraction. Progress in this area was shown in the ISPRS/EUROSDR Benchmark on Multi-Platform Photogrammetry and is also noticeable in the growing interest in the use of this kind of imagery. The higher level of accuracy in the orientation of oblique aerial images that has become possible in the last few years should result in a higher level of accuracy in the measurements of these types of images. The main goal of this research was to set and empirically verify the accuracy of measurements in oblique aerial images. The research focused on photogrammetric measurements composed of many images, which use a high overlap within an oblique dataset and different view angles. During the experiments, two series of images of urban areas were used. Both were captured using five DigiCam cameras in a Maltese cross configuration. The tilt angles of the oblique cameras were 45 degrees, and the position of the cameras during flight used a high grade GPS/INS navigation system. The orientation of the images was set using the Pix4D Mapper Pro software with both measurements of the in-flight camera position and the ground control points (measured with GPS RTK technology). To control the accuracy, check points were used (which were also measured with GPS RTK technology). As reference data for the whole study, an area of the city-based map was used. The archived results were referred to image orientation accuracy and to the ground sampling distance of the used images. The results show that the recent development of image orientation methods for oblique aerial images allow these images to be used for high quality photogrammetric measurements.

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Urban Vulnerability Assessment for Pandemic Surveillance—The COVID-19 Case in Bogotá, Colombia

Sustainability ◽

10.3390/su13063402 ◽

2021 ◽

Vol 13 (6) ◽

pp. 3402

Author(s):

Jeisson Prieto ◽

Rafael Malagón ◽

Jonatan Gomez ◽

Elizabeth León

Keyword(s):

Vulnerability Assessment ◽

Disease Transmission ◽

Urban Areas ◽

A Priori ◽

Vulnerability Index ◽

Past Century ◽

Vulnerability Factors ◽

Early Assessment ◽

Global Citizens ◽

Urban Vulnerability

A pandemic devastates the lives of global citizens and causes significant economic, social, and political disruption. Evidence suggests that the likelihood of pandemics has increased over the past century because of increased global travel and integration, urbanization, and changes in land use with a profound affectation of society–nature metabolism. Further, evidence concerning the urban character of the pandemic has underlined the role of cities in disease transmission. An early assessment of the severity of infection and transmissibility can help quantify the pandemic potential and prioritize surveillance to control highly vulnerable urban areas in pandemics. In this paper, an Urban Vulnerability Assessment (UVA) methodology is proposed. UVA investigates various vulnerability factors related to pandemics to assess the vulnerability in urban areas. A vulnerability index is constructed by the aggregation of multiple vulnerability factors computed on each urban area (i.e., urban density, poverty index, informal labor, transmission routes). This methodology is useful in a-priori evaluation and development of policies and programs aimed at reducing disaster risk (DRR) at different scales (i.e., addressing urban vulnerability at national, regional, and provincial scales), under diverse scenarios of resources scarcity (i.e., short and long-term actions), and for different audiences (i.e., the general public, policy-makers, international organizations). The applicability of UVA is shown by the identification of high vulnerable areas based on publicly available data where surveillance should be prioritized in the COVID-19 pandemic in Bogotá, Colombia.

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Archaeological Surveying of Subarctic and Arctic Landscapes: Comparing the Performance of Airborne Laser Scanning and Remote Sensing Image Data

Sustainability ◽

10.3390/su13041917 ◽

2021 ◽

Vol 13 (4) ◽

pp. 1917

Author(s):

Alma Elizabeth Thuestad ◽

Ole Risbøl ◽

Jan Ingolf Kleppe ◽

Stine Barlindhaug ◽

Elin Rose Myrvoll

Keyword(s):

Remote Sensing ◽

Laser Scanning ◽

Digital Terrain Model ◽

Image Data ◽

Remote Sensing Image ◽

Airborne Laser Scanning ◽

Aerial Images ◽

Detection Rates ◽

Airborne Laser ◽

Pros And Cons

What can remote sensing contribute to archaeological surveying in subarctic and arctic landscapes? The pros and cons of remote sensing data vary as do areas of utilization and methodological approaches. We assessed the applicability of remote sensing for archaeological surveying of northern landscapes using airborne laser scanning (LiDAR) and satellite and aerial images to map archaeological features as a basis for (a) assessing the pros and cons of the different approaches and (b) assessing the potential detection rate of remote sensing. Interpretation of images and a LiDAR-based bare-earth digital terrain model (DTM) was based on visual analyses aided by processing and visualizing techniques. 368 features were identified in the aerial images, 437 in the satellite images and 1186 in the DTM. LiDAR yielded the better result, especially for hunting pits. Image data proved suitable for dwellings and settlement sites. Feature characteristics proved a key factor for detectability, both in LiDAR and image data. This study has shown that LiDAR and remote sensing image data are highly applicable for archaeological surveying in northern landscapes. It showed that a multi-sensor approach contributes to high detection rates. Our results have improved the inventory of archaeological sites in a non-destructive and minimally invasive manner.

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Evaluation of Community Resilience in Rural China—Taking Licheng Subdistrict, Guangzhou as an Example

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18115827 ◽

2021 ◽

Vol 18 (11) ◽

pp. 5827

Author(s):

Jianhong Fan ◽

You Mo ◽

Yunnan Cai ◽

Yabo Zhao ◽

Dongchen Su

Keyword(s):

Spatial Distribution ◽

Rural Communities ◽

Rural Areas ◽

Urban Areas ◽

Rural China ◽

Social Resilience ◽

Learning Abilities ◽

The Sustainable Development ◽

Guangzhou City ◽

Local Sustainability

Resilience of rural communities is becoming increasingly important to contemporary society. In this study we used a quantitative method to measure the resilience regulating ability of rural communities close to urban areas—in Licheng Subdistrict, Guangzhou City, China. The main results are as follows: (1) Rural systems close to urban areas display superior adapting and learning abilities and have a stronger overall resilience strength, the spatial distribution of which is characterized by dispersion in whole and aggregation in part; (2) the resilience of most rural economic subsystems can reach moderate or higher levels with apparent spatial agglomeration, whilst the ecological subsystem resilience and social resilience are generally weaker; the spatial distribution of the former shows a greater regional difference while the latter is in a layered layout; (3) some strategies such as rebuilding a stable ecological pattern, making use of urban resources and cultivating rural subjectivity are proposed on this basis, in order to promote the sustainable development of rural areas and realize rural revitalization. This work also gives suggestion for the creation of appropriate and effective resilience standards specifically targeted for rural community-aiming to achieve the delivery of local sustainability goals.

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