Iterative processing of laser scanning data by full waveform analysis

Kirchhof, Michael; Jutzi, Boris; Stilla, Uwe

doi:10.1016/j.isprsjprs.2007.08.006

Cited by 32 publications

(16 citation statements)

References 18 publications

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“…The technical information relating to airborne laser scanners has been widely covered in abundant literatures such as (Wehr and Lohr 1999, Kirchhof 2008, and Petrie 2011, and there is no requirement to go in details here. Since the segmentation of the single tree from point cloud data is the key research in this project, the Airborne Laser Scanners (ALS) technology and its behaviour in vegetation canopy are briefly reviewed.…”

Section: A Brief Overview On Airborne Laser Scannersmentioning

confidence: 99%

New Approach for Segmentation and Extraction of Single Tree From Point Clouds Data and Aerial Images

Homainejad¹

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper addresses a new approach for reconstructing a 3D model from single trees via Airborne Laser Scanners (ALS) data and aerial images. The approach detects and extracts single tree from ALS data and aerial images. The existing approaches are able to provide bulk segmentation from a group of trees; however, some methods focused on detection and extraction of a particular tree from ALS and images. Segmentation of a single tree within a group of trees is mostly a mission impossible since the detection of boundary lines between the trees is a tedious job and basically it is not feasible. In this approach an experimental formula based on the height of the trees was developed and applied in order to define the boundary lines between the trees. As a result, each single tree was segmented and extracted and later a 3D model was created. Extracted trees from this approach have a unique identification and attribute. The output has application in various fields of science and engineering such as forestry, urban planning, and agriculture. For example in forestry, the result can be used for study in ecologically diverse, biodiversity and ecosystem.

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Section: A Brief Overview On Airborne Laser Scannersmentioning

confidence: 99%

New Approach for Segmentation and Extraction of Single Tree From Point Clouds Data and Aerial Images

Homainejad¹

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Most of studies in object extraction from Laser Scanning data have been focused on the signal processing or mathematical modelling which has been developed based on parameters of orientation of Laser Scanner beam with the surface of the object. For example, Silván-Cárdenas and Wang (2006) implemented Multiscale Hermit Transform (MHT) due to decompose signal for profiling the surface of terrain, or Kirchhof et al (2008) and Bae et al (2009) independently developed a mathematical model for object extraction from the point clouds based on parameters of orientation of Laser Scanner beam with the terrain. Since the provided point clouds from the terrain for this project did not include any pre-knowledge regarding to parameters of Laser Scanner orientation and received waveform, a few operators were developed and implemented for detecting and extracting interest objects from the point clouds or DTM which was developed from the point clouds, but only two of them will be discussed here.…”

Section: Background and Proposalmentioning

confidence: 99%

An Innovation Approach for Developing a 3d Model by Registering a Mono Image on a DTM

Homainejad

2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper is reflecting a study on developing and reconstructing a 3D model from registering an aerial image on a point clouds or a DTM. The point clouds has been chosen as the main data for reconstructing a 3D model. For achieving the aspects of the study, all objects were individually detected and extracted from the point clouds and captured in a particular layer in a CAD environment. Then each object will be converted to a raster format and will be registered on the image. This process is called the reverse registration in this study. Since the object segmentation and detection from a digital image is a complex process, the reverse registration is implemented in order to assist the process of the object detection from the image. This paper will discuss two methods of object detection from point clouds for the reverse registration. These methods were proposed and implemented for this study. Also, the paper will discuss the reverse registration and how this method improves the process of the object detection and extraction from the image. Discussion of reconstructing a 3D model from registering the digital image on a DTM or DSM (both of which developed from the point clouds data) is another goal of this paper.

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“…Indeed, the FWHM of undervegetation ground points may have been modified by the complex optical medium. These investigations have been performed on simulated waveforms reflected by a tilted planar surface (Kirchhof et al, 2008). The simulation consists in a temporal convolution product between the emitted laser pulse chosen of Gaussian shape, the impulse response of the receiver, the spatial beam profile and the illuminated area.…”

Section: Orthoimagesmentioning

confidence: 99%

Terrain surfaces and 3-D landcover classification from small footprint full-waveform lidar data: application to badlands

Bretar

Chauve

Bailly

et al. 2009

Hydrol. Earth Syst. Sci.

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Abstract. This article presents the use of new remote sensing data acquired from airborne full-waveform lidar systems for hydrological applications. Indeed, the knowledge of an accurate topography and a landcover classification is a prior knowledge for any hydrological and erosion model. Badlands tend to be the most significant areas of erosion in the world with the highest erosion rate values. Monitoring and predicting erosion within badland mountainous catchments is highly strategic due to the arising downstream consequences and the need for natural hazard mitigation engineering.Additionally, beyond the elevation information, fullwaveform lidar data are processed to extract the amplitude and the width of echoes. They are related to the target reflectance and geometry. We will investigate the relevancy of using lidar-derived Digital Terrain Models (DTMs) and the potentiality of the amplitude and the width information for 3-D landcover classification. Considering the novelty and the complexity of such data, they are presented in details as well as guidelines to process them. The morphological validation of DTMs is then performed via the computation of hydrological indexes and photo-interpretation. Finally, a 3-D landcover classification is performed using a Support Vector Machine classifier. The use of an ortho-rectified optical image in the classification process as well as full-waveform lidar data for hydrological purposes is finally discussed.

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Iterative processing of laser scanning data by full waveform analysis

Cited by 32 publications

References 18 publications

New Approach for Segmentation and Extraction of Single Tree From Point Clouds Data and Aerial Images

New Approach for Segmentation and Extraction of Single Tree From Point Clouds Data and Aerial Images

An Innovation Approach for Developing a 3d Model by Registering a Mono Image on a DTM

Terrain surfaces and 3-D landcover classification from small footprint full-waveform lidar data: application to badlands

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