Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 673-678 |
| Seitenumfang | 6 |
| Fachzeitschrift | Journal of the Indian Society of Remote Sensing |
| Jahrgang | 42 |
| Ausgabenummer | 3 |
| Frühes Online-Datum | 7 Feb. 2014 |
| Publikationsstatus | Veröffentlicht - Sept. 2014 |
Abstract
Classification of Mobile Mapping LiDAR (Light Detection and Ranging) data is a challenge in the research community since the day when laser scanner system were integrated and mounted on vehicles for collection of 3D data in urban environment. The approach proposed here for classifying LiDAR data is analogous to the process followed for classifying data from satellite images. Pixel based and segmentation based methods have been employed in past for classifying images obtained from satellites. These methods were based on spectral properties of objects present in the images. But for Mobile mapping LiDAR data this approach has been applied and tested for the first time. The properties of this data are completely different from that of satellite images. So even if the basic approach remains the same, many changes have to be made in the entire classification process. The paper here aims to propose the basic procedure of using pixel-wise classification on dense 3D LiDAR data.
ASJC Scopus Sachgebiete
- Sozialwissenschaften (insg.)
- Geografie, Planung und Entwicklung
- Erdkunde und Planetologie (insg.)
- Erdkunde und Planetologie (sonstige)
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in: Journal of the Indian Society of Remote Sensing, Jahrgang 42, Nr. 3, 09.2014, S. 673-678.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - A New Approach to 3D Dense LiDAR Data Classification in Urban Environment
AU - Chauhan, Inshu
AU - Brenner, Claus
AU - Garg, R. D.
AU - Parida, M.
PY - 2014/9
Y1 - 2014/9
N2 - Classification of Mobile Mapping LiDAR (Light Detection and Ranging) data is a challenge in the research community since the day when laser scanner system were integrated and mounted on vehicles for collection of 3D data in urban environment. The approach proposed here for classifying LiDAR data is analogous to the process followed for classifying data from satellite images. Pixel based and segmentation based methods have been employed in past for classifying images obtained from satellites. These methods were based on spectral properties of objects present in the images. But for Mobile mapping LiDAR data this approach has been applied and tested for the first time. The properties of this data are completely different from that of satellite images. So even if the basic approach remains the same, many changes have to be made in the entire classification process. The paper here aims to propose the basic procedure of using pixel-wise classification on dense 3D LiDAR data.
AB - Classification of Mobile Mapping LiDAR (Light Detection and Ranging) data is a challenge in the research community since the day when laser scanner system were integrated and mounted on vehicles for collection of 3D data in urban environment. The approach proposed here for classifying LiDAR data is analogous to the process followed for classifying data from satellite images. Pixel based and segmentation based methods have been employed in past for classifying images obtained from satellites. These methods were based on spectral properties of objects present in the images. But for Mobile mapping LiDAR data this approach has been applied and tested for the first time. The properties of this data are completely different from that of satellite images. So even if the basic approach remains the same, many changes have to be made in the entire classification process. The paper here aims to propose the basic procedure of using pixel-wise classification on dense 3D LiDAR data.
KW - Classification
KW - High volume 3D data
KW - LiDAR
KW - Principal component analysis
KW - Urban environment
UR - http://www.scopus.com/inward/record.url?scp=84893181053&partnerID=8YFLogxK
U2 - 10.1007/s12524-013-0354-4
DO - 10.1007/s12524-013-0354-4
M3 - Article
AN - SCOPUS:84893181053
VL - 42
SP - 673
EP - 678
JO - Journal of the Indian Society of Remote Sensing
JF - Journal of the Indian Society of Remote Sensing
SN - 0255-660X
IS - 3
ER -