Assessing the Usability of LiDAR Processing Methods on UAV Data

Horvat, Denis; Kobale, Dean; Zorec, Jan; Mongus, Domen; Žalik, Borut

doi:10.1109/csci.2016.0131

Cited by 2 publications

(2 citation statements)

References 17 publications

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“…The principle of DMP was proposed by Pesaresi and Benediktsson [58]. Although it was originally developed for segmentation and classification of high-resolution satellite images [58]- [60], its principle was also used for classifying ALS [61] and photogrammetric UAV point clouds [62].…”

Section: B Multi-scale Decomposition Of the Dtmsmentioning

confidence: 99%

Detecting Historical Terrain Anomalies With UAV-LiDAR Data Using Spline-Approximation and Support Vector Machines

Storch¹,

Lange²,

Jarmer³

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The documentation of historical remains and cultural heritage is of great importance to preserve historical knowledge. Many studies use low-resolution airplane-based laser scanning and manual interpretation for this purpose. In this study, a concept to automatically detect terrain anomalies in a historical conflict landscape using high-resolution UAV-LiDAR data was developed. We applied different ground filter algorithms and included a spline-based approximation step in order to improve the removal of low vegetation. Due to the absence of comprehensive labeled training data, a one-class support vector machine algorithm was used in an unsupervised manner in order to automatically detect the terrain anomalies. We applied our approach in a study site with different densities of low vegetation. The morphological ground filter was the most suitable when dense near-ground vegetation is present. However, with the use of the spline-based processing step, all filters used could be significantly improved in terms of the F1-score of the classification results. It increased by up to 42 percentage points in the area with dense low vegetation and by up to 14 percentage points in the area with sparse low vegetation. The completeness (recall) reached maximum values of 0.8 and 1.0, respectively, when taking into account the results leading to the highest F1score for each filter. Therefore, our concept can support on-site field prospection.

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Section: B Multi-scale Decomposition Of the Dtmsmentioning

confidence: 99%

Detecting Historical Terrain Anomalies With UAV-LiDAR Data Using Spline-Approximation and Support Vector Machines

Storch¹,

Lange²,

Jarmer³

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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show abstract

“…The POS is used to provide the position and attitude information and assist the highresolution imaging. The main types of sensors used for UAV remote sensing include aerial cameras, airborne LiDAR (Horvat et al 2016), hyperspectral imagers (Zhong et al 2018), infrared thermal imager, and small Synthetic Aperture Radar (SAR) (Guerreiro et al 2017). In the case of UAV flight, the inertial stabilization platform is applied to ensure the stability of remote sensing sensors by absorbing and smoothing the mechanical jitter during flight.…”

Section: Uav Sub-systemmentioning

confidence: 99%