Generation of digital terrain model from multispectral LiDar using different ground filtering techniques

Ali, Mahmoud El Nokrashy O.; Taha, Lamyaa Gamal El-deen; Mohamed, Mostafa; Mandouh, A

doi:10.1016/j.ejrs.2020.12.004

Cited by 12 publications

(6 citation statements)

References 12 publications

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“…Recently, Ali et al [ 132 ] proposed the idea of generating DTM from MSL data. They extracted DTM from each channel of the Optech Titan MSL sensor separately and made a comparison between them.…”

Section: Multispectral Lidar Applicationsmentioning

confidence: 99%

Multispectral Light Detection and Ranging Technology and Applications: A Review

Takhtkeshha,

Mandlburger,

Remondino

et al. 2024

Sensors

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Light Detection and Ranging (LiDAR) is a well-established active technology for the direct acquisition of 3D data. In recent years, the geometric information collected by LiDAR sensors has been widely combined with optical images to provide supplementary spectral information to achieve more precise results in diverse remote sensing applications. The emergence of active Multispectral LiDAR (MSL) systems, which operate on different wavelengths, has recently been revolutionizing the simultaneous acquisition of height and intensity information. So far, MSL technology has been successfully applied for fine-scale mapping in various domains. However, a comprehensive review of this modern technology is currently lacking. Hence, this study presents an exhaustive overview of the current state-of-the-art in MSL systems by reviewing the latest technologies for MSL data acquisition. Moreover, the paper reports an in-depth analysis of the diverse applications of MSL, spanning across fields of “ecology and forestry”, “objects and Land Use Land Cover (LULC) classification”, “change detection”, “bathymetry”, “topographic mapping”, “archaeology and geology”, and “navigation”. Our systematic review uncovers the potentials, opportunities, and challenges of the recently emerged MSL systems, which integrate spatial–spectral data and unlock the capability for precise multi-dimensional (nD) mapping using only a single-data source.

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Section: Multispectral Lidar Applicationsmentioning

confidence: 99%

Multispectral Light Detection and Ranging Technology and Applications: A Review

Takhtkeshha,

Mandlburger,

Remondino

et al. 2024

Sensors

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“…However, these levees are frequently subjected to damage from flood erosion, human activities, and natural subsidence, which collectively heighten their susceptibility to structural failure. Potential breaches in these defenses pose severe risks of casualties and economic losses [6][7][8][9][10]. The Pearl River Delta, one of South China's most densely populated regions, is distinguished by its low-lying topography and intricate river networks.…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Levee Deformation for Urban Flood Risk Management Using Airborne 3D Point Clouds

Wang,

Liao

et al. 2024

Water

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In the low-lying, river-rich Pearl River Delta in South China, an extensive network of flood defense levees, spanning over 4400 km, plays a crucial role in urban flood management. These levees are designed to withstand floods and storm surges, yet their failure can lead to significant human and economic losses, highlighting the need for robust urban flood defense strategies. This necessitates the development of a sophisticated geographic information system for the levee network and rapid, accurate assessment methods for levee conditions to support water management and flood mitigation efforts. This study focuses on the levees along the Hengmen waterway in the Pearl River Delta, utilizing airborne Light Detection and Ranging (LiDAR) technology to gather 3D spatial data of the levees. Employing the Cloth Simulation Filter (CSF) algorithm, non-ground point cloud data were extracted. The study improved upon the region-growing algorithm, using a seed point set approach for the automatic extraction of levee point cloud data. The accuracy and completeness of levee extraction were evaluated using the quality index. This method achieved effective extraction of four levee types, showing significant improvements over traditional algorithms, with extraction quality ranging from 72% to 83%. Key research outcomes include the development of a novel method for detecting localized levee depressions based on the computation of the variance of angles between normal vectors in single-phase levee point cloud data. An adaptive optimal neighborhood approach was utilized to accurately determine the normal vectors, effectively representing the local morphology of the levee point clouds. Applied in three levee depression detection experiments, this method proved effective, demonstrating the capability of single-phase data in identifying regions of levee depression deformation. This advancement in levee monitoring technology marks a significant step forward in enhancing urban flood defense capabilities in regions such as the cities of the Pearl River Delta in China.

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“…It is now possible, thanks to the multispectral Lidar system, to obtain the geometric and spectral information of the ground features faster and accurately at the same time without data fusion. This is because of the system's ability to collect information in multiple spectral bands [5]. Multispectral lidar also offers four Number Of Returns (NOR) instead of the one return provided by single-wavelength lidar.…”

Section: Introductionmentioning

confidence: 99%

The Potential of Multispectral Lidar for Building Extraction in a Complex Urban Area Using CANUPO Algorithm

Mandouh,

Ali,

Mohamed

et al. 2023

Journal of Al-Azhar University Engineering Sector

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The process of extracting buildings from remotely sensed data is essential for various applications such as 3D building modeling, city planning, disaster evaluation, and updating digital maps and GIS databases. The primary focus of this study is to examine how well multi-spectral lidar can extract individual buildings in dense urban environments. Recently developed remote sensing technologies include multi-spectral lidar. The primary lidar only uses one wavelength (NIR), while this newer gadget combines three wavelengths (NIR, MID, and Green) for more comprehensive data. This study evaluated multi-spectral lidar's effectiveness in extracting buildings from metropolitan regions under two different scenarios. The first scenario, which is a simplification of the single-wavelength lidar, utilized the initial return from the NIR alone. Since each wavelength of multispectral lidar contains four numbers of returns, they were combined to form a single dataset for the second scenario. The data underwent a filtration process to distinguish between ground and non-ground points, enhancing the building extraction's efficacy in both scenarios. The two scenarios in the CANUPO algorithm were executed using open-source software cloud-compare. This method utilizes multiscale dimensions to attain high-quality results while ensuring ground objects' safety. Eigenvalues were computed for all data points using varying scales ranging from 10m to 100m. The findings indicate that the second scenario, utilizing the spectral diversity of multispectral lidar for more efficient extraction of building points compared to the first scenario, resulted in a 95% improvement in balanced accuracy.

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Generation of digital terrain model from multispectral LiDar using different ground filtering techniques

Cited by 12 publications

References 12 publications

Multispectral Light Detection and Ranging Technology and Applications: A Review

Multispectral Light Detection and Ranging Technology and Applications: A Review

Monitoring of Levee Deformation for Urban Flood Risk Management Using Airborne 3D Point Clouds

The Potential of Multispectral Lidar for Building Extraction in a Complex Urban Area Using CANUPO Algorithm

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