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Towards a framework for point-cloud-based visual analysis of historic gardens: Jichang Garden as a case study

Peng, Y. (author), Zhang, Guanting (author), Nijhuis, S. (author), Agugiaro, G. (author), Stoter, J.E. (author)

Historic gardens, regarded as a significant genre of cultural heritage, encapsulate the enduring essence of bygone eras while concurrently transcending temporal boundaries to resonate with the present and future. These gardens provide us vitality and inspiration, holding a collective repository of human memory and serving as a testament to our...

journal article 2024

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Occupancy Grid Mapping for Automotive Driving Exploiting Clustered Sparsity

Önen, Çağan (author), Pandharipande, Ashish (author), Joseph, G. (author), Myers, N.J. (author)

Occupancy grid maps provide information about obstacles and available free space in the environment and are crucial in automotive driving applications. An occupancy map is constructed using point cloud data from sensor modalities such as light detection and ranging (LiDAR) and radar used for automotive perception. In this article, we...

journal article 2024

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Three-Dimensional Mapping of Habitats Using Remote-Sensing Data and Machine-Learning Algorithms

Amani, Meisam (author), Foroughnia, Fatemeh (author), Moghimi, Armin (author), Mahdavi, Sahel (author), Jin, Shuanggen (author)

Progress toward habitat protection goals can effectively be performed using satellite imagery and machine-learning (ML) models at various spatial and temporal scales. In this regard, habitat types and landscape structures can be discriminated against using remote-sensing (RS) datasets. However, most existing research in three-dimensional (3D)...

journal article 2023

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Distributed processing of Dutch AHN laser altimetry changes of the built-up area

Lindenbergh, R.C. (author), Cserép, Máté (author)

The evolution and spreading of data capturing methods ranging from simple GPS devices like smart-phones to large scale imaging equipment – including very high resolution and hyperspectral cameras and LiDAR – resulted in an exponential growth in the amount of spatial data maintained by companies and organizations. At the same time methods for...

journal article 2023

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Indoor localisation and location tracking in indoor facilities based on LiDAR point clouds and images of the ceilings

Dardavesis, Ioannis (author), Verbree, E. (author), Rafiee, A. (author)

Localisation and navigation technologies have vastly evolved during the last years, facilitating users’ guidance in various environments. Unlike outdoor environments where GNSS comprises a universal solution, in indoor environments various localisation techniques have been used, each one with its drawbacks. Thus, this research investigates the...

journal article 2023

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Towards a Practical Method for Voxel-based Visibility Analysis with Point Cloud Data for Landscape Architects: Jichang Garden (Wuxi, China) as an Example

Peng, Y. (author), Nijhuis, S. (author), Zhang, Guangting (author), Stoter, J.E. (author), Agugiaro, G. (author)

This paper focuses on GIS-based visibility analysis to explore landscape architecture com-positions as a means to understand visual-spatial characteristics and identify related design principles. More specifically, the paper elaborates a practical method to employ high-resolution data acquired by terrestrial LiDAR (Light Detection and Ranging or...

journal article 2022

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City3D: Large-Scale Building Reconstruction from Airborne LiDAR Point Clouds

Huang, J. (author), Stoter, J.E. (author), Peters, R.Y. (author), Nan, L. (author)

We present a fully automatic approach for reconstructing compact 3D building models from large-scale airborne point clouds. A major challenge of urban reconstruction from airborne LiDAR point clouds lies in that the vertical walls are typically missing. Based on the observation that urban buildings typically consist of planar roofs connected...

journal article 2022

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Semantic Scene Completion using Local Deep Implicit Functions on LiDAR Data

Rist, C.B. (author), Emmerichs, David (author), Enzweiler, Markus (author), Gavrila, D. (author)

Semantic scene completion is the task of jointly estimating 3D geometry and semantics of objects and surfaces within a given extent. This is a particularly challenging task on real-world data that is sparse and occluded. We propose a scene segmentation network based on local Deep Implicit Functions as a novel learning-based method for scene...

journal article 2022

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Realistic correction of sky-coloured points in Mobile Laser Scanning point clouds

González, Elena (author), Balado Frías, J. (author), Arias, Pedro (author), Lorenzo, Henrique (author)

The enrichment of the point clouds with colour images improves the visualisation of the data as well as the segmentation and recognition processes. Coloured point clouds are becoming increasingly common, however, the colour they display is not always as expected. Errors in the colouring of point clouds acquired with Mobile Laser Scanning are...

journal article 2022

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A Two-Step Feature Extraction Algorithm: Application to deep learning for point cloud classification

Nurunnabi, A. (author), Teferle, F. N. (author), Laefer, D. F. (author), Lindenbergh, R.C. (author), Hunegnaw, A. (author)

Most deep learning (DL) methods that are not end-to-end use several multi-scale and multi-type hand-crafted features that make the network challenging, more computationally intensive and vulnerable to overfitting. Furthermore, reliance on empirically-based feature dimensionality reduction may lead to misclassification. In contrast, efficient...

journal article 2022

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Airborne Laser Scanning Point Cloud Classification Using the DGCNN Deep Learning Method

