Land cover classification using LiDAR intensity data and neural network
Land cover classification using LiDAR intensity data and neural network
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DOI：
10.7848/ksgpc.2011.29.4.429
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发表时间：
2011-08
期刊：
影响因子：
--
通讯作者：
N. Minh;La Phu Hien
中科院分区：
文献类型：
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作者：
N. Minh;La Phu Hien
激光雷达技术是激光测距、卫星定位技术和数字图像技术的结合，用于高精度地研究和确定3D真实地球表面特征。激光扫描数据通常是地面上的点云，包括从地面上的物体到传感器的激光的坐标、高度和强度（Wehr & Lohr，1999）。激光扫描的数据可以产生数字高程模型（DEM）、数字表面模型（DSM）和强度数据等产品。在越南，激光雷达技术自2005年以来一直在应用。然而，激光雷达在越南的应用主要是拓扑映射和DEM建立使用点云三维坐标。在这项研究中，激光雷达数据的另一个应用。本研究以碧江市为研究对象，利用强度影像联合收割机与其他数据集（高程数据、全色影像、RGB影像），利用神经网络方法进行土地覆盖分类。结果表明，它是可能的，从激光雷达数据获得的土地覆盖类。然而，使用LiDAR数据与其他数据集可以获得最高精度的分类，并且神经网络分类更适合于传统方法，例如最大似然分类。
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.