지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
오류제보하기
LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground to the sensor (Wehr & Lohr, 1999). Data from laser scanning can produce products such as digital elevation model (DEM), digital surface model (DSM) and the intensity data.
In Vietnam, the LIDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.
In Vietnam, the LIDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.
목차
Abstract
1. Introduction
2. Land cover classification methods using the intensity image
3. Experiment of land cover classification using intensity LiDAR data
4. Analysis and evaluation
5. Conclusion
References
참고문헌 (13)
참고문헌 신청
1. [학술지(정기간행물)] - Antonarakis, A / 2009 / bject-based land cover classification using airborne LiDAR / Remote Sensing of Environment : 2988 ~ 2998
2. [학술대회논문] - Barbarella, M / 2004 / Intergration of airborne laser data and high resolution satellite images over landslides risk areas / ISPRS Congress Istanbul 2004, Proceedings of Commission IV : 945 ~
3. [학술대회논문] - Díez, A. / 2008 / Fusion and Optimization of LiDAR and Photogrammetric Technologies and Methodologies for Cartographic Production / ISPRS Congress Beijing 2008 : 349 ~
4. [학술대회논문] - Garcia-Gutierreza, J / 2009 / Decision trees on LiDAR to classify land uses and covers / IAPRS Conference on Laserscanning09 : 323 ~ 328
5. [학술대회논문] - Hosomura, T. K / 1998 / Optical image data fusion by using intensity operation on HSI transformation / Geoscience and Remote Sensing Symposium Proceedings, IGARSS '98 : 1318 ~ 1319
2. [학술대회논문] - Barbarella, M / 2004 / Intergration of airborne laser data and high resolution satellite images over landslides risk areas / ISPRS Congress Istanbul 2004, Proceedings of Commission IV : 945 ~
3. [학술대회논문] - Díez, A. / 2008 / Fusion and Optimization of LiDAR and Photogrammetric Technologies and Methodologies for Cartographic Production / ISPRS Congress Beijing 2008 : 349 ~
4. [학술대회논문] - Garcia-Gutierreza, J / 2009 / Decision trees on LiDAR to classify land uses and covers / IAPRS Conference on Laserscanning09 : 323 ~ 328
5. [학술대회논문] - Hosomura, T. K / 1998 / Optical image data fusion by using intensity operation on HSI transformation / Geoscience and Remote Sensing Symposium Proceedings, IGARSS '98 : 1318 ~ 1319
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UCI(KEPA) : I410-ECN-0101-2014-530-003349593