Widyaningrum, E. (author), Bai, Q. (author), Fajari, Marda K. (author), Lindenbergh, R.C. (author)

Classification of aerial point clouds with high accuracy is significant for many geographical applications, but not trivial as the data are massive and unstructured. In recent years, deep learning for 3D point cloud classification has been actively developed and applied, but notably for indoor scenes. In this study, we implement the point-wise...

journal article 2021

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Point-based morphological opening with input data retrieval

Balado Frías, J. (author), van Oosterom, P.J.M. (author), Díaz-Vilarino, L. (author), Lorenzo, H. (author)

Mathematical morphology is a technique recently applied directly for point cloud data. Its working principle is based on the removal and addition of points from an auxiliary point cloud that acts as a structuring element. However, in certain applications within a more complex process, these changes to the original data represent an...

journal article 2021

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Investigation of pointnet for semantic segmentation of large-scale outdoor point clouds

Nurunnabi, A. (author), Teferle, F. N. (author), Li, J. (author), Lindenbergh, R.C. (author), Parvaz, S. (author)

Semantic segmentation of point clouds is indispensable for 3D scene understanding. Point clouds have credibility for capturing geometry of objects including shape, size, and orientation. Deep learning (DL) has been recognized as the most successful approach for image semantic segmentation. Applied to point clouds, performance of the many DL...

journal article 2021

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An efficient deep learning approach for ground point filtering in aerial laser scanning point clouds

Nurunnabi, A. (author), Teferle, F. N. (author), Li, J. (author), Lindenbergh, R.C. (author), Hunegnaw, A. (author)

Ground surface extraction is one of the classic tasks in airborne laser scanning (ALS) point cloud processing that is used for three-dimensional (3D) city modelling, infrastructure health monitoring, and disaster management. Many methods have been developed over the last three decades. Recently, Deep Learning (DL) has become the most dominant...

journal article 2021

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Semantic segmentation of mobile laser scanning point clouds with long short-term memory networks: Preliminary results

Balado Frías, J. (author), van Oosterom, P.J.M. (author), Díaz-Vilarino, L. (author), Arias, P. (author)

Although point clouds are characterized as a type of unstructured data, timestamp attribute can structure point clouds into scanlines and shape them into a time signal. The present work studies the transformation of the street point cloud into a time signal based on the Z component for the semantic segmentation using Long Short-Term Memory ...

journal article 2021

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Influence of spatial and temporal resolution on time series-based coastal surface change analysis using hourly terrestrial laser scans

Anders, K.P. (author), Winiwarter, L. (author), Mara, H. (author), Lindenbergh, R.C. (author), Vos, S.E. (author), Höfle, B. (author)

Near-continuously acquired terrestrial laser scanning (TLS) data contains valuable information on natural surface dynamics. An important step in geographic analyses is to detect different types of changes that can be observed in a scene. For this, spatiotemporal segmentation is a time series-based method of surface change analysis that...

journal article 2021

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Disturbance analysis in the classification of objects obtained from urban lidar point clouds with convolutional neural networks

Balado Frías, J. (author), Arias, Pedro (author), Lorenzo, Henrique (author), Meijide-Rodríguez, Adrián (author)

Mobile Laser Scanning (MLS) systems have proven their usefulness in the rapid and accurate acquisition of the urban environment. From the generated point clouds, street furniture can be extracted and classified without manual intervention. However, this process of acquisition and classification is not error-free, caused mainly by disturbances...

journal article 2021

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Cross-shore intertidal bar behavior along the dutch coast: Laser measurements and conceptual model

Vos, S.E. (author), Spaans, Lennard (author), Reniers, A.J.H.M. (author), Holman, Rob (author), McCall, Robert (author), de Vries, S. (author)

Intertidal bars are naturally occurring morphological features along the waterline of sandy beaches. Present quantitative knowledge on intertidal bar behavior is limited, due to the scarcity of data resources and the limitations of traditional survey techniques. To investigate and quantify the cross-shore morphologic behavior of intertidal...

journal article 2020

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Novel approach to automatic traffic sign inventory based on mobile mapping system data and deep learning

Balado Frías, J. (author), González, Elena (author), Arias, Pedro (author), Castro, David (author)

Traffic signs are a key element in driver safety. Governments invest a great amount of resources in maintaining the traffic signs in good condition, for which a correct inventory is necessary. This work presents a novel method for mapping traffic signs based on data acquired with MMS (Mobile Mapping System): images and point clouds. On the...

journal article 2020

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A new quantitative approach to tree attributes estimation based on LiDAR point clouds

Fan, Guangpeng (author), Nan, L. (author), Chen, Feixiang (author), Dong, Yanqi (author), Wang, Zhiming (author), Li, Hao (author), Chen, Danyu (author)

Tree-level information can be estimated based on light detection and ranging (LiDAR) point clouds. We propose to develop a quantitative structural model based on terrestrial laser scanning (TLS) point clouds to automatically and accurately estimate tree attributes and to detect real trees for the first time. This model is suitable for forest...

journal article 2020